Dissertations / Theses on the topic 'Virtual Power Plants'

The growing number of micro generation devices in the electrical network is leading many to consider that these devices can no longer be considered as fit and forget, but should instead be considered as having a demonstrable network impact which should be predicted and utilised. One of the techniques for considering the impacts of these devices is the Virtual Power Plant (VPP). The VPP is the aggregation of all the Distributed Generation (DG) connected into the network up to and including the connection voltage of the VPP, such that the cumulative power up the voltage levels can be seen in the single VPP unit, rather than across a broad spread of devices. One of the crucial tasks in characterising the VPP, developed in this work, is the ability to correctly predict and then aggregate the behaviour of several technology types which are weather driven, as a large proportion of DG is weather driven. Of this weather driven DG, some can only typically be dispatched with modification and the rest cannot be dispatched at all. The aggregation of the VPP as part of the electrical network is also developed, as the constraints of the network and the reliability of the network cannot be overlooked when considering the aggregation of the VPP. From a distribution network operator's (DNO) perspective, these characterisation models can be used to highlight problems in the network introduced by the addition of DG, but are also generally utilitarian in their role of predicting the power output (or negative load) found throughout the network due to DG. For a commercial agent interested in selling energy, these models allow for accurate predictions of energy to be determined for the trading period. A VPP agent would also be adversely affected by line failure in the network, leading to the development of an N-1 analysis based upon reliability rates of the network, which is used as the basis for a discussion on the impacts of single line failure and the mitigation available through feedback from the DNO.

I confini delle risorse di energia distribuita sono in continua espansione negli ultimi anni con conseguenti cambiamenti nella gestione ottimizzata di energia nelle Smart Grid per soddisfare la domanda di energia, apportare miglioramenti alle condizioni ambientali e minimizzare i prezzi. Per raggiungere questo obiettivo si utilizza un Virtual Power Plant con al suo interno un gestore di energia che coordina le unit`a distribuite relative al sistema di energia elettrico. Questo lavoro di tesi sviluppa un modello per la gestione energetica all’interno di un Virtual Power Plant per decidere come e con quali fonti energetiche soddisfare la domanda di energia elettrica. Le decisioni riguardanti le quantita` ed il tipo di risorse energetiche utilizzate ad intervalli orari nell’arco di una giornata avvengono dinamicamente e dipendono da fattori variabili provenienti dalla disponibilit`a delle risorse di energia rinnovabili, dal costo dell’energia elettrica acquistata dalla rete esterna, dal costo del diesel, dai carichi associati ad utenze domestiche e dalla possibilit`a di immagazzinare o rilasciare energia all’interno dell’unit`a di storage. La soluzione `e calcolata mediante l’utilizzo di una funzione costo minimizzata la quale prende in considerazione solo i costi diretti relativi all’impianto VPP. Le conclusioni teoriche e le aspettative sono verificate mediante una simulazione di uno scenario reale.

At present, conventional fossil fuels such as coal, petroleum and natural gas still remain dominant in electricity generation. Therefore, distributed energy resources (DERs) attract people's attention for being renewable and environmentally friendly and hence promotes the utilisation of DERs in electric power systems. This offers an opportunity to aggregate prosumers into virtual power plants (VPPs) operated as a single dispatchable resource. Yet that raises the question of how to financially reward prosumers for participating in VPPs. Against this backdrop, this thesis explores dynamic export tariffs based on the dual variables of the optimisation problem used for aggregation. In contrast to the existing approaches, we use a multi-period optimisation model to account for inter-temporal coupling introduced by battery storage systems, which can reflect prosumers' energy consumption behaviours and hence, have better performance to reward prosumers for exporting energy surplus back to the grid. The work begins with an introductory chapter, aiming to demonstrate the motivation, outline, and contribution of the research. Then, a literature review follows to demonstrate the necessity of the research. The thesis continues by presenting mathematical formulations for the VPP models and the proposed multi-period dynamic export tariff. Then, we use AMPL-MATLAB platform to simulate a VPP test system under the given operating parameters, aiming to investigate the efficacy of dynamic export tariffs on prosumers' electricity cost-saving participating in those VPPs from both financial and electrical aspects. Furthermore, the sensitivity analysis for the dynamic export tariff is implemented. The results demonstrate that the proposed multi-period dynamic export tariff can effectively reduce the current electricity cost of prosumers participating in VPPs.

In the current climate crisis, there is an increasing need for the integration of renewableenergy in higher penetration indexes, which is boosting innovation not only in the technology but also in new business models.  Virtual Power Plants (VPPs) are an aggregation model for generation that is said to be able to decrease imbalances from renewable generation while improving economic performance.  While the regulation in some countries still does not allow this type of activity there are also many others in which aggregation of demand and even VPPs are growing in numbers. This study aims to prove the previous statement and quantify the amount of imbalances that can be offset and the consequent penalties avoided for a VPP located  in  the  north  of  Portugal  composed  of  a  pumped-storage  hydro  plant  and  onshore wind generation.  In order to do so, two case studies have been compared:  a baseline case in which each unit is operated independently and another in which all the units are aggregated under the VPP model.  With this aim, a simplified bidding strategy has been simulated for both cases and three different error levels, to finally compare the results through four key performance indicators (KPIs):  increase in profit, increase revenues, decrease in imbalance and decrease in penalty cost.  The optimization problem was formulated as a mixed-integer linear programming (MILP) problem and it was carried out in two steps:  one for the day ahead session and a second for the intraday market.  It aims to diversify the generation port- folio of the hydro power plant and divide it among the available products:  energy sold in the day ahead market, capacity reserves for the secondary reserves, and energy sold as tertiary reserves.  It was decided to follow a deterministic approach, considering in the strategy a tree of scenarios and their associated probabilities.  In order to formulate this scenarios historical data was used, due to the high dependence between the market variables.  The results show that an average annual 16% decrease in energy deviations could be achieved which implies a 16.3% decrease in the penalty costs.  Moreover, it was also found that the combined oper- ation of the assets in the intraday market, together with the penalty reduction, would lead to a 1% increase in profit with a 0.1% decrease in revenues, concluding that a more detailed and data intensive model would be required to analyse the full advantage of the VPP modelwhen operating the assets together also during the day ahead session.
I den nuvarande klimatkrisen finns det ett ökande behov av integration av en högre andel förnybar energi, vilket ökar behovet av innovationer inte bara inom tekniken utan också i nya affärsmodeller. Virtuella kraftverk (Virtual Power Plants VPP) är en aggregeringsmodell för produktion som sägs kunna minska obalansen från förnybar produktion samtidigt somden förbättrar det ekonomiska utfallet. Ä ven om förordningen i vissa länder fortfarande intetillåter denna typ av verksamhet finns det också många andra där aggregering av efterfrågan och till och med VPP växer i antal. Denna studie syftar till att visa på nyttan av VPP och kvantifiera mängden obalanser som kan kompenseras och de orsakade obalans-kostnader som undviks för en VPP som ligger i norra Portugal som består av ett vattenkraftverk med pumplagring och vindkraft på land. För att göra det har två fallstudier jämförts: ett basfall där varje enhet drivs oberoende och en annan där alla enheterna är aggregerade enligt VPPmodellen. Med detta syfte har en förenklad budstrategi simulerats för båda fallen och tre olika nivåer på fel i prognoser för att slutligen kunna jämföra resultaten genom fyra olika indikatorer (KPI:er): vinstökning, ökning av intäkter, minskning av obalans och minskning av obalanskostnader. Optimeringsproblemet formulerades som ett mixed-linear-integer programmeringsproblem (MILP) och det genomfördes i två steg: ett för dagenföremarknaden och ett andra för intradagsmarknaden. Detta syftar till att diversifiera produktionsportföljen för vattenkraftverket och dela den mellan de tillgängliga produkterna: energi som säljs i den kommande marknaden, kapacitetsreserver för sekundära reserver och energi som säljs som tertiära reserver. I studien har vi valt en deterministisk strategi med beaktande av ett scenarioträd med respektive sannolikheter. För att formulera dessa scenarier användes historiska data på grund av den stora korrelationen mellan marknadsvariablerna. Resultaten visar att en genomsnittlig årlig minskning av energiavvikelserna med 16% skulle kunna uppnås vilket innebär en minskning av obalanskostnaderna med 16,3%. Dessutom konstaterades det att den kombinerade driften av tillgångarna på intradagsmarknaden, tillsammans med minskningen av obalanser, skulle leda till en vinstökning på 1% med en minskning av intäkterna på 0,1%, från vilket vi drar slutsatsen att en mer detaljerad och datakrävande modell skulle krävas för att analysera VPP-modellens fulla potential när mananvänder tillgångarna tillsammans även under dagenföremarknaden.

Electrical demand flexibility is a key component to enabling a low cost, low carbon grid. In this study, residential electricity demand and flexibility is explored from the lens of a virtual power plant operator. Individual and aggregate asset consumption is analysed using a pool of >10,000 household assets over 6 years. Key safety, comfort and availability limitations are identified per asset type. Pool flexibility is analysed using a combination of past data and principled calculations, with flexibility quantified for different products and methods of control. A machine learning model is built for a small pool of 200 assets, predicting consumption 24 hours in advance. Calculated flexibility and asset limitations are then used within an optimisation model, leveraging flexibility and combining the value of self consumption and day ahead price optimisation for a residential home.
Flexibilitet i efterfrågan av elektricitet är essentiellt för att möjliggöra ett elnät med låga kostnader och utsläpp. I denna studie undersöks elanvändning av en bostad samt flexibilitet i perspektiv från en virtuell kraftverksoperatör. Individuell och sammanlagd konsumtion analyseras genom tillgång av data från >10 000 bostäder över 6 år. Begränsningar av säkerhet, komfort och tillgänglighet identifieras per tillgångstyp. Sammanlagda flexibiliteten analyseras genom en kombination av tidigare data och principiella beräkningar, med flexibilitet kvantifierad för diverse produkter och kontrollmetoder. En modell för maskininlärning utvecklades för 200 bostäder och förutser konsumtion 24 timmar i förväg. Den beräknade flexibiliteten och tillgångsbegränsningar används sedan i en optimeringsmodell som utnyttjar flexibilitet och kombinerar värdet av självkonsumtion och optimerat pris för nästkommande dag för ett bostadshus.

