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1
Chang, Ya Chin, Sung Ling Chen, Rung Fang Chang, and Chan Nan Lu. "Optimal Virtual Power Plant Dispatching Approach." Applied Mechanics and Materials 590 (June 2014): 511–15. http://dx.doi.org/10.4028/www.scientific.net/amm.590.511.
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As the integrator of energy resources (DERs), a virtual power plant (VPP) would be able to control the amount of the power access to the distribution transformers such that energy efficiency can be improved. Battery energy storage system (BESS) and demand response (DR) as DERs can entrust the VPP with certain controllability to regulate the power supply of the distribution system. This paper aims to maximize the benefit of the supplied powers over the 24 hours under VPP operation. Combining an iterative dynamic programming optimal BESS schedule approach and a PSO-based DR scheme optimization approach, an optimal VPP operational method is proposed to minimize the total electricity cost with respect to the power supply limit of the distribution transformers and the system security constraints, especially, within the peak load hours. With the TOU rate given each hour, test results had confirmed the validity of the proposed method with the obviously decreased power supply in each peak-load hours and the largely reduced electricity cost accordingly.
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Li, Tian Ran, Yun Hu Luo, and Lin Sun. "Risk Management of Virtual Power Plant Reserve Allocation." Applied Mechanics and Materials 448-453 (October 2013): 2695–98. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2695.
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Virtual Power Plant (VPP) is a new entity in power systems that manages a set of various distributed energy resources (DERs). One of the functions of VPP is to determine the allocation of reserve to solve the problem of renewable generation uncertainty. In this paper, the reserve resources of VPP are classified into non-renewable distributed generation (NRDG), energy storage device (ESD), interruptible load (IL) and reserve bought from the market (RBFM). Their complementary properties should be utilized to improve the economy of reserve allocation. An optimal coordination model for risk management of NRDG configuration of VPP reserve allocation is proposed. Simulation results are presented to validate that an optimal value of NRDG configuration should exist.
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Sun, Zhong Wei. "Communication System Architecture for Hierarchical Virtual Power Plant Control." Applied Mechanics and Materials 631-632 (September 2014): 878–81. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.878.
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Virtual Power Plant (VPP) is recognized as essential for the successful implementation of smart grids, and information communication technology is enabling technology for VPP implementation. However, finding the most appropriate technology that can satisfy their future communication needs is still an unsolving issue for VPP. Focusing on the hierarchial VPP control model, and utilizing Ethernet Passive Optical Network (EPON) network technology, this paper has presented an EPON-based communication architecture for virtual power plant.
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Su, Da Wei, Ji Nian Pang, and Hao Jiang. "Review on Functions and Control Technologies of Virtual Power Plant." Applied Mechanics and Materials 644-650 (September 2014): 3767–72. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3767.
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The basic design concept and the necessities of virtual power plant (VPP) are introduced after analyzing the future conditions of global energy demand. According to the differences in functions, VPP is divided into two roles, the commercial virtual power plant and the technical virtual power plant. After comparing their characteristics, related connections between them are proposed. Power quality control technologies and auxiliary services provided by VPP are discussed in detail based on current domestic and international research situation. Finally three scheduling control modes, the centralized mode, the decentralized mode and the distributed mode are compared. Correspondingly, the result that distributed control mode is more suitable for optimal scheduling control of VPP is pointed out.
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Geng, Shiping, Caixia Tan, Dongxiao Niu, and Xiaopeng Guo. "Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles." Mathematical Problems in Engineering 2021 (June 12, 2021): 1–19. http://dx.doi.org/10.1155/2021/5552323.
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To push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP with electric vehicles and models each unit of the VPP. Secondly, the typical scenarios of wind power, photovoltaic, electric vehicle charging and discharging, and load are formed by the Monte Carlo method to reduce the output deviation of each unit. Then, taking the maximization of the net income and clean energy consumption of the VPP as the objective function, the capacity optimal allocation model of the VPP considering multiobjective is constructed, and the conditional value-at-risk (CVaR) is introduced to represent the investment uncertainty faced by the VPP. Finally, a VPP in a certain area of Shanxi Province is used to analyze a calculation example and solve it with CPLEX. The results of the calculation example show that, on the one hand, reasonable selection of the optimal scale of EV connected to the VPP is able to improve the economy and environment of the VPP. On the other hand, the introduction of CVaR is available for the improvement of the scientific nature of VPP capacity allocation decisions.
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Oh, Eunsung. "Risk-Based Virtual Power Plant Implementation Strategy for Smart Energy Communities." Applied Sciences 11, no. 17 (2021): 8248. http://dx.doi.org/10.3390/app11178248.
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This paper focuses on a virtual power plant (VPP) implementation strategy for smart local energy communities (SECs) with energy service providers. It is difficult to balance energy in the implementation stage due to uncertainties in demand and resources. Therefore, VPP implementation was modeled using the risk factor of energy balance. Using this risk factor, it was shown that the temporal correlation between demand and resources was the dominant factor involved in VPP implementation. Based on this, two risk-based VPP implementation strategies are proposed: an optimization-based strategy and a simple strategy that is solved in an iterative way. To minimize VPP implementation costs, the proposed strategies select the resources that have high correlation coefficients with demand and low correlation coefficients with other resources. Experimental results using real data sets show that the proposed strategies based on the risk factor are effective means of VPP implementation for commercial and residential SECs. The results imply that VPPs for commercial SECs are possible when PV is used as the main resource and is supplemented by wind, and it is effective to configure VPPs for residential SECs using wind according to the correlation between demand and resources.
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Duan, Jie, Xiaodan Wang, Yajing Gao, et al. "Multi-Objective Virtual Power Plant Construction Model Based on Decision Area Division." Applied Sciences 8, no. 9 (2018): 1484. http://dx.doi.org/10.3390/app8091484.
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Virtual power plant (VPP) is an effective technology form to aggregate the distributed energy resources (DERs), which include distributed generation (DG), energy storage (ES) and demand response (DR). The establishment of a unified and coordinated control of VPP is an important means to achieve the interconnection of energy internet. Therefore, this paper focuses on the research of VPP construction model. Firstly, a preliminary introduction on all kinds of the DERs is carried out. According to the relevant guidelines, the decision area of the VPP is carefully divided, and the decision variables representing the various resources in the area are determined. Then, in order to get a VPP with low daily average cost, good load characteristics, high degree of DG consumption and high degree of resource aggregation, a multi-objective VPP construction model based on decision area division is established, and various constraints including geographic information are considered. The improved bat algorithm based on priority selection is used to solve this model. Finally, the correctness and effectiveness of the model are verified by an example.
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Candra, Dodiek, Kilian Hartmann, and Michael Nelles. "Economic Optimal Implementation of Virtual Power Plants in the German Power Market." Energies 11, no. 9 (2018): 2365. http://dx.doi.org/10.3390/en11092365.
