Relevant bibliographies by topics / Microgrid optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Microgrid optimization'

Author: Grafiati
Published: 20 February 2023

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Journal articles on the topic "Microgrid optimization"

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Lei, Bingyin, Yue Ren, Huiyu Luan, Ruonan Dong, Xiuyuan Wang, Junli Liao, Shu Fang, and Kaiye Gao. "A Review of Optimization for System Reliability of Microgrid." Mathematics 11, no. 4 (February 6, 2023): 822. http://dx.doi.org/10.3390/math11040822.

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Clean and renewable energy is the only way to achieve sustainable energy development, with considerable social and economic benefits. As a key technology for clean and renewable energy, it is very important to research the reliability optimization of microgrids. This paper reviews the research progress in microgrid reliability optimization. This paper first classifies and summarizes the existing research on microgrid control strategies and reliability assessment. Then, the system reliability optimization framework is summarized in terms of both microgrid systems and optimization objectives. Next, we summarize the most commonly used optimization algorithms for microgrid reliability for different microgrid systems. Finally, we provide a bibliometric analysis of the literature on the reliability research of microgrids. In addition, we propose some research challenges in the future for the reliability of microgrids.
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Twaisan, Kumail, and Necaattin Barışçı. "Integrated Distributed Energy Resources (DER) and Microgrids: Modeling and Optimization of DERs." Electronics 11, no. 18 (September 6, 2022): 2816. http://dx.doi.org/10.3390/electronics11182816.

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In the near future, the notion of integrating distributed energy resources (DERs) to build a microgrid will be extremely important. The DERs comprise several technologies, such as diesel engines, micro turbines, fuel cells, photovoltaic, small wind turbines, etc. The coordinated operation and control of DER together with controllable loads and storage devices, such as flywheels, energy capacitors and batteries, are central to the concept of microgrid. Microgrids can operate interconnected to the main distribution grid, or in an islanded mode. This paper reviews the studies on microgrid technologies. The modeling and optimization methodologies of DERs are also presented and discussed in this paper along with system control approaches for DERs and microgrids. The review findings indicate that the use of multimodal indicators that take into consideration the financial, technological, ecological, and social elements of microgrids increased the community’s and stakeholders’ reaction capability. The microgrid structure under consideration comprises several types of combined heat power devices, boilers, and various types of DERs, including FC units, distributed generators, and MTs. Moreover, compared to grid-connected mode, the microgrid’s total operation cost is significantly higher in isolated mode.
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Azeem, Omar, Mujtaba Ali, Ghulam Abbas, Muhammad Uzair, Ayman Qahmash, Abdulmohsen Algarni, and Mohammad Rashid Hussain. "A Comprehensive Review on Integration Challenges, Optimization Techniques and Control Strategies of Hybrid AC/DC Microgrid." Applied Sciences 11, no. 14 (July 6, 2021): 6242. http://dx.doi.org/10.3390/app11146242.

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The depletion of natural resources and the intermittence of renewable energy resources have pressed the need for a hybrid microgrid, combining the benefits of both AC and DC microgrids, minimizing the overall deficiency shortcomings and increasing the reliability of the system. The hybrid microgrid also supports the decentralized grid control structure, aligning with the current scattered and concentrated load scenarios. Hence, there is an increasing need to explore and reveal the integration, optimization, and control strategies regarding the hybrid microgrid. A comprehensive study of hybrid microgrid’s performance parameters, efficiency, reliability, security, design flexibility, and cost-effectiveness is required. This paper discusses major issues regarding the hybrid microgrids, the integration of AC and DC microgrids, their security and reliability, the optimization of power generation and load management in different scenarios, the efficient management regarding uncertainty for renewable energy resources, the optimal placement of feeders, and the cost-effective control methodologies for the hybrid microgrid. The major research areas are briefly explained, aiming to find the research gap that can further improve the performance of the grid. In light of the recent trends in research, novel strategies are proposed that are found most effective and cost-friendly regarding the hybrid microgrid. This paper will serve as a baseline for future research, comparative analysis, and further development of novel techniques regarding hybrid microgrids.
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Gao, Kaiye, Tianshi Wang, Chenjing Han, Jinhao Xie, Ye Ma, and Rui Peng. "A Review of Optimization of Microgrid Operation." Energies 14, no. 10 (May 14, 2021): 2842. http://dx.doi.org/10.3390/en14102842.