Renewable energy resources are projected to claim a larger part of the Swedish power mix in coming years. This could potentially increase frequency fluctuations in the power grid due to the intermittency of renewable power generating resources. These fluctuations can in turn cause issues in the power grid if left unchecked. In order to resolve these issues, countermeasures are employed. One such countermeasure is for private actors to regulate power; in exchange they are financially compensated through reserve markets. The reserve market studied in this thesis is called Frequency Containment Reserve – Normal (FCR-N). Currently hydroelectric power provides almost all regulated power within this market. As the need for power regulation is expected to increase in the coming years, there exists a need to study other technologies capable of power regulation. This thesis focuses on one such technology called, virtual power plants. While virtual power plants are operating in other parts of the world, there were no virtual power plants operating in Sweden. As a result, the nature of an optimized virtual power plant and the economic benefits of optimization had not been previously investigated. To answer such questions, this thesis modelled and optimized the revenue of a virtual power plant. The examined virtual power plant consisted of cooling chillers, lighting, ventilation fans and a battery energy storage system. Where varying their total power demand allowed for them to provide power regulation. With the virtual power plant market in Sweden being in its infancy, this thesis serves as a first look into how an optimized virtual power plant using these components could function. To put the economic results of the optimization into context, a comparative model was constructed. The comparative model was based on a semi-static linear model. This is what the thesis’s industry partner Siemens currently uses. For the simulated scenarios, the optimized model generated at least 85% higher net revenues than the semi-static linear model. The increase in revenue holds potential to increase the uptake of virtual power plants on the Swedish market, thus increasing stability in the power grid and easing the transition to renewable energy.
Då förnyelsebara energiresurser antas omfatta en större roll av den svenska elproduktionen inom kommande år, så kan detta leda till att frekvensfluktueringar i elnätet ökar. Detta sker på grund av att den oregelbundna elproduktionen från förnyelsebara energiresurser inte matchas med konsumtion. Om dessa fluktueringar inte hanteras kan det i sin tur leda till skadliga störningar inom elnätet. För att motverka detta och således stabilisera elnätet används diverse lösningar. Ett sätt att åstadkomma ökad stabilisering i elnätet är att låta privata aktörer kraftreglera. De privata aktörerna som står för kraftregleringen gör detta i utbyte mot ekonomisk kompensation, genom att delta i reservmarknader. Den reservmarknad som studerades inom detta examensarbete kallas Frequency Containment Reserve – Normal (FCR-N). I nuläget står vattenkraft för nästan all reglerad kraft inom den här marknaden. Men då behovet av kraftreglering antas öka inom kommande år så behövs nya teknologier studeras som kan bistå med kraftregleringen. Den studerade teknologin inom detta examensarbete var ett virtuellt kraftverk. Då inga virtuella kraftverk var i bruk i Sverige då denna uppsats skrevs fanns det osäkerheter kring hur man optimalt styr ett virtuellt kraftverk och de ekonomiska fördelarna som detta skulle kunna leda till. Detta examensarbete modellerade och optimerade ett virtuellt kraftverk ur ett vinstperspektiv. Det virtuella kraftverket var uppbyggt utav kylmaskiner, ljus, ventilationsfläktar och ett batterisystem. Deras kraftkonsumtion styrdes på ett sådant sätt som lätt de bidra till kraftreglering på reservmarknaden. För att kunna analysera de ekonomiska resultaten från det optimerade virtuella kraftverket, så byggdes en jämförelsemodell. Denna jämförelsemodell är baserad på en semistatisk linjär modell, vilket är det som examensarbetets industripartner Siemens använder. Den ekonomiska jämförelsens resultat påvisade att inkomsten från den optimerade modellen var minst 85% högre än den semistatiskt linjära modellen, inom de studerade scenarierna. Denna inkomstökning skulle potentiellt kunna öka användningen av virtuella kraftverk på den svenska reservmarknaden vilket i sin tur skulle medföra högre stabilitet på elnätet. Genom att öka stabiliteten på elnätet kan således förnyelsebara energiresurser i sin tur lättare implementeras.

This report explores the impacts of variable renewable energy (VRE) on power trading in the European wholesale electricity market. The intricate operation of a typical power exchange in Europe is accompanied by an equally complex balancing system. The increasing amount of VRE in the power system, such as wind and solar power, has far-reaching impacts for power traders in both this electricity market and the corresponding balancing system. As a result, the electricity market is evolving in unprecedented ways and new participants are entering the playing field to capitalize on the changing dynamics caused by VRE generators. One novel participant, the virtual power plant (VPP), possesses an advantage over other market participants by aggregating VRE generators with controllable renewable energy generators, like biogas and hydro plants, into one entity. This allows the VPP to both gain access to live VRE production data that larger plants don’t have, which it then utilizes to remotely dispatch various subpools of assets, and to provide balancing services to the grid. Subsequently, VPPs are able to trade VRE and other renewable electricity superiorly on the same spot markets and balancing systems as large central power plants and industrial consumers. The report asserts that VPP traders can earn profits through means of innovative trading strategies that exploit predictable market impacts caused by VRE power through a robust understanding of the electricity market and their unique access to data.
Denna rapport undersöker effekterna av variabel förnybar energi (VRE) på krafthandeln på den europeiska elhandelsmarknaden för stora aktörer. Den komplicerade driften av ett typiskt kraftutbyte i Europa åtföljs av ett lika komplicerat balanseringssystem. Den ökande mängden VRE i kraftsystemet, såsom vind- och solkraft, har långtgående effekter för krafthandlare på både denna elmarknad och motsvarande balanseringssystem. Som ett resultat utvecklas elmarknaden på enastående sätt och nya deltagare kommer in på spelplanen för att dra nytta av den förändrade dynamiken som orsakas av VRE-generatorer. En ny spelare, det virtuella kraftverket (VPP), har en fördel jämfört med andra marknadsaktörer genom att samla VRE-generatorer med styrbara förnybara energiproducenter, som biogas och vattenkraftverk, till en enhet. Detta gör att VPP både kan få tillgång till live VRE-produktionsdata som större anläggningar inte har, som den sedan använder för att distribuera olika underpooler av tillgångar och för att tillhandahålla balanstjänster till nätet. Därefter kan VPP: er handla med VRE och annan förnybar el på ett överlägset sätt på samma spotmarknader och balanseringssystem som stora centrala kraftverk och industrikonsumenter. Rapporten visar att VPP-handlare kan göra vinster genom innovativa handelsstrategier som utnyttjar förutsägbara marknadseffekter orsakade av VRE-kraft genom en detaljerad förståelse för elmarknaden och unik tillgång till data för produktionen av förnybar energi

QC 20201118

During the last century, the electrical energy infrastructures have been governed by synchronous generators, producing electrical energy to the vast majority of the population worldwide. However, power systems are no longer what they used to be. During the last two decades of this new millennium the classical, centralized and hierarchical networks have experienced an intense integration of renewable energy sources, mainly wind and solar, thanks also to the evolution and development of power conversion and power electronics industry. Although the current electrical system was designed to have a core of generation power plants, responsible of producing the necessary energy to supply end users and a clear power flow, divided mainly into transmission and distribution networks, as well as scalable consumers connected at different levels, this scenario has dramatically changed with the addition of renewable generation units. The massive installation of wind and solar farms, connected at medium voltage networks, as well as the proliferation of small distributed generators interfaced by power converters in low voltage systems is changing the paradigm of energy generation, distribution and consumption. Despite the feasibility of this integration in the existing electrical network, the addition of these distributed generators made grid operators face new challenges, especially considering the stochastic profile of such energy producers. Furthermore, the replacement of traditional generation units for renewable energy sources has harmed the stability and the reliable response during grid contingencies. In order to cope with the difficult task of operating the electrical network, transmission system operators have increased the requirements and modified the grid codes for the newly integrated devices. In an effort to enable a more natural behavior of the renewable systems into the electrical grid, advanced control strategies were presented in the literature to emulate the behavior of traditional synchronous generators. These approaches focused mainly on the power converter relying on their local measurement points to resemble the operation of a traditional generating unit. However, the integration of those units into bigger systems, such as power plants, is still not clear as the effect of accumulating hundreds or thousands of units has not been properly addressed. In this regard, the work of this thesis deals with the study of the so-called virtual synchronous machine (VSM) in three control layers. Furthermore, an in-depth analysis of the general structure used for the different virtual synchronous machine approaches is presented, which constitutes the base implementation tree for all existent strategies of virtual synchronous generation. In a first stage, the most inner control loop is studied and analyzed regarding the current control on the power converter. This internal regulator is in charge of the current injection and the tracking of all external power reference. Afterward, the synchronous control is oriented to the device, where the generating unit relies on its local measurements to emulate a synchronous machine in the power converter. In this regard, a sensorless approach to the virtual synchronous machine is introduced, increasing the stability of the power converter and reducing the voltage measurements used. Finally, the model of the synchronous control is extrapolated into a power plant control layer to be able to regulate multiple units in a coordinated manner, thus emulating the behavior of a unique synchronous machine. In this regard, the local measurements are not used for the emulation of the virtual machine, but they are switched to PCC measurements, allowing to set the desired dynamic response at the power plant level.
Sistemes d'energia elèctrica

Virtual Power Plant (VPP) is a concept that aggregate Distributed Energy Resources (DER) together, aims to overcome the capacity limits of single DER and the intermit-ted natural characteristics of renewable energy sources like wind and solar. The whole system can be viewed as a single large-capacity power plant from the system‘s point of view. In this project, the literature review of VPP concept, architecture, existed project and the survey of VPP in Sweden are being conducted first. Secondly, the simplified VPP model is built on MATLAB/Simulink software. The simplified system contains a wind farm, a hydro power plant, a dynamic system load and an infinite bus representing the large transmission grid. During the simulation process, the generation and consump-tion unites are running according to the real history data located in external database. In the third place, optimized control schemes for the hydro unit in VPP model to decrease its effects on transmission grid are implemented in Simulink model. At the same time, hydro turbine should be controlled in an optimized way that without large turbulence. Basically, the hydro power plant is responsible for balancing the active power between the wind farm and dynamic load. Since there is a limit for the hydro turbine output, the rest of either power shortage or surplus power need to be com-pensated by the grid. This is the fundamental control scheme, so called run time con-trol scheme. The advanced control schemes here are based on the moving average control method and forecast compensation control method. The forecast compensa-tion control method use the 24 hours ahead load forecasting data generated by Artifi-cial Neural Network. Later on, analysis of those three control schemes will be pre-sented. The last part of the project is the conclusion of the different control schemes according to comparison of their control results.