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The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energy availability and the marginal costs of the VPP components. The size of the VPP components is positively correlated to the components’ share of the energy generated. It was also found that projecting or implementing VPPs in Germany at current market prices (EPEX/EEX prices) is not yet economically feasible for a small share of market products. However, the secured power can be marketed on the SPOT and in the futures market with higher and more stable prices compared with the status quo.
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Podder, Amit Kumer, Sayemul Islam, Nallapaneni Manoj Kumar, et al. "Systematic Categorization of Optimization Strategies for Virtual Power Plants." Energies 13, no. 23 (2020): 6251. http://dx.doi.org/10.3390/en13236251.
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Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.
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Lin, Whei-Min, Chung-Yuen Yang, Zong-Yo Wu, and Ming-Tang Tsai. "Optimal Control of a Virtual Power Plant by Maximizing Conditional Value-at-Risk." Applied Sciences 11, no. 16 (2021): 7752. http://dx.doi.org/10.3390/app11167752.
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This research acquired data from the Central Weather Bureau Observation Data Inquiry System (CODIS) for historical weather information, such as observation time, temperature, humidity, wind speed, global radiation, etc., and constructed a historical weather database by using Excel software. Least square support vector machine (LSSVM) was used to forecast wind speed and solar radiation; then, the power output of wind and solar was derived. Considering factors of the demand response and the load and electricity pricing, a maximized risk income model of the virtual power plant (VPP) is established based on conditional value-at-risk (CVAR). An enhanced bacterial foraging algorithm (EBFA) was proposed to solve the risk dispatch problem of a VPP in this paper. In an EBFA, the stochastic weight trade-off is embedded to improve the behavior pattern of individual bacteria to enhance their sorting efficiency and accuracy in a high-dimension solution space. Various moving patterns of EBFA were considered for improvement, which were demonstrated by using a VPP system on Penghu island, Taiwan. Many scenarios were created, including various seasons, power rebate pricings, and confidence levels, so the maximal risk and return of VPP could be simulated and analyzed. Simulation and tests show a positive result for a VPP to perform the power dispatch by maximizing risk income. This paper also provides a guideline for the VPP to handle the risk management.
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Jasiński, Michał. "Combined Correlation and Cluster Analysis for Long-Term Power Quality Data from Virtual Power Plant." Electronics 10, no. 6 (2021): 641. http://dx.doi.org/10.3390/electronics10060641.
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Analysis of the connection between different units that operate in the same area assures always interesting results. During this investigation, the concerned area was a virtual power plant (VPP) that operates in Poland. The main distributed resources included in the VPP are a 1.25 MW hydropower plant and an associated 0.5 MW energy storage system. The mentioned VPP was a source of synchronic, long-term, multipoint power quality (PQ) data. Then, for five related measurement points, the conclusion about the relation in point of PQ was performed using correlation analysis, the global index approach, and cluster analysis. Global indicators were applied in place of PQ parameters to reduce the amount of analyzed data and to check the correlation between phase values. For such a big dataset, the occurrence of outliers is certain, and outliers may affect the correlation results. Thus, to find and exclude them, cluster analysis (k-means algorithm, Chebyshev distance) was applied. Finally, the correlation between PQ global indicators of different measurement points was performed. It assured general information about VPP units’ relation in point of PQ. Under the investigation, both Pearson’s and Spearman’s rank correlation coefficients were considered.
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Jasiński, Michał, Tomasz Sikorski, Dominika Kaczorowska, et al. "A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements." Energies 14, no. 4 (2021): 974. http://dx.doi.org/10.3390/en14040974.
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One of the recent trends that concern renewable energy sources and energy storage systems is the concept of virtual power plants (VPP). The majority of research now focuses on analyzing case studies of VPP in different issues. This article presents the investigation that is based on a real VPP. That VPP operates in Poland and consists of hydropower plants (HPP), as well as energy storage systems (ESS). For specific analysis, cluster analysis, as a representative technique of data mining, was selected for power quality (PQ) issues. The used data represents 26 weeks of PQ multipoint synchronic measurements for 5 related to VPP points. The investigation discusses different input databases for cluster analysis. Moreover, as an extension to using classical PQ parameters as an input, the application of the global index was proposed. This enables the reduction of the size of the input database with maintaining the data features for cluster analysis. Moreover, the problem of the optimal number of cluster selection is discussed. Finally, the assessment of clustering results was performed to assess the VPP impact on PQ level.
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Yu, Jie, Qizhi Feng, Yang Li, and Jinde Cao. "Stochastic Optimal Dispatch of Virtual Power Plant considering Correlation of Distributed Generations." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/135673.
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Virtual power plant (VPP) is an aggregation of multiple distributed generations, energy storage, and controllable loads. Affected by natural conditions, the uncontrollable distributed generations within VPP, such as wind and photovoltaic generations, are extremely random and relative. Considering the randomness and its correlation of uncontrollable distributed generations, this paper constructs the chance constraints stochastic optimal dispatch of VPP including stochastic variables and its random correlation. The probability distributions of independent wind and photovoltaic generations are described by empirical distribution functions, and their joint probability density model is established by Frank-copula function. And then, sample average approximation (SAA) is applied to convert the chance constrained stochastic optimization model into a deterministic optimization model. Simulation cases are calculated based on the AIMMS. Simulation results of this paper mathematic model are compared with the results of deterministic optimization model without stochastic variables and stochastic optimization considering stochastic variables but not random correlation. Furthermore, this paper analyzes how SAA sampling frequency and the confidence level influence the results of stochastic optimization. The numerical example results show the effectiveness of the stochastic optimal dispatch of VPP considering the randomness and its correlations of distributed generations.
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Sun, Zhong Wei, and Jing Jiao. "A Survey of Vehicle-to-Grid Implementation through Virtual Power Plants." Applied Mechanics and Materials 631-632 (September 2014): 314–17. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.314.
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The Smart Grid uses two-way flows of electricity and information to create a widely distributed automated energy delivery network, and Vehicle-to-Grid (V2G) and Virtual Power Plant (VPP) are two innovative smart grid applications. This survey focuses on V2G implementation through VPPs. First, the concept of V2G and its architectures are introduced. Then VPP, a new power plant concept and its corresponding control methods are described. Finally, implementation strategies of V2G through VPPs are categorized.
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Ropuszyńska-Surma, Edyta, and Magdalena Węglarz. "The Virtual Power Plant – A Review Of Business Models." E3S Web of Conferences 108 (2019): 01006. http://dx.doi.org/10.1051/e3sconf/201910801006.