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Clean and renewable energy is developing to realize the sustainable utilization of energy and the harmonious development of the economy and society. Microgrids are a key technique for applying clean and renewable energy. The operation optimization of microgrids has become an important research field. This paper reviews the developments in the operation optimization of microgrids. We first summarize the system structure and provide a typical system structure, which includes an energy generation system, an energy distribution system, an energy storage system and energy end users. Then, we summarize the optimization framework for microgrid operation, which contains the optimization objective, decision variables and constraints. Next, we systematically review the optimization algorithms for microgrid operations, of which genetic algorithms and simulated annealing algorithms are the most commonly used. Lastly, a literature bibliometric analysis is provided; the results show that the operation optimization of microgrids has received increasing attention in recent years, and developing countries have shown more interest in this field than developed countries have. Finally, we highlight future research challenges for the optimization of the operation of microgrids.
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Liu, Jicheng, Fangqiu Xu, Shuaishuai Lin, Hua Cai, and Suli Yan. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization." Energies 11, no. 12 (November 25, 2018): 3286. http://dx.doi.org/10.3390/en11123286.

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The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.
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Rokicki, Łukasz. "Optimization of the Configuration and Operating States of Hybrid AC/DC Low Voltage Microgrid Using a Clonal Selection Algorithm with a Modified Hypermutation Operator." Energies 14, no. 19 (October 5, 2021): 6351. http://dx.doi.org/10.3390/en14196351.

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The issue of optimization of the configuration and operating states in low voltage microgrids is important both from the point of view of the proper operation of the microgrid and its impact on the medium voltage distribution network to which such microgrid is connected. Suboptimal microgrid configuration may cause problems in networks managed by distribution system operators, as well as for electricity consumers and owners of microsources and energy storage systems connected to the microgrid. Structures particularly sensitive to incorrect determination of the operating states of individual devices are hybrid microgrids that combine an alternating current and direct current networks with the use of a bidirectional power electronic converter. An analysis of available literature shows that evolutionary and swarm optimization algorithms are the most frequently chosen for the optimization of power systems. The research presented in this article concerns the assessment of the possibilities of using artificial immune systems, operating on the basis of the CLONALG algorithm, as tools enabling the effective optimization of low voltage hybrid microgrids. In his research, the author developed a model of a hybrid low voltage microgrid, formulated three optimization tasks, and implemented an algorithm for solving the formulated tasks based on an artificial immune system using the CLONALG algorithm. The conducted research consisted of performing a 24 h simulation of microgrid operation for each of the formulated optimization tasks (divided into 10 min independent optimization periods). A novelty in the conducted research was the modification of the hypermutation operator, which is the key mechanism for the functioning of the CLONALG algorithm. In order to verify the changes introduced in the CLONALG algorithm and to assess the effectiveness of the artificial immune system in solving optimization tasks, optimization was also carried out with the use of an evolutionary algorithm, commonly used in solving such tasks. Based on the analysis of the obtained results of optimization calculations, it can be concluded that the artificial immune system proposed in this article, operating on the basis of the CLONALG algorithm with a modified hypermutation operator, in most of the analyzed cases obtained better results than the evolutionary algorithm. In several cases, both algorithms obtained identical results, which also proves that the CLONALG algorithm can be considered as an effective tool for optimizing modern power structures, such as low voltage microgrids, including hybrid AC/DC microgrids.
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Silva, Vanderlei Aparecido, Alexandre Rasi Aoki, and Germano Lambert-Torres. "Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System." Energies 13, no. 19 (October 5, 2020): 5188. http://dx.doi.org/10.3390/en13195188.

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Optimal scheduling is a requirement for microgrids to participate in current and future energy markets. Although the number of research articles on this subject is on the rise, there is a shortage of papers containing detailed mathematical modeling of the distributed energy resources available in a microgrid. To address this gap, this paper presents in detail how to mathematically model resources such as battery energy storage systems, solar generation systems, directly controllable loads, load shedding, scheduled intentional islanding, and generation curtailment in the microgrid optimal scheduling problem. The proposed modeling also includes a methodology to determine the availability cost of battery and solar systems assets. Simulations were carried out considering energy prices from an actual time-of-use tariff, costs based on real market data, and scenarios with scheduled islanding. Simulation results provide support to validate the proposed model. Data illustrate how energy arbitrage can reduce microgrid costs in a time-of-use tariff. Results also show how the microgrid’s self-sufficiency and the storage system’s capacity can impact the microgrid’s energy bill. The findings also bring out the need to consider the scheduled islanding event in the day-ahead optimization for microgrids.
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Shezan, Sk A., Kazi Nazmul Hasan, Akhlaqur Rahman, Manoj Datta, and Ujjwal Datta. "Selection of Appropriate Dispatch Strategies for Effective Planning and Operation of a Microgrid." Energies 14, no. 21 (November 2, 2021): 7217. http://dx.doi.org/10.3390/en14217217.