Дисертація на здобуття наукового ступеня кандидата технічних наук (доктора філософії) за спеціальністю 05.14.02 - електричні станції, мережі і системи (141 – електроенергетика, електротехніка та електромеханіка). – Національний технічний університет «Харківський політехнічний інститут» МОН України, Харків, 2019. Зміст анотації. Дисертація присвячена розв’язанню актуальної науково- прикладної задачі у галузі забезпечення заявлених графіків видачі потужності у вузлі генерації електричних станцій на відновлювальних джерелах енергії (ВДЕ), шляхом використання систем акумуляції та концепції віртуальних електричних станцій. Актуальність теми дисертаційної роботи полягає у наступному, сучасні тенденції в розвитку електроенергетичних систем передбачають суттєве збільшення частки електричних станцій на відновлювальних джерелах енергії в загальній структурі генерації розвинутих країн, що призводить до необхідності їх додаткового резервування. З гідно статті 71.5 закону про «Ринок електричної енергії України», Гарантований покупець повинен придбати всю енергію від виробників з ВДЕ, що працюють за «Зеленим тарифом». Особливістю режимів роботи електричних станцій на відновлювальних джерелах є майже пряма залежність від погодних умов, що призводить до відхилень значення потужності в точках генерації від заявлених значень. Отже виникає необхідність в компенсації виникаючих небалансів. Використовуючи концепцію віртуальних електричних станцій, що поєднують електричні станції на ВДЕ, активних споживачів та системи акумуляції в єдину станцію зі спільною системою управління, можливо зменшити небаланси в точці генерації. Це потребує створення методів вибору оптимальної компоновки систем накопичення; алгоритмів систем управління для віртуальних електричних станцій та розподілених систем акумулювання; рекомендацій по їх застосуванню для електричних мереж, які тільки починають перехід від традиційних до інтелектуальних і мають дефіцит маневрових потужностей. Розробка технічних заходів для забезпечення заявлених графіків роботи сонячних електростанцій (СЕС) та вітряних електростанцій (ВЕС) дозволить їх інтегрувати до графіку генерації в якості базових станцій. Це дасть можливість виконати зобов‘язання всіх учасників процесу та не порушувати заплановані режими роботи інших станцій. Мета і задачі дослідження. Мета дослідження полягає у забезпеченні заявлених графіків видачі потужності у вузлі генерації електричних станцій на відновлювальних джерелах енергії, шляхом використання систем акумуляції та концепції віртуальних електричних станцій. Для досягнення поставленої мети визначені задачі дослідження: – проаналізувати основні методи та засоби забезпечення графіків видачі потужності електричних станцій на відновлювальних джерелах енергії в Україні та світі і фактори, що впливають на них; – розробити математичну модель для дослідження режимів роботи електричних станцій гібридної генерації на основі сонячної та вітроелектростанції та провести перевірку адекватності розробленої математичної моделі; – уточнити методику розрахунку вартості електричної енергії від систем акумулювання у вузлі генерації з урахуванням втрат при передачі та перетворенні енергії; – вдосконалити методику оптимізації конфігурації систем акумулювання для балансування генерації СЕС та ВЕС за умови мінімізації питомої вартості електричної енергії; – провести комп‘ютерне моделювання роботи електричних станцій на відновлювальних джерелах енергії на основі погодних даних обраного адміністративного району України з метою визначення необхідної конфігурації системи акумулювання на основі розробленої методики; – розробити комп‘ютерну модель віртуальної електричної станції, що поєднує в собі удосконалені математичні моделі генерації активної потужності СЕС і ВЕС, комп‘ютерні моделі систем накопичення енергії, імітацію активних споживачів і енергетичного ринку, а також елементи апаратно-комп‘ютерного моделювання. – розробити алгоритм роботи інформаційно-керуючої системи віртуальної електричної станції, на основі уточненого методу розрахунку вартості електричної енергії та провести його апробацію на комп‘ютерній моделі віртуальної електричної станції. – дослідити можливість застосування концепції віртуальних електричних станцій для забезпечення добових графіків генерації з урахуванням вимог Гарантованого покупця. Об’єктом досліджень – електромагнітні процеси в мережах з електричними станціями на основі відновлювальних джерел енергії. Предметом досліджень – електричні та інформаційні параметри режимів обладнання електричних станцій на відновлюваних джерелах енергії. Наукова новизна одержаних результатів: 1) Отримала подальший розвиток математична модель віртуальної електричної станції, яка відрізняється від існуючих тим, що додано елементи для зв‘язку з реальним програмованим логічним контролером ОВЕН 110-60 та на основі регресійного аналізу враховано додатковий коефіцієнт співвідношення вхідних погодних умов та результуючої потужності для встановлення відповідності з реальними характеристиками обладнання, що дозволило застосувати апаратно-програмне моделювання, збільшити точність розрахунку вихідної активної потужності сонячної електричної станції на 5% та проводити моделювання роботи вітряної електричної станції на швидкостях вітру більших за номінальні. 2) Отримав подальший розвиток метод розрахунку вартості електричної енергії яка використовується для забезпечення добових графіків генерації ВДЕ на основі акумуляції в межах однієї віртуальної електричної станції, який відрізняється від відомих врахуванням витрат пов‘язаних з розташуванням, встановленням та роботою додаткового обладнання, що дозволяє підвищити точність виконання розрахунків і підвищити енергоефективність таких систем за рахунок задіяння найбільш доцільних їх елементів. 3) Науково і технічно обґрунтовано використання концепції віртуальних електричних станцій для забезпечення добових графіків генерацій сонячних та вітроелектростанцій в умовах енергетичного ринку України, що дозволить забезпечити функціонування механізму Гарантованого покупця з мінімальним застосуванням додаткових маневрових потужностей. Практичне значення одержаних результатів. Для електроенергетичної галузі України полягає в тому, що на підставі виконаних досліджень визначені способи оптимізації режимів роботи електричних станцій на відновлювальних джерелах енергії за допомогою акумуляції. Такий підхід дозволить встановити відповідність між діючим та прогнозним значенням потужності у точці генерації, сформувати графік навантаження для традиційних електричних станцій без необхідності додаткового їх маневрування для компенсацій електростанцій на відновлювальних джерелах енергії. Окрім того, результати досліджень допоможуть збільшити точність розрахунків вартості електричної енергії у точці генерації від систем акумулювання. Розроблена методика вибору конфігурації систем акумуляції дозволяє визначити мінімально необхідну ємність накопичувачів енергії та їх потужність, що забезпечить мінімізацію вартості устаткування. Запропонований алгоритм управління розподіленою системою акумулювання дозволяє вирішити задачу розподіленого балансування, а також враховує можливість залучення активних споживачів та енергетичного ринку до процесу балансування. Результати дисертаційної роботи були впроваджені: - у ТОВ «ЛЕО» для розрахунку мінімально необхідного об’єму систем накопичення енергії, що будуть рекомендовані для забезпечення заявлених графіків генерації електричних станцій на ВДЕ які працюють за зеленим тарифом; - у навчальному процесі кафедри електричних станцій Національного технічного університету “Харківський політехнічний інститут” для студентів спеціальностей 141 спеціальності за спеціалізаціями: 141-01 «Електричні станції» та 141-05 «Енергетичний менеджмент та енергоефективні технології» під час викладання курсів лекцій з дисциплін «Електрична частина станцій та підстанцій», «АСУТП станцій та підстанцій», «Системи відновлюваної енергетики та вторинні енергоресурси» , під час написання дипломних проектів, випускних кваліфікаційних робіт. Дисертація виконана згідно планів наукових досліджень кафедр електричних станцій та загальної електротехніки Національного технічного університету «Харківський політехнічний інститут» у відповідності до договору «Методи удосконалення електроенергетичних систем» (ДР № 0116U000885).
Dissertation for the degree of candidate of technical sciences (doctor of philosophy) in specialty 05.14.02 - Electric power stations, networks and systems (141 - Power engineering, electrical engineering and electromechanics). – National Technical University "Kharkiv Polytechnic Institute", Ministry of Education and Science of Ukraine, Kharkiv, 2019. Annotation content. The dissertation is devoted to solving the actual scientific and applied problem in the providing the stated schedules of power generation at renewable energy sources (RES) through the use of storage systems and the concept of virtual power plants. According to the legislation of Ukraine, the Guaranteed Buyer must purchase all energy from renewable energy producers operating under the Green Tariff. The peculiarity of the operating modes of power plants on renewable sources is almost a direct dependence on weather conditions, which leads to deviations of the power value at the points of generation from the declared values. Therefore, there is a need to compensate for emerging imbalances. Using the concept of virtual power plants that combine RES, active consumers and storage systems into a single station with a common control system, it is possible to reduce imbalances at the generation point. This requires the creation of methods for selecting the optimal layout of the accumulation systems; control systems algorithms for virtual power plants and distributed storage systems; recommendations for their application to power grids that are just beginning to transition from traditional to intelligent and have a lack of maneuverability. The development of technical measures to ensure the declared schedules of solar power plants (SPP) and wind power plants (WPP) will allow them to be integrated into the generation schedule as base stations. This will make it possible to fulfill the obligations of all participants of the process and not violate the planned operating modes of other stations. The purpose and tasks of the study. The purpose of the study is to provide the stated schedules of power generation at the generation site of renewable energy sources through the use of storage systems and the concept of virtual power plants. To achieve the goal, the research objectives are defined: – to analyze the basic methods and means of providing the schedules of power outputs of renewable energy sources in Ukraine and the world and the factors that influence them; – to develop a mathematical model for the study of operating modes of hybrid power plants based on solar and wind power plants and to check the adequacy of the developed mathematical model; – clarify the methodology for calculating the cost of electricity from storage systems at the generation site, taking into account losses in energy transmission and conversion; – improve the method of optimization of the configuration of accumulation systems for balancing the generation of SES and WPP, while minimizing the specific cost of electricity; – carry out computer simulation of the operation of renewable energy power plants based on the weather data of the selected administrative district of Ukraine in order to determine the required configuration of the accumulation system based on the developed methodology; – to develop a computer model of a virtual power plant that combines advanced mathematical models of SES and WPP power generation, computer models of energy storage systems, imitation of active consumers and the energy market, as well as elements of hardware and computer modeling. – to develop an algorithm of operation of the information and control system of the virtual power plant, based on the specified method of calculating the cost of electricity, and to test it on a computer model of the virtual power plant. – explore the possibility of applying the concept of virtual power plants to provide daily generation schedules, taking into account the requirements of the Guaranteed Buyer. The object of research is the electromagnetic processes in grids with power plants based on renewable energy sources. Subject of research – electrical and information parameters of modes of equipment of power plants on renewable energy sources. Scientific novelty: 1) The mathematical model of the virtual power plant has been further developed, which differs from the existing ones by adding elements for communication with the real programmable logic controller OVEN 110-60 and based on the regression analysis the additional coefficient of the ratio of incoming weather conditions and the resulting power is taken into account the real characteristics of the equipment, which allowed to apply hardware and software modeling, to increase the accuracy of the calculation of the output active power of solar panels at 5% and conduct simulations of wind power station at wind speeds greater than nominal. 2) The method of calculating the cost of electricity, which is used to provide daily schedules of generation of RES on the basis of accumulation within one virtual power station, which differs from the known costs related to the location, installation and operation of additional equipment, which improves the accuracy of calculations, was further developed. and to increase the energy efficiency of such systems by utilizing their most relevant elements. 3) It is scientifically and technically grounded to use the concept of virtual power plants for providing daily schedules of generation of solar and wind power plants in the conditions of the energy market of Ukraine, which will allow to ensure the functioning of the Guaranteed Buyer mechanism with minimal use of additional maneuvering capacities. Practical value: The practical value of the work lies in the fact that methods of optimization of modes of operation of power plants on renewable energy sources by means of accumulation are determined on the basis of the performed researches. This approach will allow to establish the correspondence between the current and the predicted value of power at the point of generation, to form a schedule of load for traditional power plants without the need for additional maneuvering for compensation of power plants on renewable energy sources. In addition, research findings will help to increase the accuracy of electricity cost calculations at the point of generation from storage systems. The developed method of choosing the configuration of accumulation systems allows to determine the minimum required capacity of energy storage and their capacity, which will minimize the cost of equipment. The proposed algorithm for managing a distributed accumulation system allows to solve the problem of distributed balancing, and also takes into account the possibility of involving active consumers and the energy market in the balancing process. The results of the dissertation work were introduced: - at LEO LLC to calculate the minimum required volume of energy storage systems that will be recommended to provide the stated generation schedules of power plants than work based on green tariff; - in the educational process of the National Technical University "Kharkiv Polytechnic Institute" for students of specialties 141 specialties in specialization: 141- 01 "Power Plants" and 141-05 "Energy Management and Energy Efficient Technologies" during the teaching of lectures on disciplines "Electrical part of stations and substations "," ACTSP of stations and substations "," Renewable energy systems and secondary energy resources ", during writing of diploma projects, final qualification works. The dissertation is executed according to the plans of scientific researches of the National Technical University "Kharkiv Polytechnic Institute" of the Department of Power stations and general electrical engineering in accordance with the economic agreement « Methods of improvement of power systems» (state registration number - 0116U000885).

Distributed energy sources are becoming more and more important in the German electricitynetwork. One solution to manage this growing number of distributed assets liesin the Virtual Power Plant concept. A Virtual Power Plant aggregates decentralizedgenerators and loads to behave like a large power plant. Based on new technologies, ituses advanced communication technologies to provide different services (generation ofenergy, steering of power systems, balancing services ...). This thesis proposes a mixedintegerstochastic model of a Virtual Power Plant. The participation to different productsis being studied: selling power on day-ahead basis on the spot market, providingflexibility to the secondary and tertiary reserve market. The particularity of this modelis to consider the revenue generated by the stochastic activation of the reserve market.An operational tool named AlocaBid is implemented in Python, based on the developedmathematical model. The performance of the model is being evaluated using four studycases, representing typical market situations. The results demonstrate the advantage ofthe proposed model over state-of-the-art method for bids’ allocation.
Distribuerade energik¨allor blir allt viktigare i det tyska eln¨atverket. En l¨osning f¨or atthantera det v¨axande antalet distribuerade tillg°angar ¨ar Virtual Power Plant-konceptet.Ett virtuellt kraftverk styr decentraliserade generatorer och laster f¨or att efterlikna ettnormalt kraftverk. Baserat p°a ny teknik anv¨ander det avancerad kommunikationsteknikf¨or att tillhandah°alla olika tj¨anster (generering av energi, styrning av kraftsystem, balanseringstj¨anster ...). Denna avhandling f¨oresl°ar en stokastisk blanda heltalsmodell avett virtuellt kraftverk. Deltagandet i olika produkter studeras: F¨ors¨aljning av maktp°a daglig basis p°a spotmarknaden, vilket ger flexibilitet till den sekund¨ara och terti¨arareservmarknaden. Det speciella med denna modell ¨ar att den tar h¨ansyn till de int¨aktersom genereras av den stokastiska aktiveringen av reservmarknaden. Ett operationsverktygmed namnet AlocaBid implementeras i Python, baserat p°a den utvecklade matematiskamodellen. Modellens prestanda utv¨arderas med fyra studiefall, som representerartypiska marknadssituationer. Resultaten visar f¨ordelen med den f¨oreslagna modelleframf¨or den senaste tekniken f¨or budgivningens f¨ordelning.