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The aim of the article is to present a critical comparison of different business models of Virtual Power Plant and pointing out both the common and the unique features for each model. Therefore, the American, German, Finnish, Danish and Australian VPP’s business models are described in the article. The VPP is an IT structure which integrates different types of distributed energy sources, flexible consumers and energy storage with each other and with other market segments in real time through a smart grid. The VPP gives positive effects on electricity grid like ensuring energy security, improving grid stability and reliability, optimization of energy resources use, lowering the load - demand response, regulation of frequency, using operational reserves, management of peak demand. The business model is perceived as a method of increasing and exploitation of company’s resources for preparing new products or services for customers in order to obtain added value (expanding the competition advantage or increasing profitability). A potential VPP’s business model in Polish conditions was proposed in case of two different types of customers.
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Tan, Zhong-fu, Huan-huan Li, Li-wei Ju, and Qing-kun Tan. "Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory." Mathematical Problems in Engineering 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/3810492.
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The installation capacity of wind and solar photovoltaic power is continually increasing, which makes renewable energy grid connection and power generation an important link of China’s power structure optimization. A virtual power plant (VPP) is an important way to help distributed energy resource grid connection and promote renewable energy industry development. To study the economic scheduling problem of various distributed energy resources and the profit distribution problem of VPP alliance, this study builds a separate operation scheduling model for individual VPP and a joint operation scheduling model for VPP alliance, as well as the profit distribution model. The case study verifies the feasibility and effectiveness of the proposed model. The sensitivity analysis provides information about VPP decision-making in accordance with the policy environment development trend.
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Oest, Frauke, Malin Radtke, Marita Blank-Babazadeh, Stefanie Holly, and Sebastian Lehnhoff. "Evaluation of Communication Infrastructures for Distributed Optimization of Virtual Power Plant Schedules." Energies 14, no. 5 (2021): 1226. http://dx.doi.org/10.3390/en14051226.
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With the transition towards renewable energy resources, the impact of small distributed generators (DGs) increases, leading to the need to actively stabilize distribution grids. DGs may be organized in virtual power plants (VPPs), where DGs’ schedules must be coordinated to enable the VPP to act as a single plant. One approach to solving this problem is using multi-agent systems (MAS) to offer autonomous, robust, and flexible control methods. The coordination of such systems requires communication between agents. The time required for this depends on communication characteristics, determined by the underlying communication infrastructure. In this paper, we investigate communication influences for the wireless technologies CDMA450 and LTE Advanced on the fully distributed optimization heuristic COHDA, which is used to perform optimized scheduling for a VPP. The use case under consideration is the adaptation of schedules to provide flexibility for regional congestion management for delivery on a regionalized ancillary service market (rAS). We investigate the scalability of the VPP and the effects of disturbances in the communication infrastructure. The results show that the optimization duration of COHDA can be influenced by the underlying communication infrastructure and that this optimization method is applicable to a limited extent for product delivery of rASs.
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Pal, Poushali, Parvathy Ayalur Krishnamoorthy, Devabalaji Kaliaperumal Rukmani, et al. "Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework." Applied Sciences 11, no. 9 (2021): 3814. http://dx.doi.org/10.3390/app11093814.
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Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.
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Kaczorowska, Dominika, Jacek Rezmer, Michal Jasinski, et al. "A Case Study on Battery Energy Storage System in a Virtual Power Plant: Defining Charging and Discharging Characteristics." Energies 13, no. 24 (2020): 6670. http://dx.doi.org/10.3390/en13246670.
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A virtual power plant (VPP) can be defined as the integration of decentralized units into one centralized control system. A VPP consists of generation sources and energy storage units. In this article, based on real measurements, the charging and discharging characteristics of the battery energy storage system (BESS) were determined, which represents a key element of the experimental virtual power plant operating in the power system in Poland. The characteristics were determined using synchronous measurements of the power of charge and discharge of the storage and the state of charge (SoC). The analyzed private network also includes a hydroelectric power plant (HPP) and loads. The article also examines the impact of charging and discharging characteristics of the BESS on its operation, analyzing the behavior of the storage unit for the given operation plans. The last element of the analysis is to control the power flow in the private network. The operation of the VPP for the given scenario of power flow control was examined. The aim of the scenario is to adjust the load of the private network to the level set by the function. The tests of power flow are carried out on the day on which the maximum power demand occurred. The analysis was performed for four cases: a constant value limitation when the HPP is in operation and when it is not, and two limits set by function during normal operation of the HPP. Thus, the article deals not only with the issue of determining the actual characteristics of charging and discharging the storage unit, but also their impact on the operation of the entire VPP.
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Sikorski, Tomasz, Michal Jasiński, Edyta Ropuszyńska-Surma, et al. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects." Energies 13, no. 12 (2020): 3086. http://dx.doi.org/10.3390/en13123086.
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The article presents calculations and power flow of a real virtual power plant (VPP), containing a fragment of low and medium voltage distribution network. The VPP contains a hydropower plant (HPP), a photovoltaic system (PV) and energy storage system (ESS). The purpose of this article is to summarize the requirements for connection of generating units to the grid. Paper discusses the impact of the requirements on the maximum installed capacity of distributed energy resource (DER) systems and on the parameters of the energy storage unit. Firstly, a comprehensive review of VPP definitions, aims, as well as the characteristics of the investigated case study of the VPP project is presented. Then, requirements related to the regulation, protection and integration of DER and ESS with power systems are discussed. Finally, investigations related to influence of DER and ESS on power network condition are presented. One of the outcomes of the paper is the method of identifying the maximum power capacity of DER and ESS in accordance with technical network requirements. The applied method uses analytic calculations, as well as simulations using Matlab environment, combined with real measurement data. The obtained results allow the influence of the operating conditions of particular DER and ESS on power flow and voltage condition to be identified, the maximum power capacity of ESS intended for the planed VPP to be determined, as well as the influence of power control strategies implemented in a PV power plant on resources available for the planning and control of a VPP to be specified. Technical limitations of the DER and ESS are used as input conditions for the economic simulations presented in the accompanying paper, which is focused on investigations of economic efficiency.
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Bianchi, Stefano, Allegra De Filippo, Sandro Magnani, Gabriele Mosaico, and Federico Silvestro. "VIRTUS Project: A Scalable Aggregation Platform for the Intelligent Virtual Management of Distributed Energy Resources." Energies 14, no. 12 (2021): 3663. http://dx.doi.org/10.3390/en14123663.
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The VIRTUS project aims to create a Virtual Power Plant (VPP) prototype coordinating the Distributed Energy Resources (DERs) of the power system and providing services to the system operators and the various players of the electricity markets, with a particular focus on the industrial sector agents. The VPP will be able to manage a significant number of DERs and simulate realistic plants, components, and market data to study different operating conditions and the future impact of the policy changes of the Balancing Markets (BM). This paper describes the project’s aim, the general structure of the proposed framework, and its optimization and simulation modules. Then, we assess the scalability of the optimization module, designed to provide the maximum possible flexibility to the system operators, exploiting the simulation module of the VPP.