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The power system responsiveness may be improved by determining the ideal size of each component and performing a reliability analysis. This study evaluated the design and optimization of an islanded hybrid microgrid system with multiple dispatch algorithms. As the penetration of renewable power increases in microgrids, the importance and influence of efficient design and operation of islanded hybrid microgrids grow. The Kangaroo Island in South Australia served as the study’s test microgrid. The sizing of the Kangaroo Island hybrid microgrid system, which includes solar PV, wind, a diesel engine, and battery storage, was adjusted for four dispatch schemes. In this study, the following dispatch strategies were used: (i) load following, (ii) cycle charging, (iii) generator order, and (iv) combination dispatch. The CO2 emissions, net present cost (NPC), and energy cost of the islanded microgrid were all optimized (COE). The HOMER microgrid software platform was used to build all four dispatch algorithms, and DIgSILENT PowerFactory was used to analyze the power system’s responsiveness and dependability. The findings give a framework for estimating the generation mix and required resources for an islanded microgrid’s optimal functioning under various dispatch scenarios. According to the simulation results, load following is the optimum dispatch technique for an islanded hybrid microgrid that achieves the lowest cost of energy (COE) and net present cost (NPC).
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langchao, He, Wu Lizhen, Chen Wei, and Hao Xiaohong. "Research on Bi-level Coordinated Optimal Dispatching Strategy for Microgrid Cluster." E3S Web of Conferences 256 (2021): 01045. http://dx.doi.org/10.1051/e3sconf/202125601045.

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The interconnection of multiple microgrids can form a microgrid cluster (MGC). The economic benefit and operation reliability of the whole system can be improved through the energy mutual-aid and coordination control between microgrids. This paper proposes a bi-level coordinated optimal dispatching strategy for microgrid clusters. The upper layer aims to minimize the operating costs of the microgrid cluster system and the power fluctuation of the tie lines. The exchange power and generation power of each sub-microgrid are coordinated and controlled, which are sent to the lower level model as scheduling instructions. The lower layer takes a single microgrid as the research object. By optimizing the output of power generation unit, the operation cost of single microgrid can be minimized. Iterative solution is adopted between the bi-level optimization models. In order to avoid the premature and local convergence of the algorithm in the optimization process, the improved artificial bee colony algorithm (ABC) is used to solve the objective function. Finally, simulation examples verify the effectiveness and feasibility of the proposed strategy.
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Wu, Xiaomin, Weihua Cao, Dianhong Wang, and Min Ding. "A Multi-Objective Optimization Dispatch Method for Microgrid Energy Management Considering the Power Loss of Converters." Energies 12, no. 11 (June 5, 2019): 2160. http://dx.doi.org/10.3390/en12112160.

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With the spreading and applying of microgrids, the economic and environment friendly microgrid operations are required eagerly. For the dispatch of practical microgrids, power loss from energy conversion devices should be considered to improve the efficiency. This paper presents a two-stage dispatch (TSD) model based on the day-ahead scheduling and the real-time scheduling to optimize dispatch of microgrids. The power loss cost of conversion devices is considered as one of the optimization objectives in order to reduce the total cost of microgrid operations and improve the utility efficiency of renewable energy. A hybrid particle swarm optimization and opposition-based learning gravitational search algorithm (PSO-OGSA) is proposed to solve the optimization problem considering various constraints. Some improvements of PSO-OGSA, such as the distribution optimization of initial populations, the improved inertial mass update rule, and the acceleration mechanism combining the memory and community of PSO, have been integrated into the proposed approach to obtain the best solution for the optimization dispatch problem. The simulation results for several benchmark test functions and an actual test microgrid are employed to show the effectiveness and validity of the proposed model and algorithm.
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Dissertations / Theses on the topic "Microgrid optimization"

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Kusnetsova, Elizaveta. "Microgrid agent-based modelling and optimization under uncertainty." Versailles-St Quentin en Yvelines, 2014. http://www.theses.fr/2014VERS005S.