The high penetration of renewable energies (RE) in power systems is increasing the volatile production on the generation side and the presence of distributed energy resources (DER) over the territory. On the other hand, Virtual Power Plants (VPPs) are an aggregation of DER managed as a single entity to promote flexibility services to power systems. Therefore, VPPs are a valid approach to cope with the arising challenges in the power system related to RE penetration. This report defines the concept of a utility-scale VPP, as a tool to stabilize the grid and increase the flexibility capacity in power systems. For this purpose, the report places special emphasis in the use cases that can be developed with a utility-scale VPP. Nevertheless, implementing a utility-scale VPP is a complex procedure, as VPP solutions are highly customizable depending on the scope and the conditions of each project. For this reason, this report analyses the main factors that must be taken into account when implementing a VPP solution. The report concludes that the two most critical factors that define the viability of a VPP project are, first, the energy market design and regulatory framework and second, the technical requirements. These two must always align with the scope of the project and the use cases intended to be developed. Further, other minor factors, including a cost estimate for a VPP solution, are also considered in the report.
Den höga penetrationen av förnybara energier i kraftsystem ökar den flyktiga produktionen på produktionssidan och närvaron av distribuerade energiresurser över territoriet. Å andra sidan är virtuella kraftverk en sammanställning av distribuerade energiresurser som hanteras som en enda enhet för att främja flexibilitetstjänster till kraftsystem. Därför är virtuella kraftverk: er en giltig strategi för att hantera de uppkomna utmaningarna i kraftsystemet relaterat till förnybara energier genomslag. I denna rapport definieras konceptet med en virtuella kraftverk verktygsskala som ett verktyg för att stabilisera nätet och öka flexibilitetskapaciteten i kraftsystem. För detta ändamål lägger rapporten särskild tonvikt på användningsfall som kan utvecklas med en virtuella kraftverk-nytta. Trots det är implementering av en virtuella kraftverknyckelskala en komplex procedur, eftersom virtuella kraftverk-lösningar är mycket anpassningsbara beroende på omfattning och villkor för varje projekt. Av denna anledning analyserar denna rapport de viktigaste faktorerna som måste beaktas vid implementering av en VPP-lösning. Rapporten drar slutsatsen att de två mest kritiska faktorerna som definierar ett virtuella kraftverk projekts livskraft är, dels energimarknadens utformning och regelverk och för det andra de tekniska kraven. Dessa två måste alltid anpassa sig till projektets omfattning och användningsfall som är avsedda att utvecklas. Vidare beaktas även andra mindre faktorer, inklusive en kostnadsuppskattning för en virtuella kraftverk lösning, i rapporten.

This thesis is a feasibility study of avirtual power plant (VPP) in centralSweden and part of a project withInnoEnergy Instinct and STRI. The VPPconsists of a wind park, small hydroplant as well as solar photovoltaic andenergy storage. The 50 kVsubtransmission network was modeled inorder to evaluate the network servicesthat could be provided by coordinatingexisting distributed energy resources inthe network. Simulations where performedusing measured hourly variations inproduction and consumption of allnetwork nodes. The studied networkservices included both reactive andactive power control.The aim of this thesis is to evaluatethe potential contribution from the VPPfor capacity firming in order to allow abalance responsible party to meet placedbids on the day-ahead spot market,minimize peak load in order to reducesubscribed power, decrease networklosses, the contribution from reactivepower control using the power convertersis studied. Comparisons of the economicgains from spot and balance markets ofthe VPP distributed energy resources aremade for each operation case.Sponsor: InnoEnergy
InnoEnergy Instinct

Esta dissertação apresenta uma contribuição aos estudos de planejamento do sistema elétrico do Estado de São Paulo, ressaltando os benefícios que se obteria, com uma maior integração das fontes renováveis à matriz elétrica desse estado (notadamente as fontes de energia solar fotovoltaica, eólica, aproveitamento dos resíduos sólidos urbano RSU e vinhaça), visando o aumento da segurança e independência energética, redução de perdas, e benefícios ambientais. Para tanto, apresenta-se o conceito das usinas virtuais, cujo propósito é obter um melhor e maior aproveitamento dos recursos energéticos normalmente dispersos espacialmente - incluindo nesse rol a microgeração distribuída, a autoprodução e cogeração, e mesmo as fontes não renováveis que se encontram perto dos centros de consumo - com o objetivo de coordenar o seu funcionamento conjunto para satisfazer os requisitos da demanda de energia, por meio do uso da Tecnologia da Informação e Telecomunicações ou das Redes Inteligentes (Smart Grid), e, além disso, configurando a usina virtual de maneira que ela atue , no que diz respeito ao sistema interconectado de energia elétrica, rede de transmissão ou distribuição, como se fosse uma planta de geração de grande porte. Apresenta-se uma análise e projeções da operação e do suprimento do subsistema Sudeste/Centro Oeste (SE/CO), com foco especial no Sistema Elétrico do Estado de São Paulo, com suas interações com o SIN.
This Thesis presents contributions for the planning of the electrical system of São Paulo State Brazil, emphasizing benefits obtained with a better integration of renewables (mainly solar photovoltaics, wind energy, from municipal solid waste and sugarcane vinasse) aiming energy security and independence, loss reduction and environmental benefits. For this, the concept of VPP Virtual Power Plant is introduced, in which a better and broader use of energetic resources, geographically dispersed, including distributed microgeneration, autoproduction, cogeneration, and even nonrenewable sources, is facilitated. Those disperse energy resources, in general located near the consumer, are grouped and jointly managed, in order of to satisfy the demand requirements, using Smart Grid and Information and Telecommunication Technologies, and making the VPP to act, for the transmission or distribution system point of view, as a conventional large electrical power plant. An analysis and forecasts of the operation of the Brazilian Southeast/Center West (SE/CO) subsystem, with special focus on São Paulo State electrical system, and its interactions with the Brazilian Interconnected Electrical System (SIN), is presented.

Le centrali elettriche virtuali (Virtual Power Plant) sono sistemi energetici che integrano diversi tipi di fonti rinnovabili e non, carichi e dispositivi di accumulo. Un tipico VPP è un grande impianto industriale con elevati carichi elettrici e termici (parzialmente shiftabili), generatori di energia rinnovabili e depositi elettrici e termici. Il lavoro oggetto di questa tesi implementa un modello di ottimizzazione in due fasi per la generazione di flussi energetici. L'ottimizzazione avviene in due fasi: la prima, offline, consiste in un approccio robusto per la modellazione dell'incertezza basata su scenari, che cerca di minimizzare il valore della funzione obiettivo lungo l'orizzonte temporale considerando diverse tipologie di funzioni obiettivo. La fase seguente, online, è costituita da un algoritmo greedy che utilizza i valori ottimizzati della domanda di carica ottenuti dalla fase offline e genera i valori dei flussi energetici. Tramite un'interfaccia appositamente realizzata è possibile personalizzare l'intero processo di ottimizzazione selezionando i componenti, lo step (offline, online), se e dove applicare l'incertezza, quale funzione obiettivo utilizzare. Tali scelte determinano risoluzioni diverse del modello elaborato in base alle quali il comportamento dei VPP si adatta. Il procedimento complessivo simula la fase decisionale dell’EMS, ovvero il centro decisionale nella gestione del VPP.

Virtual power plants (VPPs) are an effective way to increase renewable integration. In this PhD research, the concept design and the detailed costs and benefits of implementing a realistic VPP in Western Australia (WA), comprising 67 dwellings, are developed. The VPP is designed to integrate and coordinate an 810kW rooftop solar PV farm, 350kW/700kWh vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and smart appliances through demand management mechanisms. This research develops a robust bidding strategy for the VPP to participate in both load following ancillary service (LFAS) and energy market in the wholesale electricity market in WA considering the uncertainties associated with PV generation and electricity market prices. Using this strategy, the payback period can be improved by 3 years (to a payback period of 6 years) and the internal rate of return (IRR) by 7.5% (to an IRR of 18%) by participating in both markets. The daily average error of the proposed robust method is 2.7% over one year when compared with a robust mathematical method. The computational effort is 0.66 sec for 365 runs for the proposed method compared to 947.10 sec for the robust mathematical method. To engage customers in the demand management schemes by the VPP owner, the gamified approach is adopted to make the exercise enjoyable while not compromising their comfort levels. Seven gamified applications are examined using a developed methodology based on Kim’s model and Fogg’s model, and the most suitable one is determined. The simulation results show that gamification can improve the payback period by 1 to 2 months for the VPP owner. Furthermore, an efficient and fog-based monitoring and control platform is proposed for the VPP to be flexible, scalable, secure, and cost-effective to realise the full capabilities and profitability of the VPP.

This paper addresses the coordinative operation problem of multi-energy virtual power plant (ME-VPP) in the context of energy internet. A bi-objective dispatch model is established to optimize the performance of ME-VPP on both economic cost(EC) and power quality (PQ).Various realistic factors are considered, which include environmental governance, transmission ratings, output limits, etc. Long short-term memory (LSTM), a deep learning method, is applied to the promotion of the accuracy of wind prediction. An improved multi-objective particle swarm optimization (MOPSO) is utilized as the solving algorithm. A practical case study is performed on Hongfeng Eco-town in Southwestern China. Simulation results of three scenarios verify the advantages of bi-objective optimization over solely saving EC and enhancing PQ. The Pareto frontier also provides a visible and flexible way for decision-making of ME-VPP operator. Two strategies, “improvisational” and “foresighted”, are compared by testing on IEEE 118-bus benchmark system. It is revealed that “foresighted” strategy, which incorporates LSTM prediction and bi-objective optimization over 5-hr receding horizon, takes 10 Pareto dominances in 24 hours.

Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.14.02 - електричні станції, мережі і системи. – Національний технічний університет «Харківський політехнічний інститут», Харків, 2019. Дисертаційна робота присвячена розв’язанню актуальної науково-прикладної задачі у напрямку забезпечення заявлених графіків генерації електричних станцій на відновлюваних джерелах енергії на основі концепції віртуальних електричних станцій. У дисертаційній роботі досліджено методи забезпечення заявлених графіків генерації електричних станцій на ВДЕ та обґрунтована доцільність використання концепції віртуальних електричних станцій для вирішення поставленої задачі. Досліджено застосування різних типів систем акумуляції, як одного з елементів віртуальної електричної станції. Проведено аналіз існуючих методів впровадження інтелектуальних мереж, що дозволило вибрати шаблон Smart Grid Architecture Model за основу для створення необхідної інфраструктури. Проведено аналіз існуючих методів визначення оптимальної ємності систем акумуляції та їх компоновки. Розроблено комп‘ютерну модель для дослідження роботи віртуальних електричних станцій, що дозволяє оцінити потенційні небаланси при генерації, перевірити достатність обсягу систем акумуляції для різних задач, а також провести апробацію роботи системи управління. Уточнено методику розрахунку вартості електричної енергії від систем акумулювання з урахуванням вартості втрат енергії при передачі та трансформації, а також додаткових факторів пов‘язаних з орендою та обслуговуванням. Розроблено, реалізовано та апробовано алгоритм управління віртуальною електричною станцією, що базується на задіянні найбільш дешевого джерела енергії для балансування з урахуванням обмежень електричних мереж, доступу до енергетичного ринку та можливості залучення активних споживачів. Показана можливість забезпечення заявлених графіків генерації електричних станцій на основі концепції віртуальних електричних станцій на прикладі умов одного з адміністративних центрів України.
Dissertation for the degree of candidate of technical sciences in specialty 05.14.02 - power plants, networks and systems. - National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2019. The thesis is devoted to the solution of the current scientific and applied problem in the field of providing the declared schedules of generating power plants with renewable energy sources based on the concept of virtual power plants. In the dissertation work, the methods of providing the declared schedules of generating power plants on renewable energy sources are investigated. The expediency of using the concept of virtual power plants to solve the problem is justified. The use of various types of accumulation systems as one of the elements of a virtual power plant is investigated. The analysis of existing methods and state-of-the-art-practices of implementing intelligent networks was carried out, which made it possible to select the Smart Grid Architecture Model pattern as the basis for creating the necessary infrastructure. The analysis of existing methods for determining the optimal capacity of accumulation systems and their layout has been carried out that was used to calculate minimal capacity for providing the declared schedules of generation of PV and wind power plant each 1 MW for one of the administrative centers of Ukraine. The developed computer model for studying the operation of virtual power plants that include PV and wind power with energy storage and connections to PLC allows assessing potential unbalances during generation, checking the sufficiency of the capacity of accumulation systems for various tasks, as well as testing the operation of the control system. The methodology for calculating the cost of electrical energy from storage systems has been refined, taking into account the cost of energy losses during transmission and transformation, as well as additional factors associated with renting and servicing. An algorithm for managing a virtual power plant was developed, implemented and tested with real PLC connected to mathematical model, based on using the cheapest energy source for balancing taking into account the limitations of electrical networks, power lines and transforming equipment, access to the energy market for buying and selling energy and the ability to attract active consumers. The possibility of providing the declared schedules of generation of power plants based on the concept of virtual power plants on the example of conditions of one of the administrative centers of Ukraine is shown.

The current shift towards renewable energy resources creates volatility in the electricity production that must be compensated by nevi sources of balancing energy. To ensure a normal operation of the power system, the transmission system operators procure power reserves able to provide regulation energy through market processes. Virtual power plants are now likely to participate on the balancing markets. In this study, the technical and economic feasibility of having virtual power plants participate in the Swiss balancing market is assessed. The study begins with the evaluation and compa.rison of four European balancing market designs and continues with the clarification of the concept of virtual power plant. The focus is then set on the Swiss ancillary services market, recently open to virtual pmver plants. After a detailed market description, an economic model simulating the participation of a virtual power plant made of industrial resources on the secondary and tertiary control markets has been developed. This model \Vas evaluated on an actual market design: the Sv.riss ancillary servicel:l market. 5 cases were simulated, allowing to estimate the opportunity fom both the capacity and the energy market productl:l. The simulations indicated that an example company (based on an actual situation) could hope a decrease in its energy cost between :3 and 4% by participating in a control pool over a year. Other simulations demonstrated the greater profit expected from secondary reserves compared to tertiary rel:lerves, and the need to develop an automatized activation system. The encouraging economic study is followed by a technical overview of the envisioned system. A generic technical characterization of virtual power plant is presented, on v.rhich the Swiss use-case is later applied. The breakdown into functional requirements allowed to highlight specific issues. The design of the control strategy, particularly to deliver secondary control, as well as the hardware communication interface to use are tvw aspects that ,vill require further analysis. Additionally, on an economic level, the investment cost for remote communication modules are acceptable with respect to the economic potentials estimated in the first part, for medium­sized industrial energy resources. In conclusion, the study established the profitability of an aggregation project on the Swisl:l market but also demonstrated the need to pursue research for the project to be fully feasible on a technical level.

Le microreti caratterizzate da unità di generazione con Fonti Energetiche Rinnovabili (FER), sono oggetto di crescente interesse in due contesti molto diversi tra loro: l’integrazione della Generazione Diffusa (GD) in reti di distribuzione pubbliche nei paesi sviluppati e l’elettrificazione di zone rurali attualmente non servite dalla rete elettrica. L’introduzione dei sistemi di accumulo nelle microreti rende possibile la compensazione della variabilità delle FER trasformando le microreti in sistemi di produzione che nel complesso risultano completamente regolabili. L’obiettivo del presente lavoro di tesi è dimostrare come le microreti possono svolgere un ruolo fondamentale per lo sviluppo delle infrastrutture elettriche nei paesi in via di sviluppo e nelle economie emergenti ponendo le basi per l’elettrificazione di aree remote e scarsamente popolate ad oggi non connesse alla rete di distribuzione dell’energia.

This thesis concerns with design of micro sources and their implementation in Micro grid system. In the first part the work is aimed at definition of smart - grid, where describes their advantages, disadvantages and necessary changes, which has to be made in current distribution network for implementation this system. Further on the thesis concerns with detailed description of Micro grid, configuration of this kind of network, the issues in implementation and possibilities to provide ancillary services. The work also describes marginally virtual power plants, presents definition, components and types of virtual power plants. The final chapter describes the creation of micro sources in System modeler and subsequent testing of consumption cover to operate in island mode.

The energy management system is the intelligent core of a virtual power plant and it manages power flows among units in the grid. This implies dealing with optimization under uncertainty because entities such as loads and renewable energy resources have stochastic behaviors. A hybrid offline/online optimization technique can be applied in such problems to ensure efficient online computation. This work devises an approach that integrates machine learning and optimization models to perform automatic algorithm configuration. It is inserted as the top component in a two-level hierarchical optimization system for the VPP, with the goal of configuring the low-level offline/online optimizer. Data from the low-level algorithm is used for training machine learning models - decision trees and neural networks – that capture the highly complex behavior of both the controlled VPP and the offline/online optimizer. Then, Empirical Model Learning is adopted to build the optimization problem, integrating usual mathematical programming and ML models. The proposed approach successfully combines optimization and machine learning in a data-driven and flexible tool that performs automatic configuration and forecasting of the low-level algorithm for unseen input instances.

In this study, an examination regarding what benefits an aggregatedpopulation of Battery Energy Storage Systems (BESSs) could result incompared to when the individual units in the population are being usedseparately has been executed. The increased flexibility and reducedsafety margins as results of the aggregation was also examined. Thestudy was executed on behalf of the smart energy service companyCheckWatt AB and the study furthermore rests upon results of earlierperformed master theses on behalf of the company. By investigating previous work and studies through a literature study,the enabling of anumerical study was done. The numerical study wasbased on a simple model of a Virtual Power Plant (VPP) where severalBESSs are smartly controlled in order to be used for both local peakshaving and as common providers of the frequency reserve FrequencyContainment Reserve - Normal (FCR-N). The study involved the formation of a numerical model which simulated cases of both aggregated and non-aggregated populations of up to 45 load profile units, this in order for advantages and differences to be distinguished. The data used inthe simulations was received mainly from the CheckWatt AB andconsisted of photovoltaic (PV) electricity production and load data of 45 customers of the company. A sensibility analysis of the numericalstudy was also performed, which showed that the studied model andsystem were quite stable. The results of the simulations of the case of the study proved thatthere are some advantages connected to aggregation of several BESSs,and that the aggregation enabled an added value and a higher level offlexibility within the system. The safety margins connected todelivery of FCR-N could be reduced when aggregating several BESS,while a more extensive study is requested regarding safety marginsconnected to peak shaving. The study’s results further showed that anaggregator can be used as a sustainable and flexible solution forbalancing the electrical grid in the transition to a sustainableenergy system allowing a higher penetration of intermittentenergy sources.

The diploma thesis is dealing with possible approaches to control distributed energy resources and storage systems. One of these approaches is a virtual power plant and its concept is described in the first part of the thesis. The virtual power plant is a controlled system of distributed energy resources, storage systems and controllable loads interconnected via communication network, that can act as a conventional power plant. The theoretical part contains a survey of control system's topologies, a brief summary of available communication infrastructures and standards. The second part of the thesis is focused on the description of operation and control of hybrid system that represents an inseparable component of virtual power plant. A Matlab Simulink model was created for this purpose. A simulation of hybrid inverter's step response is realised to test the operation of the hybrid system and it is compared with the real measurements in the laboratory. A comparison of control approaches of hybrid system implemented on the basis of measurements is also included in this thesis and was published in the scientific paper attached in the appendix.

Les politiques entreprises dans le domaine de la production d’électricité pour lutter contre le changement climatique reposent communément sur le remplacement des moyens de production fossiles et centralisés par de nouveaux moyens de type renouvelables. Ces énergies renouvelables sont en grande partie distribuées dans les réseaux moyenne et basse tension et sont le plus souvent intermittentes (énergies éolienne et photovoltaïque principalement). Les gestionnaires de réseaux s’attentent à ce que ce changement de paradigme induise des difficultés conséquences dans leurs opérations. Les mondes de la recherche et de l’industrie se sont ainsi structurés depuis le milieu des années 2000 afin d’apporter une réponse aux problèmes anticipés. Cette réponse passe notamment par le déploiement de technologies de l’information et de la communication (TIC) dans les réseaux électriques, des centres de contrôle jusqu’au sein même des moyens de production distribués. C’est ce que l’on appelle le Smart Grid. Parmi le champ des possibles du Smart Grid, ces travaux de thèses se sont en particulier attachés à apporter une réponse aux enjeux de stabilité en fréquence du système électrique, mise en danger par la réduction anticipée de l’inertie des systèmes électriques et la raréfaction des moyens de fourniture de réserve primaire (FCR), auxquels incombent le maintien de la fréquence en temps réel. En vue de suppléer les moyens de fourniture de réserve conventionnels et centralisés, il a ainsi été élaboré un concept de coordination de charges électriques délestables distribuées, qui se déconnectent et se reconnectent de manière autonome sur le réseau au gré des variations de fréquence mesurées sur site. Ces modulations de puissance répondent à un schéma préétabli qui dépend de la consommation électrique effective de chacune des charges. Ces travaux ont été complétés d’une étude technico-économique visant à réutiliser cette infrastructure de coordination de charges délestables pour la fourniture de services systèmes ou de produits de gros complémentaires. Ce travail de thèse réalisée au sein des équipes innovation de Schneider Electric et du laboratoire de Génie Electrique de Grenoble (G2Elab), est en lien avec les projets Européens EvolvDSO et Dream, financés dans le cadre du programme FP7 de la Commission Européenne
Climate change mitigation policies in the power generation industry lead commonly on the replacement of bulk generation assets by Renewable Energy Resources (RES-E). Such RES-E are largely distributed among the medium and low voltage grids and most of them are intermittent like photovoltaic and wind power. System Operators expect that such new power system paradigm induces significant complications in their operations. The communities of research and industry started thus to structure themselves in the mid-2000s in order to respond to these coming issues, notably through the deployment of Information and Communication Technology (ICT) in power systems assets, from the Network Operations Centers (NOCs) down to Distributed Energy Resources (DERs) units. This is the Smart Grid. Among the range of possibilities of the Smart Grid, this Ph.D work aims in priority to provide a solution to handle the issue of frequency stability of the power system that are endangered by the combined loss of inertia of the power system and the phasing-out of conventional assets which used to be in charge of the maintain of the frequency in real time through the supply of Frequency Containment Reserve (FCR). The concept developed lead on a process of coordinated modulation of the level of loads of DERs, whose evolve depending on the system frequency measured in real time on-site. The strategy of modulation of each DER follows a pattern which is determined at the scale of the portfolio of aggregation of the DER, depending on the effective level of load of the DER at normal frequency (i.e. 50Hz in Europe). This work is completed by a cost benefit analysis that assesses the opportunity of sharing of the previous infrastructure of coordinated modulation of DERs for the supply of ancillary services and wholesale products. This thesis conducted within Schneider Electric’s Innovation teams and Grenoble Electrical Engineering Laboratory (G2Elab) is linked with the European projects Dream and EvolvDSO, and funded under European Commission’s FP7 program