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Moreno, Guillermo, Carlos Santos, Pedro Martín, Francisco Javier Rodríguez, Rafael Peña, and Branislav Vuksanovic. "Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants." Sensors 21, no. 16 (2021): 5648. http://dx.doi.org/10.3390/s21165648.
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Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. This paper introduces a method to efficiently produce intra-day accurate Photovoltaic (PV) power forecasts at different locations, by using free and available information. Prediction intervals, which are based on the Mean Absolute Error (MAE), account for the forecast uncertainty which provides additional information about the VPP node power generation. The performance of the forecasting strategy has been verified against the power generated by a real PV installation, and a set of ground-based meteorological stations in geographical proximity have been used to emulate a VPP. The forecasting approach is based on a Long Short-Term Memory (LSTM) network and shows similar errors to those obtained with other deep learning methods published in the literature, offering a MAE performance of 44.19 W/m2 under different lead times and launch times. By applying this technique to 8 VPP nodes, the global error is reduced by 12.37% in terms of the MAE, showing huge potential in this environment.
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Przychodzień, Arkadiusz. "Virtual power plants - types and development opportunities." E3S Web of Conferences 137 (2019): 01044. http://dx.doi.org/10.1051/e3sconf/201913701044.
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Modern power engineering meets new challenges. With the development of new energy production and storage technologies, creates new demands for energy services. To support this development, it is necessary to implement new teleinformatic systems that will allow for resource management. Such systems are called Virtual Power Plants (VPP). There are many definitions of this type of solutions due to the very wide range of possible applications. VPPs can be developed by many types of entities, e.g. distribution system operators, electricity generators, energy clusters. The ability to build a system based on modules allows you to customize the system to user’s needs. An opportunity for the development of VPP will be a package “Clean energy for all Europeans” (so called “Winter package”) that introduces regulations that allow for the development of renewable energy sources, including prosumers, and enables an active participation in the energy market for energy consumers. In addition, more stringent requirements for balancing production and energy consumption are introduced, requiring greater balancing accuracy.
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Gao, Rui, Hongxia Guo, Ruihong Zhang, et al. "A Two-Stage Dispatch Mechanism for Virtual Power Plant Utilizing the CVaR Theory in the Electricity Spot Market." Energies 12, no. 17 (2019): 3402. http://dx.doi.org/10.3390/en12173402.
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The electricity spot market is now being implemented in China. Demand response, as a kind of flexible resource, is also being studied and explored for the constructed power market. Among the many demand response applications, the virtual power plant (VPP) as an aggregator of distributed energy resources (DERs), receives ever-increasing attention. However, the participation manner and related impacts of the VPP to the electricity spot market are still unknown within the current power market rules. Under this background, obeying the present trading rules of China’s electricity spot market, a two-stage dispatching model with optimized bidding and operating strategy in the day-ahead (DA) and real-time (RT) market for the VPP is proposed. In the designed model, the conditional risk value (CVaR) is adopted to address the risk encountered by the uncertainty of the electricity spot market price. The impact of the user-side over-deviated revenue mechanism (UORM) of the China spot market on the income of the VPP in the DA and RT market is also analyzed. For a full evaluation, different coefficients for the influence of DA and RT risk, UORM, and energy storage system (ESS) are tested to investigate their respective impacts on the revenue of the VPP. The simulation cases prove that the proposed method is helpful for the VPP to optimize DERs’ output in the electricity spot market according to its own risk preference.
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Ko, Rakkyung, and Sung-Kwan Joo. "Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants." Energies 13, no. 1 (2019): 67. http://dx.doi.org/10.3390/en13010067.
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Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method.
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Alhelou, Hassan Haes, Pierluigi Siano, Massimo Tipaldi, Raffaele Iervolino, and Feras Mahfoud. "Primary Frequency Response Improvement in Interconnected Power Systems Using Electric Vehicle Virtual Power Plants." World Electric Vehicle Journal 11, no. 2 (2020): 40. http://dx.doi.org/10.3390/wevj11020040.
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The smart grid concept enables demand-side management, including electric vehicles (EVs). Thus way, some ancillary services can be provided in order to improve the power system stability, reliability, and security. The high penetration level of renewable energy resources causes some problems to independent system operators, such as lack of primary reserve and active power balance problems. Nowadays, many countries are encouraging the use of EVs which provide a good chance to utilize them as a virtual power plant (VPP) in order to contribute to frequency event. This paper proposes a new control method to use EV as VPP for providing primary reserve in smart grids. The primary frequency reserve helps the power system operator to intercept the frequency decline and to improve the frequency response of the whole system. The proposed method calculates the electric vehicles’ primary reserve based on EVs’ information, such as the state of charge (SOC), the arriving time and the vehicle’s departure time. The effectiveness of the proposed scheme is verified by several simulation scenarios on a real-world modern power system with different generating units, such as conventional power plants, renewable energy resources, and electric vehicles.
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Jasiński, Michal, Tomasz Sikorski, Dominika Kaczorowska, et al. "A Case Study on Power Quality in a Virtual Power Plant: Long Term Assessment and Global Index Application." Energies 13, no. 24 (2020): 6578. http://dx.doi.org/10.3390/en13246578.
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The concept of virtual power plants (VPP) was introduced over 20 years ago but is still actively researched. The majority of research now focuses on analyzing case studies of such installations. In this article, the investigation is based on a VPP in Poland, which contains hydropower plants (HPP) and energy storage systems (ESS). For specific analysis, the power quality (PQ) issues were selected. The used data contain 26 weeks of multipoint, synchronic measurements of power quality levels in four related points. The investigation is concerned with the application of a global index to a single-point assessment as well as an area-related assessment approach. Moreover, the problem of flagged data is discussed. Finally, the assessment of VPP’s impact on PQ level is conducted.
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Behi, Behnaz, Ali Baniasadi, Ali Arefi, Arian Gorjy, Philip Jennings, and Almantas Pivrikas. "Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study." Energies 13, no. 10 (2020): 2614. http://dx.doi.org/10.3390/en13102614.
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Achieving the renewable energy integration target will require the extensive engagement of consumers and the private sector in investment and operation of renewable-based energy systems. Virtual power plants are an efficient way to implement this engagement. In this paper, the detailed costs and benefits of implementing a realistic virtual power plant (VPP) in Western Australia, comprising 67 dwellings, are calculated. The VPP is designed to integrate and coordinate rooftop solar photovoltaic panels (PV), vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and demand management mechanisms. An 810-kW rooftop solar PV system is designed and located using the HelioScope software. The charging and the discharging of a 700-kWh VRFB are scheduled for everyday use over a year using an optimization algorithm, to maximize the benefit of it for the VPP owners and for the residents. The use of heat pump HWSs provides a unique opportunity for the residents to save energy and reduce the total cost of electricity along with demand management on some appliances. The cost-and-benefit analysis shows that the cost of energy will be reduced by 24% per dwelling in the context of the VPP. Moreover, the internal rate of return for the VPP owner is at least 11% with a payback period of about 8.5 years, which is a promising financial outcome.
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Jasiński, Michał, Tomasz Sikorski, Dominika Kaczorowska, et al. "A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data." Energies 14, no. 4 (2021): 907. http://dx.doi.org/10.3390/en14040907.
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The integration of virtual power plants (VPP) has become more popular. Thus, research on VPP for different issues is highly desirable. This article addresses power quality issues. The presented investigation is based on multipoint, synchronic measurements obtained from five points that are related to the VPP. This article provides a proposition and discussion of using one global index in place of the classical power quality (PQ) parameters. Furthermore, in the article, one new global power quality index was proposed. Then the PQ measurements, as well as global indexes, were used to prepare input databases for cluster analysis. The mentioned cluster analysis aimed to detect the short-term working conditions of VPP that were specific from the point of view of power quality. To realize this the hierarchical clustering using the Ward algorithm was realized. The article also presents the application of the cubic clustering criterion to support cluster analysis. Then the assessment of the obtained condition was realized using the global index to assure the general information of the cause of its occurrence. Furthermore, the article noticed that the application of the global index, assured reduction of database size to around 74%, without losing the features of the data.
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Gao, Yajing, Xiaojie Zhou, Jiafeng Ren, Xiuna Wang, and Dongwei Li. "Double Layer Dynamic Game Bidding Mechanism Based on Multi-Agent Technology for Virtual Power Plant and Internal Distributed Energy Resource." Energies 11, no. 11 (2018): 3072. http://dx.doi.org/10.3390/en11113072.
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As renewable energies become the main direction of global energy development in the future, Virtual Power Plant (VPP) becomes a regional multi-energy aggregation model for large-scale integration of distributed generation into the power grid. It also provides an important way for distributed energy resources (DER) to participate in electricity market transactions. Firstly, the basic concept of VPP is outlined, and various uncertainties within VPP are modeled. Secondly, using multi-agent technology and Stackelberg dynamic game theory, a double-layer nested dynamic game bidding model including VPP and its internal DERs is designed. The lower layer is a bidding game for VPP internal market including DER. VPP is the leader and each DER is a subagent that acts as a follower to maximize its profit. Each subagent uses the particle swarm algorithm (PSA) to determine the optimal offer coefficient, and VPP carries out internal market clearing with the minimum variance of unit profit according to the quoting results. Then, the subagents renew the game to update the bidding strategy based on the outcomes of the external and internal markets. The upper layer is the external market bidding game. The trading center (TC) is the leader and VPP is the agent and the follower. The game is played with the goal of maximum self-interest. The agent uses genetic algorithms to determine the optimal bid strategy, and the TC carries out market clearance with the goal of maximizing social benefits according to the quotation results. Each agent renews the game to update the bidding strategy based on the clearing result and the reporting of the subagents. The dynamic game is repeated until the optimal equilibrium solution is obtained. Finally, the effectiveness of the model is verified by taking the IEEE30-bus system as an example.
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Sikorski, Tomasz, Michał Jasiński, Edyta Ropuszyńska-Surma, et al. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Economic Aspects." Energies 12, no. 23 (2019): 4447. http://dx.doi.org/10.3390/en12234447.
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This paper analyzes the technical and economic possibilities of integrating distributed energy resources (DERs) and energy-storage systems (ESSs) into a virtual power plant (VPP) and operating them as a single power plant. The purpose of the study is to assess the economic efficiency of the VPP model, which is influenced by several factors such as energy price and energy production. Ten scenarios for the VPP were prepared on the basis of the installed capacities of a hydropower plant (HPP), rooftop solar photovoltaic (PV), and energy-storage system (ESS), as well as weather conditions, in Poland. On the basis of technical conditions, it was assumed that the maximum power capacity of the ESS equaled 1.5 MW. The economic efficiency analysis presented in this paper demonstrated that, in seven years, the VPP will achieve a positive value of the net present value (NPV) for a scenario with 0.5 MW battery storage and rainy summers. Furthermore, sensitivity analysis was conducted on price factors and DER production volume. The price variable had a major impact on the NPV value for all scenarios. The scenario with a 0.5 MW battery and typical summers was highly sensitive to all factors, and its sensitivity decreased as the ESS capacity grew from 0.5 to 1.5 MW.
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Dey, Partha Pratim, Dulal Chandra Das, Abdul Latif, S. M. Suhail Hussain, and Taha Selim Ustun. "Active Power Management of Virtual Power Plant under Penetration of Central Receiver Solar Thermal-Wind Using Butterfly Optimization Technique." Sustainability 12, no. 17 (2020): 6979. http://dx.doi.org/10.3390/su12176979.
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Striving for the suppression of greenhouse emissions, the modern power network is facing fundamental changes with the utilization of renewable energies (REs) for the future carbon-free society. The utilization of intermittent renewable-green power needs a better power management system and virtual power plant (VPP) can be a vital candidate that meets this demand. This study investigates a coordinated control grid integrated virtual power plant (VPP) in the presence of Central Receiver Solar Thermal System (CRSTS), Wind Turbine Generator (WTG), and Electric Vehicle (EV). To this end, CRSTS employed with thermal storage acts as a dispatchable renewable generating unit and coordinated control of the system units are achieved using the available control strategy on interconnected microgrids in the modified form, employing communication time delay. The proposed control strategy employs the proportional-integral (PI) and PI-derivative (PID) controller. Coordinated power control with real-time communication delay in grid integrated VPP in presence of CRSTS, WTG, and EV is a novel approach. Genetic algorithm (GA), Particle Swarm Optimization (PSO), Slap Swarm Algorithm (SSA), and recent Butterfly Optimization Algorithm (BOA) are used for tuning the necessary control parameters. The results establish the superiority of the BOA over SSA and PSO in suppressing system frequency deviations and tie line power deviation. The analysis of the dynamic response reveals that the consideration of the communication delay in the system expressively impedes the stable operation of the power system.
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Sun, Guoqiang, Weihang Qian, Wenjin Huang, et al. "Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach." Energies 12, no. 10 (2019): 1918. http://dx.doi.org/10.3390/en12101918.
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The present study establishes a stochastic adaptive robust dispatch model for virtual power plants (VPPs) to address the risks associated with uncertainties in electricity market prices and photovoltaic (PV) power outputs. The model consists of distributed components, such as the central air-conditioning system (CACS) and PV power plant, aggregated by the VPP. The uncertainty in the electricity market price is addressed using a stochastic programming approach, and the uncertainty in PV output is addressed using an adaptive robust approach. The model is decomposed into a master problem and a sub-problem using the binding scenario identification approach. The binding scenario subset is identified in the sub-problem, which greatly reduces the number of iterations required for solving the model, and thereby increases the computational efficiency. Finally, the validity of the VPP model and the solution algorithm is verified using a simulated case study. The simulation results demonstrate that the operating profit of a VPP with a CACS and other aggregated units can be increased effectively by participating in multiple market transactions. In addition, the results demonstrate that the binding scenario identification algorithm is accurate, and its computation time increases slowly with increasing scenario set size, so the approach is adaptable to large-scale scenarios.