Les énergies renouvelables variables prennent une part croissante de la production raccordée aux réseaux électriques. Par conséquent, elles doivent s’intégrer aux mécanismes de services système qui assurent l’équilibre entre production et con-sommation de puissance sur les réseaux. Toutefois la forte incertitude de la production variable est un obstacle à la fourniture de ces services qui requièrent une fiabilité élevée. L’agrégation de centrales renouvelables dispersées et contrôlées par une centrale virtuelle permet de diminuer cette incertitude en profitant du foisonnement entre les centrales. Cette thèse propose plusieurs modèles de prévision probabiliste afin d’évaluer la capacité d’une centrale virtuelle renouvelable variable à offrir des services système avec une fiabilité maximale: ces modèles sont des adaptations d’arbres de décisions, de réseaux de neurones récurrents et convolutifs, ainsi que de distributions dédiées aux quantiles extrêmement faibles. Une attention particulière est portée à la combinaison de sources d’énergie (Photovoltaïque, éolien, hydraulique au fil de l’eau). Ensuite, des stratégies d’offre optimale d’énergie et de réserve par une agrégation renouvelable sont établies en utilisant les prévisions de production et en considérant les incertitudes associées aux différents marchés. Ces stratégies explorent plusieurs options de modélisation: dépendance entre production renouvelable et prix par une copule, taux de défaillance contrôlé par optimisation sous contraintes probabilistes, et enfin offre de services système multiples à l’aide d’une formulation Lagrangienne
As variable renewable energy plants penetrate significantly the electricity generation mix, they are expected to contribute to the supply of reserve power, albeit the high uncertainty levels on their production. A solution to reduce the uncertainty consists in aggregating renewable plants dispersed over several climates to obtain a smoother production profile and operate them within a Virtual Power Plant control system. In this thesis, a series of probabilistic forecasting models are proposed to assess the capacity of a variable renewable Virtual Power Plant to provide ancillary services with maximum reliability: these models are adapted decision-tree regression models, recurrent and convolutional neural networks, as well as distributions dedicated to extremely low quantiles. The combination of energy sources (Photovoltaics, Wind, Run-of-river Hydro) is considered in detail. Optimal strategies for the joint offer of energy and ancillary services by a variable renewable Virtual Power Plant are later defined, based on production forecasts and market uncertainties. Offer strategies explore several modelling options:dependence between renewable production and prices via a copula, controlled rate of reserve underfullfilment with a chance-constraint optimization, and finally offer of multiple ancillary services thanks to a Lagrangian formulation

La raréfaction des sources de production conventionnelles et leurs émissions nocives ont favorisé l’essor notable de la production renouvelable, plus durable et mieux répartie géographiquement. Toutefois, son intégration au système électrique est problématique. En effet, la production renouvelable est peu prédictible et issue de sources majoritairement incontrôlables, ce qui compromet la stabilité du réseau, la viabilité économique des producteurs et rend nécessaire la définition de solutions adaptées pour leur participation au marché de l’électricité. Dans ce contexte, le projet scientifique Winpower propose de relier par un réseau à courant continu les ressources de plusieurs acteurs possédant respectivement des fermes éoliennes offshore (acteurs EnR) et des centrales de stockage de masse (acteurs CSM). Cette configuration impose aux acteurs d’assurer conjointement la gestion du réseau électrique.Nous supposons que les acteurs participent au marché comme une entité unique : cette hypothèse permet aux acteurs EnR de tirer profit de la flexibilité des ressources contrôlables pour minimiser le risque de pénalités sur le marché de l’électricité, aux acteurs CSM de valoriser leurs ressources auprès des acteurs EnR et/ou auprès du marché et à la coalition de faciliter la gestion des déséquilibres sur le réseau électrique, en agrégeant les ressources disponibles. Dans ce cadre, notre travail s’attaque à la problématique de la participation au marché EPEX SPOT Day-Ahead de la coalition comme une centrale électrique virtuelle ou CVPP (Cooperative Virtual Power Plant). Nous proposons une architecture de pilotage multi-acteurs basée sur les systèmes multi-agents (SMA) : elle permet d’allier les objectifs et contraintes locaux des acteurs et les objectifs globaux de la coalition.Nous formalisons alors l’agrégation et la planification de l’utilisation des ressources comme un processus décisionnel de Markov (MDP), un modèle formel adapté à la décision séquentielle en environnement incertain, pour déterminer la séquence d’actions sur les ressources contrôlables qui maximise l’espérance des revenus effectifs de la coalition. Toutefois, au moment de la planification des ressources de la coalition, l’état de la production renouvelable n’est pas connue et le MDP n’est pas résoluble en l’état : on parle de MDP partiellement observable (POMDP). Nous décomposons le POMDP en un MDP classique et un état d’information (la distribution de probabilités des erreurs de prévision de la production renouvelable) ; en extrayant cet état d’information de l’expression du POMDP, nous obtenons un MDP à état d’information (IS-MDP), pour la résolution duquel nous proposons une adaptation d’un algorithme de résolution classique des MDP, le Backwards Induction.Nous décrivons alors un cadre de simulation commun pour comparer dans les mêmes conditions nos propositions et quelques autres stratégies de participation au marché dont l’état de l’art dans la gestion des ressources renouvelables et contrôlables. Les résultats obtenus confortent l’hypothèse de la minimisation du risque associé à la production renouvelable, grâce à l’agrégation des ressources et confirment l’intérêt de la coopération des acteurs EnR et CSM dans leur participation au marché de l’électricité. Enfin, l’architecture proposée offre la possibilité de distribuer le processus de décision optimale entre les différents acteurs de la coalition : nous proposons quelques pistes de solution dans cette direction
Renewable Energy Sources (RES) has grown remarkably in last few decades. Compared to conventional energy sources, renewable generation is more available, sustainable and environment-friendly - for example, there is no greenhouse gases emission during the energy generation. However, while electrical network stability requires production and consumption equality and the electricity market constrains producers to contract future production a priori and respect their furniture commitments or pay substantial penalties, RES are mainly uncontrollable and their behavior is difficult to forecast accurately. De facto, they jeopardize the stability of the physical network and renewable producers competitiveness in the market. The Winpower project aims to design realistic, robust and stable control strategies for offshore networks connecting to the main electricity system renewable sources and controllable storage devices owned by different autonomous actors. Each actor must embed its own local physical device control strategy but a global network management mechanism, jointly decided between connected actors, should be designed as well.We assume a market participation of the actors as an unique entity (the coalition of actors connected by the Winpower network) allowing the coalition to facilitate the network management through resources aggregation, renewable producers to take advantage of controllable sources flexibility to handle market penalties risks, as well as storage devices owners to leverage their resources on the market and/or with the management of renewable imbalances. This work tackles the market participation of the coalition as a Cooperative Virtual Power Plant. For this purpose, we describe a multi-agent architecture trough the definition of intelligent agents managing and operating actors resources and the description of these agents interactions; it allows the alliance of local constraints and objectives and the global network management objective.We formalize the aggregation and planning of resources utilization as a Markov Decision Process (MDP), a formal model suited for sequential decision making in uncertain environments. Its aim is to define the sequence of actions which maximize expected actual incomes of the market participation, while decisions over controllable resources have uncertain outcomes. However, market participation decision is prior to the actual operation when renewable generation still is uncertain. Thus, the Markov Decision Process is intractable as its state in each decision time-slot is not fully observable. To solve such a Partially Observable MDP (POMDP), we decompose it into a classical MDP and an information state (a probability distribution over renewable generation errors). The Information State MDP (IS-MDP) obtained is solved with an adaptation of the Backwards Induction, a classical MDP resolution algorithm.Then, we describe a common simulation framework to compare our proposed methodology to some other strategies, including the state of the art in renewable generation market participation. Simulations results validate the resources aggregation strategy and confirm that cooperation is beneficial to renewable producers and storage devices owners when they participate in electricity market. The proposed architecture is designed to allow the distribution of the decision making between the coalition’s actors, through the implementation of a suitable coordination mechanism. We propose some distribution methodologies, to this end

Global economy growth, continuous development and the extensive use of technologies by consumers is increasing the demands of consumers for a reliable and efficient energy supply. Along with the rising energy consumption in the world, new technologies will influence the way we generate, distribute and consume energy. Alongside others, distributed energy generation is expected to become a major trend in many countries. The fast upward penetration of Distributed Energy Resources (DER) and the ongoing trend towards a more competitive electricity market requires new technologies and policies to handle emerging technical and economic issues. In order to handle distributed generation and to increase its participation within power markets, the idea of a Virtual Power Plant (VPP) has emerged. The concept of a VPP is recognized as an effective option to aggregate and operate DER and allowing for wholesale energy market participation to provide the required flexibility services to the local grid. Also, many DERs are available in urban areas and exploiting the flexibility of a VPP and developing a robust business case requires advanced considerations on their technical and commercial constraints and trade-offs in developing the VPP's operations regarding flexibility when simultaneously participating in the market. Considering the potential of activating commercial consumers in demand response programs, this paper proposes a new framework for energy scheduling of a distribution grid based on the concept of a technical virtual power plant (TVPP). This concept aims to enhance the flexibility of the grid, while contributing to an increase in the quality and reliability of the system, which also brings economic benefits. In this paper, a stochastic mixed-integer linear programming (MILP) optimization model was developed, which guarantees that the global optimum solution is obtained, in this case, maximizing the total profit of a TVPP. Regarding operational constraints, the TVPP allows the presence of commercial buildings and other distributed energy resources a day-ahead (DA) electricity market, as a price maker agent. In this context, this paper presents a comprehensive, integrated techno-economic approach that assesses the technical constraints and commercial flexibility opportunities. The case study includes the VPP's energy scheduling, improving system reliability by improving the voltage profile, and demand response and main commercial customers' assets (electric vehicles (EVs) parking lots and Heating Ventilation and Air Condition (HVAC) systems) aggregation and management. The model is tested using the IEEE 119-Bus test system, and results show that with the optimal management of DER, EVs parking lots and HVAC systems in commercial buildings allows the TVPP to increase its profit, by a percentage of 49,23%.

Global economy growth, continuous development and the extensive use of technologies by consumers is increasing the demands of consumers for a reliable and efficient energy supply. Along with the rising energy consumption in the world, new technologies will influence the way we generate, distribute and consume energy. Alongside others, distributed energy generation is expected to become a major trend in many countries. The fast upward penetration of Distributed Energy Resources (DER) and the ongoing trend towards a more competitive electricity market requires new technologies and policies to handle emerging technical and economic issues. In order to handle distributed generation and to increase its participation within power markets, the idea of a Virtual Power Plant (VPP) has emerged. The concept of a VPP is recognized as an effective option to aggregate and operate DER and allowing for wholesale energy market participation to provide the required flexibility services to the local grid. Also, many DERs are available in urban areas and exploiting the flexibility of a VPP and developing a robust business case requires advanced considerations on their technical and commercial constraints and trade-offs in developing the VPP's operations regarding flexibility when simultaneously participating in the market. Considering the potential of activating commercial consumers in demand response programs, this paper proposes a new framework for energy scheduling of a distribution grid based on the concept of a technical virtual power plant (TVPP). This concept aims to enhance the flexibility of the grid, while contributing to an increase in the quality and reliability of the system, which also brings economic benefits. In this paper, a stochastic mixed-integer linear programming (MILP) optimization model was developed, which guarantees that the global optimum solution is obtained, in this case, maximizing the total profit of a TVPP. Regarding operational constraints, the TVPP allows the presence of commercial buildings and other distributed energy resources a day-ahead (DA) electricity market, as a price maker agent. In this context, this paper presents a comprehensive, integrated techno-economic approach that assesses the technical constraints and commercial flexibility opportunities. The case study includes the VPP's energy scheduling, improving system reliability by improving the voltage profile, and demand response and main commercial customers' assets (electric vehicles (EVs) parking lots and Heating Ventilation and Air Condition (HVAC) systems) aggregation and management. The model is tested using the IEEE 119-Bus test system, and results show that with the optimal management of DER, EVs parking lots and HVAC systems in commercial buildings allows the TVPP to increase its profit, by a percentage of 49,23%.