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Luo, Jingjing, Yajing Gao, Wenhai Yang, Yongchun Yang, Zheng Zhao, and Shiyu Tian. "Optimal Operation Modes of Virtual Power Plants Based on Typical Scenarios Considering Output Evaluation Criteria." Energies 11, no. 10 (2018): 2634. http://dx.doi.org/10.3390/en11102634.
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Stimulated by the severe energy crisis and the increasing awareness about the need for environmental protection, the efficient use of renewable energy has become a hot topic. The virtual power plant (VPP) is an effective way of integrating distributed energy systems (DES) by effectively deploying them in power grid dispatching or electricity trading. In this paper, the operating mode of the VPP with penetration of wind power, solar power and energy storage is investigated. Firstly, the grid-connection requirements of VPP according to the current wind and solar photovoltaic (PV) grid-connection requirements, and analyzed its profitability are examined. Secondly, under several typical scenarios grouped by a self-organization map (SOM) clustering algorithm using the VPP’s output data, a profit optimization model is established as a guideline for the VPP’s optimal operation. Based on this model, case studies are performed and the results indicate that this model is both feasible and effective.
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Meng, Shao Xin, Hao Bai, and Yu Li Wang. "Optimal Energy Management for Smart Distribution Grid Based on Virtual Power Plant." Advanced Materials Research 986-987 (July 2014): 388–93. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.388.
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Virtual Power Plant (VPP) technology can take advantage of interactive communication and energy management system to optimize and coordinate the control of distributed generation, controllable load, energy storage device, so as to integrate them and participate in the energy exchange of the grid and the quote trading of power market. This paper is devoted to study the energy management system in virtual power plant. Under the day-ahead market ,this project puts forward the maximum profit model, analyzes the operation condition of various elements in virtual power plant, and set restrictions for its operation and energy storage; According to the randomness of the energy resources such as wind and light in actual operation as well as the price in power market, the change of power grid load and electricity demand, and the fluctuations in the retail price of electricity, this paper adopts the proposed model of optimal allocation to coordinate and optimize the configuration of the elements in virtual power plant.
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Ko, Rakkyung, Daeyoung Kang, and Sung-Kwan Joo. "Mixed Integer Quadratic Programming Based Scheduling Methods for Day-Ahead Bidding and Intra-Day Operation of Virtual Power Plant." Energies 12, no. 8 (2019): 1410. http://dx.doi.org/10.3390/en12081410.
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As distributed energy resources (DERs) proliferate power systems, power grids face new challenges stemming from the variability and uncertainty of DERs. To address these problems, virtual power plants (VPPs) are established to aggregate DERs and manage them as single dispatchable and reliable resources. VPPs can participate in the day-ahead (DA) market and therefore require a bidding method that maximizes profits. It is also important to minimize the variability of VPP output during intra-day (ID) operations. This paper presents mixed integer quadratic programming-based scheduling methods for both DA market bidding and ID operation of VPPs, thus serving as a complete scheme for bidding-operation scheduling. Hourly bids are determined based on VPP revenue in the DA market bidding step, and the schedule of DERs is revised in the ID operation to minimize the impact of forecasting errors and maximize the incentives, thus reducing the variability and uncertainty of VPP output. The simulation results verify the effectiveness of the proposed methods through a comparison of daily revenue.
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Li, Xiangyu, Dongmei Zhao, and Baicang Guo. "Decentralized and Collaborative Scheduling Approach for Active Distribution Network with Multiple Virtual Power Plants." Energies 11, no. 11 (2018): 3208. http://dx.doi.org/10.3390/en11113208.
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In order to build an active distribution system with multi virtual power plants (VPP), a decentralized two-stage stochastic dispatching model based on synchronous alternating direction multiplier method (SADMM) was proposed in this paper. Through the integration of distributed energy and large-scale electric vehicles (EV) in the distribution network by VPP group, coordinative complementarity, and global optimization were realized. On the premise of energy autonomy management of active distribution network (AND) and VPP, after ensuring the privacy of stakeholders, the power of tie-line was taken as decoupling variable based on SADMM. Furthermore, without the participation of central coordinators, the optimization models of VPPs and distribution networks were decoupled to achieve fully decentralized optimization. Aiming at minimizing their own operating costs, the VPPs aggregate distributed energy and large-scale EVs within their jurisdiction to interact with the upper distribution network. On the premise of keeping operation safe, the upper distribution network formulated the energy interaction plan with each VPP, and then, the global energy optimization management of the entire distribution system and the decentralized autonomy of each VPP were achieved. In order to improve the stochastic uncertainty of distributed renewable energy output, a two-stage stochastic optimization method including pre-scheduling stage and rescheduling stage was adopted. The pre-scheduling stage was used to arrange charging and discharging plans of EV agents and output plans of micro gas turbines. The rescheduling stage was used to adjust the spare resources of micro gas turbines to deal with the uncertainty of distributed wind and light. An example of active distribution system with multi-VPPs was constructed by using the improved IEEE 33-bus system, then the validity of the model was verified.
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Zhang, Jiahui, Zhiyu Xu, Weisheng Xu, Feiyu Zhu, Xiaoyu Lyu, and Min Fu. "Bi-Objective Dispatch of Multi-Energy Virtual Power Plant: Deep-Learning-Based Prediction and Particle Swarm Optimization." Applied Sciences 9, no. 2 (2019): 292. http://dx.doi.org/10.3390/app9020292.
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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 in terms of 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 the Institute of Electrical and Electronic Engineers (IEEE) 118-bus benchmark system. It is revealed that “foresighted” strategy, which incorporates LSTM prediction and bi-objective optimization over a 5-h receding horizon, takes 10 Pareto dominances in 24 h.
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Ullah, Zahid, and Nayyar Hussain Mirjat. "Virtual power plant: state of the art providing energy flexibility to local distribution grids." E3S Web of Conferences 231 (2021): 01002. http://dx.doi.org/10.1051/e3sconf/202123101002.
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Integrating decentralised energy sources into the traditional distribution networks can result in technical issues impacting the power quality. Innovative ideas are, therefore, needed to promote the transformation of systems to a smart grid. Distribution System operator (DSO) could make use of the flexibility of emerging technologies as a method to address these power quality issues. This study aims to present an overview of a local flexibility market (LFM) which will allow DSO requirements to be fulfilled through the (VPP) as an energy flexibility provider. The required optimization loads, generators and as well as storage units, are undertaken in the general algebraic modeling simulation (GAMS) environment. The aim of the optimization problem is to provide DSOs the opportunity to increase or curtail the local generations and loads in order to satisfy their requirement. The VPP will then be responsible for handling the relevant requests in real time to ensure the correct operating schedule of a resource is applied. The preliminary results of simulation studies presented in this paper have shown that the local market framework for flexibility could have potential for deferring investments in distribution network capacity, minimizing energy costs and improving the hosting capacity of distribution networks.
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Lyu, Xu, Wang, Fu, and Xu. "A Two-Layer Interactive Mechanism for Peer-to-Peer Energy Trading Among Virtual Power Plants." Energies 12, no. 19 (2019): 3628. http://dx.doi.org/10.3390/en12193628.
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This paper addresses decentralized energy trading among virtual power plants (VPPs) and proposes a peer-to-peer (P2P) mechanism, including two interactive layers: on the bottom layer, each VPP schedules/reschedules its internal distributed energy resources (DERs); and on the top layer, VPPs negotiate with each other on the trade price and quantity. The bottom-layer scheduling provides initial conditions for the top-layer negotiation, and the feedback of top-layer negotiation affects the bottom-layer rescheduling. The local scheduling/rescheduling of a VPP is formulated as a stochastic optimization problem, which takes into account the uncertainties of wind and photovoltaic power by using the scenarios-based method. In order to describe the capability of a seller VPP to generate more energy than the scheduled result, the concept of power generation potential is introduced and then considered during order initialization. The multidimensional willingness bidding strategy (MWBS) is modified and applied to the price bidding process of P2P negotiation. A 14-VPP case is studied by performing numerous computational experiments. The optimal scheduling model is effective and flexible to deal with VPPs with various configurations of DERs. The parallel price bidding with MWBS is adaptive to market situations and efficient due to its rapid convergence. It is revealed that VPPs can obtain higher profit by participating in P2P energy trading than from traditional centralized trading, and the proposed mechanism of two-layer “interactivity” can further increase VPPs’ benefits compared to its “forward” counterpart. The impacts of VPP configuration and VPP number are also studied. It is demonstrated that the proposed mechanism is applicable to most cases where VPPs manage some controllable DERs.
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Kalaf, A. A., O. Sh Alyozbaky, and A. I. Alghannam. "A modern technique to manage energy profile in Iraq: virtual power plant (VPP)." Journal of Physics: Conference Series 1973, no. 1 (2021): 012078. http://dx.doi.org/10.1088/1742-6596/1973/1/012078.
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Nguyen, Duc Huu. "An approach to balance state of charges of distributed batteries in virtual power plants." Vietnam Journal of Science and Technology 56, no. 1 (2018): 81. http://dx.doi.org/10.15625/2525-2518/56/1/8715.
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Small distributed energy sources could be aggregated to form a virtual power plant (VPP) in order to overall improve technical and market issues. VPPs should be composed of several distributed batteries (DB) to solve the problem of intermittency due to wind and solar. This paper presents an approach to balance state of charge batteries. It is therefore to improve the lifetime of batteries in VPPs. According to the proposed method, the real-time SOC of DB will be tracking on the balancing SOC determined in VPP. During operation, the difference of SOC among DBs will be shrunk and finally the share of exchange power among DB is equal. Moreover, the duration time to achieve the balancing SOC can be determined by adjusting the exponent parameter of SOC in the presented function.
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Pudjianto, D., C. Ramsay, and G. Strbac. "Microgrids and virtual power plants: Concepts to support the integration of distributed energy resources." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 222, no. 7 (2008): 731–41. http://dx.doi.org/10.1243/09576509jpe556.
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This article presents the concepts of the microgrid and the virtual power plant (VPP) as vehicles to facilitate cost-efficient integration of distributed energy resources (DERs) into the existing power system. These concepts were designed to enhance the system value and the controllability of DER and to provide frameworks for the development of interfaces among energy and ancillary service resources, system operators, and energy market participants. Through aggregation, DER access to energy markets is facilitated, and DER-based system support and ancillary services can be provided. By enabling this additional functionality, it is envisaged that system performance measured in the form of energy efficiency, power quality, security, and economic operation can be improved. In this paper, the technical and commercial functionality facilitated through the microgrid and VPP concepts is described. The paper concludes with case studies demonstrating the application of the concepts on a test system.
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Zhong, Weilin, Junru Chen, Muyang Liu, Mohammed Ahsan Adib Murad, and Federico Milano. "Coordinated Control of Virtual Power Plants to Improve Power System Short-Term Dynamics." Energies 14, no. 4 (2021): 1182. http://dx.doi.org/10.3390/en14041182.
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The paper proposes a coordinated frequency control strategy for Virtual Power Plant (VPPs), with the inclusion of Distributed Energy Resource (DERs), e.g., Solar Photo-Voltaic Generation (SPVG), Wind Generator (WG) as well as Energy Storage System (ESS). The objective is to improve the short-term dynamic response of the overall power system. The robustness of the proposed control is evaluated through a Monte Carlo analysis and a detailed modeling of stochastic disturbances of loads, wind speed, and solar irradiance. The impact of communication delays of a variety of realistic communication networks with different bandwidths is also discussed and evaluated. The case study is based on a modified version of the WSCC 9-bus test system with inclusion of a VPP. This is modeled as a distribution network with inclusion of a variety of DERs.
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Behi, Behnaz, Ali Arefi, Philip Jennings, Arian Gorjy, and Almantas Pivrikas. "Advanced Monitoring and Control System for Virtual Power Plants for Enabling Customer Engagement and Market Participation." Energies 14, no. 4 (2021): 1113. http://dx.doi.org/10.3390/en14041113.
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To integrate large-scale renewable energy into energy systems, an effective participation from private investors and active customer engagement are essential. Virtual power plants (VPPs) are a very promising approach. To realize this engagement, an efficient monitoring and control system needs to be implemented for the VPP to be flexible, scalable, secure, and cost-effective. In this paper, a realistic VPP in Western Australia is studied, comprising 67 dwellings, including a 810 kW rooftop solar photovoltaic (PV) system, a 700 kWh vanadium redox flow battery (VRFB), a heat pump hot water system (HWS), an electric vehicle (EV) charging station, and demand management mechanisms. The practical and detailed concept design of the monitoring and control system for EEBUS-enabled appliances, and also for the PV and VRFB system, with smart inverters, is proposed. In addition, a practical fog-based storage and computing system is developed to enable the VPP owner to manage the PV, VRFB, and EV charging station for maximizing the benefit to the customers and the VPP owner. Further, the proposed cloud-based applications enable customers to participate in gamified demand response programs for increasing the level of their engagement while satisfying their comfort level. All proposed systems and architecture in this paper have the capability of being implemented fully and relevant references for practical devices are given where necessary.
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Naval, Natalia, and Jose M. Yusta. "Water-Energy Management for Demand Charges and Energy Cost Optimization of a Pumping Stations System under a Renewable Virtual Power Plant Model." Energies 13, no. 11 (2020): 2900. http://dx.doi.org/10.3390/en13112900.