Yes
The advent of smart meter technology has enabled periodic monitoring of consumer energy consumption. Hence, short term energy forecasting is gaining more importance than conventional load forecasting. An Accurate forecasting of energy consumption is indispensable for the proper functioning of a virtual power plant (VPP). This paper focuses on short term energy forecasting in a VPP. The factors that influence energy forecasting in a VPP are identified and an artificial neural network based energy forecasting model is built. The model is tested on Sydney/ New South Wales (NSW) electricity grid. It considers the historical weather data and holidays in Sydney/ NSW and forecasts the energy consumption pattern with sufficient accuracy.

碩士
國立中興大學
應用經濟學系所
104
The core value of virtual power plants is that they can integrate dispersed and sporadic virtual peaking capacity to lower the power demand with the power plant during the peak time, to achieve the goal of lower the power demand of the electricity system during the peak time. The effective function of virtual power plants depends on whether the majority of electric power customers are willing to participate the integration program of distributed generations and flexible pricing program programs or not. Due to the conditions of different types of electric power customers (such as whether their electrical behavior is flexible or not, whether they have own distributed power generation equipment or not, etc.), they will have different benefits and costs when they take part in the flexible pricing program which were executed by virtual power plants. Therefore, this study aims to use a quantitative economic benefit model to identify low-voltage lighting customers’, high-voltage customers’ and the whole society’s economic benefits and opportunity costs when they participate in virtual power plants’ operation, and continuously assess whether the participation of the electric power customers and whole society have economic feasibility or not, and make related policy recommendation base on the simulation result. According to the empirical analysis of this study, it shows that whether low-voltage lighting customers are willing to involve in the operation of virtual power plants or not, the most relevance is the discount of the demand charge of the flexible pricing program, and the economic benefits of participate in the operation of virtual power plant can’t be raised by changing the behavior (in basic simulation scenario, when the low-voltage lighting customer only participate the flexible pricing program, his BCR is 0.8732. The demand charge discount and energy charge discount were raised around 1.5 times in alternative plan, BCR were1.24 and 0.91；if we double the curtails times and the curtails kW number in summer months, the BCR would become 0.5 and 0.526); if the high-voltage customer can integrate and utilize his own distributed power generation equipment effectively to participate the operation of virtual power plants, under our simulation result, his NPV will be 2667931(NTD), and BCR will be 1.53, then it will have huge economic benefits. Moreover, from the holistic viewpoint of the society, if we can encourage electric power customers to join the flexible pricing program actively and construct more renewable energy generation equipment to supply power use, or store the electricity energy storage system further for emergency, it will help to slow down the building of peak load power plants, save the capacity avoided cost, and help to reduce the carbon emission at the same time. According to the simulation result of our empirical analysis, we have three mainly policy recommendations. The first is Taiwan Power Company should properly raise the current discount of basic demand charge in the Demand Bidding Program up to 100 (NTD / per kW per month) or more, to increase the incentive compatibility and make customers have motivations to coordinate with the energy conservation policy of the government. The second is the government can develop virtual power plant or similar industries like Aggregator, to integrate the low-voltage lighting customer of low electric demand and let the low-voltage lighting customer have more opportunities of the self-selection pricing scheme. In short, by implementing crowdsourcing to achieve the energy conservation policy. The last one is the plan of the electricity policy should be state with cross-system idea, not just enhance the connection among renewable energy itself but the connection between renewable energy, energy storage system and flexible pricing program, using the new technology of the energy management to systematically integrate the supply and demand agent.

碩士
國立中山大學
通訊工程研究所
102
In recent years, the concept of the virtual power plant is receiving a great deal of attention in the literature because of owing the following two potentials. One is that the virtual power plant can protect the power system by controlling the demand response customers and the energy storage systems to confine the power demand to the power system restriction. The other is that the virtual power plant can integrate the renewable power with the power system. By controlling the energy storage systems, the virtual power plant can solve the harmful impact of the renewable power. Although the virtual power plant benefits the power system, the investigators are wondering about the profit of running the virtual power plant. For this reason, we aim to study a way on earning the profit by controlling the demand response customers and the energy storage systems. With the proposed method, the business owners can understand how to run the virtual power plant.

博士
國立成功大學
電機工程學系
107
In light of the development of renewable energy and concerns over environmental protection, renewable energy resources have become a trend in distribution systems. Accordingly, the dispatch strategy of the system need to be changed. As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant plays a key role as not only a consumer but a prosumer. The structure also transform the traditional one-direction power delivery to bi-direction. The virtual power plant thus can enable itself to supply energy and ancillary services to the utility grid to maximize its profit. To deal with the security, dispatch, operation and bidding issues faced by VPP, this dissertation proposes an overcurrent protection strategies with distributed generations and fault current limiters, the demand response potential analysis, elasticity demand response model construction, and operation and bidding strategy determination. By scheduling the energy storage systems, demand response, and renewable energy sources, virtual power plants can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, a bi-level game theory model is introduced to modify the bidding environment among market operators and all the participants. The numerical results demonstrate the stable operation and profit maximized can be achieved through the proposed adaptive protection scheme and operation and bidding strategy optimization. By involving the uncertainty consideration and thus getting rid of penalty due to failing to provide the winning ancillary service quantity, the economic efficiency is proved to be increased.

With increasing penetration of intermittent resources such as wind and solar, power system operations are facing much more challenges in cost effective provision of energy balancing and frequency regulation services. Enabled by advances in sensing, control and communication, the concept of Virtual Power Plant (VPP) is proposed as one possible solution which aggregates and firms up spatially distributed resources? net power injection to the system. This thesis proposes a coordinated control and bidding strategy for VPPs to provide energy balancing and grid frequency regulation services in electricity market environment. In this thesis, the VPP consists of two energy conversion assets: a Doubly Fed Induction Generator (DFIG)-based wind farm and a co-located Flywheel Energy Storage System (FESS). The coordination of the VPP is implemented through power electronics?based controllers. A five-bus system test case demonstrates the technical feasibility of VPPs to respond to grid frequency deviation as well as to follow energy dispatch signals. To enable the participation of VPPs in electricity market, this thesis also proposes an optimization based bidding strategy for VPPs in both energy balancing and frequency regulation service markets. The potential economic benefits of this bidding strategy are demonstrated under Denmark wholesale electricity market structure. Four case studies show the economic benefit of coordinating VPPs.

碩士
國立中興大學
高階經理人碩士在職專班
103
The development of heat pump system and virtual power plant in Taiwan has not yet mature. However, as domestic communities are gradually paying more attention to renewable energy, the framework of virtual power plant will be formed. The good opportunity for the development of heat pump system will be coming soon. In Taiwan, it is very important to explore the issue of how the heat pump system will be developed with the current trend of renewable energy to respond to market changes and adjust related innovative business model and its strategies. The study adopted “Delphi Method” to explore the business model of innovative management of heat pump system under framework of virtual power plant in Taiwan and plan the strategies in response to changes in the market. The author interviewed eight experts and scholars, including two professors from academia, the Secretary-General of Taiwan Heat Pumps Association, and five decision makers in supply chains of heat pump system. Interviewees filled in two rounds of questionnaires and provided professional opinions. According to the result of first-round survey: 1. The development of heat pump system in Taiwan has potential for steady growth, subject to the market niche. In particular, if Taiwan can follow the practice of advanced countries in terms of the innovative management of heat pump system under framework of virtual power plant and consider the development of renewable energy an indispensible part, the heat pump system will have a promising future in Taiwan; 2. The trend of global energy, governmental policy of energy, consumer awareness, and scale of market are key factors which affect the development of heat pump system in Taiwan; 3. It is recommended that the heat pump system in Taiwan develop its own brand to expand the scale of market, manage core technologies, and improve competitiveness; 4. It is feasible to rent the equipment or save the energy expenses to pay the purchase cost of equipment. However, the best way is to take individual clients’ best interest into account and provide different programs and increase customers’ willingness to purchase a heat pump system based on the concept of investment; and 5. It is feasible to consider the heat pump as distributed power under the framework of virtual power plant, combined with the demand response program proposed by the power company in the innovative business model, which focuses on the degree of consumers’ awareness and the attraction to consumers. Due to different professional backgrounds of experts and scholars, the focuses on questions varied. Accordingly, the second round of questionnaire was compiled based on the result of first round and provided for interviewees to choose answers to questions. According to the result of second-round survey: 1. The price is the most important key to the promotion of heat pump system, followed by market visibility, standard of governmental regulations, and subsidies; 2. Sales of heat pump system could be improved by providing after-sale service, reducing the price of heat pump system, and helping clients obtain premium demand response programs; and 3. The reason why consumers resisted the business model of integration of heat pump system and demand response program was that consumers did not understand the actual benefits generated from the heat pump system. Moreover, such business model was so complicated that consumers tended to remain status quo and resist the heat pump system. The study obtained the applicable business model of innovative management of heat pump system under the framework of virtual power plant with a favorable price in the demand response program. In addition, the study also proposed necessary strategies for development of heat pump system in response to gradually popular trend of renewable energy and distributed generation facilities. The core value of heat pump system is that the heat pump is one of renewable energy which is obtained from air, waters, soil in nature as well as a distributed generation facility which can store energy. Since the power supply from renewable energy is not steady, the energy storage system like heat pump is required to serve as an indispensable component during high-proportion power generation of renewable energy. Keywords: Virtual power plant, Heat pump system, Delphi method, Innovative business model, Energy service company, Aggregator, The third party

Yes
The penetration of renewable energies in the energy market has increased significantly over the last two decades due to environmental concerns and clean energy requirements. The principal advantage of renewable energy resources (RESs) over non-RESs is that it has no direct carbonisation impact on the environment and that it has none of the global warming effects which are caused by carbon emissions. Furthermore, the liberalisation of the energy market has led to the realisation of the virtual power plant (VPP) concept. A VPP is a unified platform for distributed energy resources that integrates the capacities of various renewable energies together for the purpose of improving power generation and management as well as catering for the buying and selling of energy in wholesale energy markets. This review study presents a comprehensive review of existing approaches to planning, operation and scheduling of the VPP system. The methodologies that were adopted, their advantages and disadvantages are assessed in detail in order to benefit new entrants in the power system and provide them with comprehensive knowledge, techniques and understanding of the VPP concept.

Climate change concerns due to the rising amounts of carbon gas in the atmosphere have in the last decade or so initiated a fast pace of technological advances in the renewable energy industry. Such developments in technology and the move towards cleaner sources of energy have made renewable resources based Distributed Generators (DGs) more desirable. However, it is a known fact that rising penetrations of DGs have adverse impacts on the grid structure and its operation. The smart grid concept has been used as a good solution to control the impact of DGs and make conventional grids more suitable for large scale deployments of DGs.