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The effects of climate change seriously affect agriculture at different latitudes of the planet because periods of drought are intensifying and the availability of water for agricultural irrigation is reducing. In addition, the energy cost associated with pumping water has increased notably in recent years due to, among other reasons, the maximum demand charges that are applied annually according to the contracted demand in each facility. Therefore, very efficient management of both water resources and energy resources is required. This article proposes the integration of water-energy management in a virtual power plant (VPP) model for the optimization of energy costs and maximum demand charges. For the development of the model, a problem related to the optimal operation of electricity generation and demand resources arises, which is formulated as a nonlinear mixed-integer programming model (MINLP). The objective is to maximize the annual operating profit of the VPP. It is worth mentioning that the model is applied to a large irrigation system using real data on consumption and power generation, exclusively renewable. In addition, different scenarios are analyzed to evaluate the variability of the operating profit of the VPP with and without intraday demand management as well as the influence of the wholesale electricity market price on the model. In view of the results obtained, the model that integrates the management of the water-energy binomial increases the self-consumption of renewable energy and saves electricity supply costs.
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Ju, Liwei, Peng Li, Qinliang Tan, Zhongfu Tan, and GejiriFu De. "A CVaR-Robust Risk Aversion Scheduling Model for Virtual Power Plants Connected with Wind-Photovoltaic-Hydropower-Energy Storage Systems, Conventional Gas Turbines and Incentive-Based Demand Responses." Energies 11, no. 11 (2018): 2903. http://dx.doi.org/10.3390/en11112903.
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To make full use of distributed energy resources to meet load demand, this study aggregated wind power plants (WPPs), photovoltaic power generation (PV), small hydropower stations (SHSs), energy storage systems (ESSs), conventional gas turbines (CGTs) and incentive-based demand responses (IBDRs) into a virtual power plant (VPP) with price-based demand response (PBDR). Firstly, a basic scheduling model for the VPP was proposed in this study with the objective of the maximum operation revenue. Secondly, a risk aversion model for the VPP was constructed based on the conditional value at risk (CVaR) method and robust optimization theory considering the operating risk from WPP and PV. Thirdly, a solution methodology was constructed and three cases were considered for comparative analyses. Finally, an independent micro-grid on an industrial park in East China was utilized for an example analysis. The results show the following: (1) the proposed risk aversion scheduling model could cope with the uncertainty risk via a reasonable confidence degree β and robust coefficient Γ. When Γ ≤ 0.85 or Γ ≥ 0.95, a small uncertainty brought great risk, indicating that the risk attitude of the decision maker will affect the scheduling scheme of the VPP, and the decision maker belongs to the risk extreme aversion type. When Γ ∈ (0.85, 0.95), the decision-making scheme was in a stable state, the growth of β lead to the increase of CVaR, but the magnitude was not large. When the prediction error e was higher, the value of CVaR increased more when Γ increased by the same magnitude, which indicates that a lower prediction accuracy will amplify the uncertainty risk. (2) when the capacity ratio of (WPP, PV): ESS was higher than 1.5:1 and the peak-to-valley price gap was higher than 3:1, the values of revenue, VaR, and CVaR changed slower, indicating that both ESS and PBDR can improve the operating revenue, but the capacity scale of ESS and the peak-valley price gap need to be set properly, considering both economic benefits and operating risks. Therefore, the proposed risk aversion model could maximize the utilization of clean energy to obtain higher economic benefits while rationally controlling risks and provide reliable decision support for developing optimal operation plans for the VPP.
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Zhang, Ming, Mingxing Guo, Bingqing Bai, et al. "Research on the designation of business model and bi-level optimization scheduling strategy of a VPP in energy market." E3S Web of Conferences 256 (2021): 02010. http://dx.doi.org/10.1051/e3sconf/202125602010.
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With the rapid development of distributed energy resource, a more powerful market operation and energy management system is in great demand for a more precise scheduling strategy. And owing to the advantages in communication and control, virtual power plant (VPP) can provide solutions to these problems. In this paper, the business orientation and service plan are discussed first. Then the mathematical model of the settled market is established to figure out the scheduling strategy of participating in energy market. And a bi-level optimization model is built, with the upper level of maximizing the profits of VPP and lower level of clearing process of energy market. Finally, the scheduling scheme under typical scenarios is discussed in the example, and the ability of the VPP to adapt to the price change is analyzed. It can be seen that the VPP can adjust its own load and processing in the face of price fluctuation to achieve the maximum benefit.
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Raab, Andreas, Enrico Lauth, Kai Strunz, and Dietmar Göhlich. "Implementation Schemes for Electric Bus Fleets at Depots with Optimized Energy Procurements in Virtual Power Plant Operations." World Electric Vehicle Journal 10, no. 1 (2019): 5. http://dx.doi.org/10.3390/wevj10010005.
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For the purpose of utilizing electric bus fleets in metropolitan areas and with regard to providing active energy management at depots, a profound understanding of the transactions between the market entities involved in the charging process is given. The paper examines sophisticated charging strategies with energy procurements in joint market operation. Here, operation procedures and characteristics of a depot including the physical layout and utilization of appropriate charging infrastructure are investigated. A comprehensive model framework for a virtual power plant (VPP) is formulated and developed to integrate electric bus fleets in the power plant portfolio, enabling the provision of power system services. The proposed methodology is verified in numerical analysis by providing optimized dispatch schedules in day-ahead and intraday market operations.
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Nadeem, Furquan, Mohd Asim Aftab, S. M. Suhail Hussain, et al. "Virtual Power Plant Management in Smart Grids with XMPP Based IEC 61850 Communication." Energies 12, no. 12 (2019): 2398. http://dx.doi.org/10.3390/en12122398.
Full textAbstract:
Communication plays a key role in the effective management of virtual power plants (VPPs). For effective and stable operation of VPPs, a reliable, secure, and standardized communication infrastructure is required. In the literature, efforts were made to develop this based on industry standards, such as the IEC 60870-5-104, OpenADR 2.0b and IEC 61850. Due to its global acceptance and strong object-oriented information models, IEC 61850 standard-based communication is preferred for smart grid operations, including VPPs. However, communication models based on IEC 61850 present cybersecurity and scalability challenges. To address this issue, this paper presents an eXtensible Message Presence Protocol (XMPP)-based IEC 61850 communication for VPPs. Firstly, a full mapping of IEC 61850 messages for VPP energy management is carried out. Secondly, XMPP-based single- and multiple-domain communications are demonstrated. Finally, a federation concept has been added to facilitate communication in multi-domain communication networks. These models show that a standard communication model can be implemented with IEC 61850 and XMPP, not only for VPPs but other wide-area communication implementations in smart grids. This not only facilitates plug-and-play (PnP) with easy component additions but secures smart grid communication against cyber-attacks.