O setor energético tem enfrentado ao longo dos últimos anos um aumento crescente da procura, resultante por um lado da massificação de novas tecnologias, bem como da evolução económica a nível mundial. Da mesma forma, a produção de energia é feita, cada vez mais, à base de fontes renováveis de forma a minimizar a dependência fóssil e o número de emissões poluentes. Estas modificações têm provocado alterações estruturais, quer na topologia, quer na operação dos sistemas elétricos, levando ao aparecimento de ferramentas de recursos energéticos distribuídos. Do lado da geração, tornaram-se cada vez mais frequentes as unidades de produção dispersa, fontes de energia mais próximas dos locais de carga, enquanto que, do lado dos consumidores, novas aplicações tecnológicas, como os veículos elétricos e a sua capacidade de fluxo de energia bidirecional - tecnologia Vehicle-to-Grid (V2G) - têm feito mudar o típico papel de cliente. Tais alterações tornam-se particularmente desafiantes ao nível da rede de distribuição. Nesse contexto, surge o conceito de Technical Virtual Power Plant (TVPP), cujo princípio de funcionamento fundamental consiste na agregação de pequenos produtores e fontes de potência, numa rede virtual de geração de energia. Este conceito visa dotar a rede de maior flexibilidade, contribuindo simultaneamente para um aumento da qualidade e da fiabilidade da energia elétrica, traduzindo-se ainda em benefícios económicos. Neste trabalho, desenvolveu-se um modelo de otimização estocástico de programação linear inteira mista, com o principal objetivo de providenciar flexibilidade ao sistema de distribuição, no contexto de uma TVPP capaz de agregar, em alguns dos seus nós, unidades de produção dispersa e veículos elétricos capazes de fornecer energia à rede. O modelo é testado usando o sistema de teste IEEE 119 Bus, sendo possível verificar que, com a inclusão de unidades de produção dispersa e V2G, o lucro da TVPP aumenta 45,4%.
The energy sector has faced a growing increase in demand over the past few years, resulting from the introduction of new technologies, as well as from economic development worldwide. Similarly, energy production based on renewable sources is increasingly used to minimize fossil fuel dependency and the associated emissions. These factors have resulted in structural changes, both in topology and operation of the electrical system, leading to the appearance of distributed energy resources (DERs) technologies. On the production side, distributed generation (DG) units, that are energy sources closer to the site of the load, have become increasingly common, while on the demand side, new technological applications, such as electric vehicles with their bidirectional flow capability (Vehicle-to-Grid (V2G) technology) have changed the typical customer role. Such changes have become particularly important at the distribution network level. In this context, the concept of a Technical Virtual Power Plant (TVPP) emerges, whose fundamental operating principle consists of the aggregation of small producers and power sources into a virtual power generation network. This concept aims to enhance the flexibility of the grid, while contributing to an increase in the quality and reliability of electric energy, which also brings economic benefits. In this thesis, a stochastic mixed-integer linear programming (MLIP) optimization model was developed. The main objective was providing flexibility to the distribution system through the concept a TVPP who is responsible for aggregating, DG units and electrical vehicles (EVs) capable of supplying energy to the grid at some of the nodes of the TVPP. The model is tested using the IEEE 119 Bus test system, and results show that with the inclusion of DG units and V2G, the profit of a TVPP increases by 45.4%.

O setor energético tem enfrentado ao longo dos últimos anos um aumento crescente da procura, resultante por um lado da massificação de novas tecnologias, bem como da evolução económica a nível mundial. Da mesma forma, a produção de energia é feita, cada vez mais, à base de fontes renováveis de forma a minimizar a dependência fóssil e o número de emissões poluentes. Estas modificações têm provocado alterações estruturais, quer na topologia, quer na operação dos sistemas elétricos, levando ao aparecimento de ferramentas de recursos energéticos distribuídos. Do lado da geração, tornaram-se cada vez mais frequentes as unidades de produção dispersa, fontes de energia mais próximas dos locais de carga, enquanto que, do lado dos consumidores, novas aplicações tecnológicas, como os veículos elétricos e a sua capacidade de fluxo de energia bidirecional - tecnologia Vehicle-to-Grid (V2G) - têm feito mudar o típico papel de cliente. Tais alterações tornam-se particularmente desafiantes ao nível da rede de distribuição. Nesse contexto, surge o conceito de Technical Virtual Power Plant (TVPP), cujo princípio de funcionamento fundamental consiste na agregação de pequenos produtores e fontes de potência, numa rede virtual de geração de energia. Este conceito visa dotar a rede de maior flexibilidade, contribuindo simultaneamente para um aumento da qualidade e da fiabilidade da energia elétrica, traduzindo-se ainda em benefícios económicos. Neste trabalho, desenvolveu-se um modelo de otimização estocástico de programação linear inteira mista, com o principal objetivo de providenciar flexibilidade ao sistema de distribuição, no contexto de uma TVPP capaz de agregar, em alguns dos seus nós, unidades de produção dispersa e veículos elétricos capazes de fornecer energia à rede. O modelo é testado usando o sistema de teste IEEE 119 Bus, sendo possível verificar que, com a inclusão de unidades de produção dispersa e V2G, o lucro da TVPP aumenta 45,4%.
The energy sector has faced a growing increase in demand over the past few years, resulting from the introduction of new technologies, as well as from economic development worldwide. Similarly, energy production based on renewable sources is increasingly used to minimize fossil fuel dependency and the associated emissions. These factors have resulted in structural changes, both in topology and operation of the electrical system, leading to the appearance of distributed energy resources (DERs) technologies. On the production side, distributed generation (DG) units, that are energy sources closer to the site of the load, have become increasingly common, while on the demand side, new technological applications, such as electric vehicles with their bidirectional flow capability (Vehicle-to-Grid (V2G) technology) have changed the typical customer role. Such changes have become particularly important at the distribution network level. In this context, the concept of a Technical Virtual Power Plant (TVPP) emerges, whose fundamental operating principle consists of the aggregation of small producers and power sources into a virtual power generation network. This concept aims to enhance the flexibility of the grid, while contributing to an increase in the quality and reliability of electric energy, which also brings economic benefits. In this thesis, a stochastic mixed-integer linear programming (MLIP) optimization model was developed. The main objective was providing flexibility to the distribution system through the concept a TVPP who is responsible for aggregating, DG units and electrical vehicles (EVs) capable of supplying energy to the grid at some of the nodes of the TVPP. The model is tested using the IEEE 119 Bus test system, and results show that with the inclusion of DG units and V2G, the profit of a TVPP increases by 45.4%.

碩士
臺灣大學
環境工程學研究所
98
Virtual power plant (VPP) is contemplated in this research, which considers electricity supply and electricity final demand, to decrease the environmental impact by changing of the electricity consumption patterns. The electricity consumption varied with electricity final demand is analyzed by the electricity input-output analysis (EIOA), and the environment impact is quantified by life cycle assessment (LCA), including human toxicity (carcinogenic and non-carcinogenic), respiratory, photochemical oxidation, terrestrial ecotoxicity, aquatic ecotoxicity, aquatic acidification, aquatic eutrophication and global warming. According to EIOA in 2008, the electricity consumptions of industries account for 80% total electricity consumption in Taiwan, and the electricity consumptions of industries are provided to household consumption, export, and other demands. Export is the main demand, which accounts for 58% of the industrial electricity consumption. Besides, sensitive industries of electricity consumption in Taiwan are divided by EIOA into 11 industries, including chemical material, textiles mills, pulp paper and paper products, chemical products, plastic products, non-metallic mineral products, iron and steel, fabricated metal products, electronic parts & components, computers electronic & Optic Prod and electrical equipment. Compared with EIOA in 2008, VPP is conducted in electricity strategy by adjusting electricity efficiency and electricity supply structure. On one hand, increasing 30% electricity efficiency in sensitive industries and insensitive industries reduce 16.38% and 13.62% industrial electricity consumption, respectively. On the other hand, electricity supply structure of sensitive industries is modified by using liquid nature gas (LNG) as an alternative fuel for the cogeneration system and installing decentralized generation system (DES). The fomer reduces 9-17% environmental impact in human toxicity (carcinogenic), respiratory, terrestrial ecotoxicity and aquatic acidification; the latter reduces 6-10% environmental impact in human toxicity (non-carcinogenic), aquatic ecotoxicity and aquatic eutrophication; and both reduce 7-9% environmental impact in photochemical oxidation and global warming. In summary, owing to reduction of environmental impact categorically, VPP is revealed enough as the electricity consumption pattern to decrease environmental impact.

碩士
國立中山大學
電機工程學系研究所
103
Owing to the increase of power demand and rising awareness of environmental protection, people start to adopt clean power. Many countries enact codes to promote the development of renewable energy, including photovoltaic, wind turbine and hydro generator. The growing demand has been a heavy burden on the power system. In order to meet the demand, the concept of virtual power plant has been proposed. The concept integrates the operation of supply-side and demand-side assets to meet customer demand for energy services in both the short-term and long-term. In short-term, virtual power plant makes extensive and sophisticated use of information technology, smart meter, automated control capabilities and electricity storage to match load fluctuations. The concept also treats long-term load reduction achieved through energy efficiency investments, distributed generation, and demand response. Using real-time pricing and demand response schemes, customer energy usage can be charged according to tariff structure to move the non-critical demand to off-peak periods, such as washing machines, dehumidifiers and dish driers. Demand response is one of demand side management schemes. Through adequate incentive offers to customers, peak load demand can be reduced at rush hours, and customer bills can be reduced. In this thesis, we build a virtual power plant model and use the concept of demand response and time of use pricing to control the distributed energy resources, such as battery energy storage system, to maximize the profits. A demand response contract is designed and different factors are taken into account in operation scheduling.

We discuss a model of a virtual power plant (VPP) that provides market access to privately-owned distributed generations (DGs). The VPP serves passive loads, processes bids from generators, and trades in the wholesale market. The generators can be renewable or thermal, and they act strategically to maximize their own profit. The VPP establishes the rules of the internal market to minimize the cost of energy and the cost of balancing while ensuring generator participation and load balancing. We derive a heuristic mechanism for internal market and propose a dynamic programming approach for minimizing the VPP cost. We present illustrative simulations for both single and multistage market bidding and then compare the resulting performance to the centralized VPP model, where the DGs are assumed to be owned by the VPP. We show that the proposed design incentivizes the DG agents to behave the same as in the centralized case, but the optimal cost paid by VPP is higher due to the payments to the DG owners.

碩士
國立中山大學
電機工程學系研究所
107
With the increase of power demand, rising concern of environment protection and decommission of nuclear and fossil fuel power plants, the utility companies are facing with various challenges. Renewable energy, such as solar photovoltaic, wind power in conjunction with energy storage system are integrated to the network in a rapid speed. Effective Coordination of these distributed energy resources could not only reduce the impacts to the system but also provide supports to system operations. This research uses the concept of virtual power plant to integrate the distributed resources in the distribution system to provide ancillary services to distribution system operator. Mathematical formulations of several ancillary services, including line losses optimization, congestion relief, voltage regulation and service restoration support, are presented. The dispatch of virtual power plant resources in a feeder level network during normal and emergency situations are studied and the enhancement of system efficiency and reliability due to the dispatch of the distributed energy resources is demonstrated.

Yes
Technological advancement on the electricity grid has focused on maximizing its use. This has led to the introduction of energy storage. Energy storage could be used to provide both peak and off-peak services to the grid. Recent work on the use of small units of energy storage like battery has proposed the vehicle to grid system. It is propose in this work to have energy storage device embedded inside the house of the energy consumer. In such a system, consumers with battery energy storage can be aggregated in to a community virtual power plant. In this paper, an optimized energy resource allocation algorithm is presented for a virtual power plant using genetic algorithm. The results show that it is critical to have a pricing scheme that help achieve goals for grid, virtual power plant, and consumers.
Mr. Oghenovo Okpako is grateful to the Niger Delta Development Commission of Nigeria for funding the work. The work has been also supported by the British Council and the UK Department of Business innovations and Skills under the GII funding of the SITARA project.