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Le travail de recherche est axé sur la gestion de l'énergie dans les micro réseaux électriques. La contribution scientifique est ici basée sur: (i) des approches de modélisation d'intelligence individuelle pour la gestion d'énergie sous incertitudes et (ii) la gestion de l'énergie dans un micro réseau intégrant différents acteurs avec des objectifs conflictuels. Les acteurs de micro réseaux, opérant sous un accès limité aux informations et en présence d'incertitudes opérationnelles et environnementales, sont modélisés par une approche orientée agent (Agent-Based Modelling). Les approches considérées pour la modélisation de l'intelligence individuelle dans cette thèse, i. E. L'apprentissage par renforcement (Reinforcement Learning) et l'optimisation robuste (Robust Optimization), attribuent à chaque agent des capacités de prise de décision,d'adaptation à leur environnement stochastique et d'interactions avec d'autres agents. Les méthodes de modélisation développées ont été testées sur des micro réseaux urbains impliquant différents consommateurs d'énergie, des sources d'énergie renouvelable et des moyens de stockage, afin d'optimiser la gestion de l'énergie en termes de fiabilité et des aspects économiques, sous incertitudes opérationnelle, environnementale et de défaillances des composants
This thesis concerns the energy management of electricity microgrids. The scientific contribution follows two directions: (i) modelling individual intelligence in energy management under uncertainty and (ii) microgrid energy management integrating diverse actors with conflicting objectives. Agent-Based Modelling (ABM) is used to describe the dynamics of microgrid actors operating under limited access to information, and operational and environmental uncertainties. The approaches considered to model individual intelligence in this thesis, Reinforcement Learning and Robust Optimization, provide each agent with the capability of making decision, adapting to the stochastic environment and interacting with other agents. The modelling frameworks developed have been tested on urban microgrids integrating different energy consumers, sources of renewable energy and storage facilities, for optimal energy management in terms of reliability and economic indicators under operational and environmental uncertainty, and components failures
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Rasouli, Disfani Vahid. "Optimization and Control for Microgrid and Power Electronic Converters." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5764.

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The proposed dissertation research investigates Optimization and Control for Microgrid and Power Electronic Converters. The research has two major parts: i- Microgrid Operation and Control, ii- Power Electronic Converter Control and Optimization. In the first part, three focuses are investigated. First, a completely distributed algorithm is developed for dc optimal power flow problem for power distribution systems as one of the necessary functions considered in unit-commitment problem in day-ahead markets. This method is derived based upon the partial primal-dual representation of the economic dispatch problem, which is finally translated to DC-OPF problem. Second, the optimal interaction between the utility and communities will be studied, due to its improtance in real-time markets. The objective of this section will be to develop an iterative agent-based algorithm for optimal utility-community control. The algorithm will consider the AC power system constraints to maintain power system stability. In this algorithm, a simplified model of microgrid is considered. In the third focus, a comprehensive model of microgrid is taken into account. The optimal operation of the microgrid considering energy storage systems and renewable energy resources is investigated. The interaction of such microgrids with the main grid to define the optimal operation of the entire embedded system is studied through two iterative methods. In the microgrid's internal problem, a moving-horizon algorithm is considered to define the optimal dispatch of all distributed energy resources while considering the time-correlated constraints of energy storage systems. A thorough analysis of the effects of the size of storage systems on energy and reserve market parameters are also performed. In the second part, the focus of research is to develop optimal control strategies for Power Electronic Converters. A Model Predictive Control (MPC) switching method is proposed for Modular Multilevel Converters (MMC). The optimal solution of MPC problem is then represented as an optimization problem. Due to lack of efficient algorithms to seek the optimal solution, a fast algorithm will be proposed in this research. The method proposed reduces the number of possible solutions and computation efforts dramatically.
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Ali, Loaqat. "Optimization of energy storages in microgrid for power generation uncertainties." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/48485.

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Microgrid is a cluster of distributed generation units, energy storages, and loads which can operate grid-connected and islanded. This research focuses on selecting an economic standalone supply system for small and remote off-grid towns in Western Australia. Existing power systems of such towns have adverse environmental impacts due to the utilization of diesel and gas. The suitable electricity supply system is a hybrid system composed of generators, renewables, and energy storages.
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Moghimi, Mojtaba. "Modelling and Optimization of Energy Management Systems in Microgrids and Multi-Microgrids." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/385882.

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With the new challenges brought by the high penetration of Renewable Energy Resources (RESs) into the modern grid, developing new solutions and concepts are necessary. Microgrid (MG) is one of the new concepts introduced to overcome upcoming issues in the modern electricity grids. MGs and Multi-Microgrids (MMGs) are defined as the building blocks of smart grids. MGs are the small units, where power generation and consumption happen at the same location and MG makes the decisions by itself. MGs can operate grid-connected or island mode depending on the functionality of the MG. Energy Management System (EMS) is the decision making centre of the MG. The data from the devices is received by the EMS and after processing, the commands are sent to the controllable components. Management of voltage, active and reactive power, neutral current, unit commitment and economic dispatch are of the tasks of EMS. In this PhD thesis, an optimal EMS for MGs and MMGs is developed. The main objective of this project by developing the EMS is to optimize the energy flow in the MGs and MMGs to obtain peak load shaving in a cost beneficial system. In order to achieve an efficient EMS, communication system, forecasting system, scheduling system, and optimization system are modelled and developed. Different types of EMS operation, centralized, decentralized and distributed, are investigated in this work to achieve the best combination for MMG EMS operation. The communication system is mainly utilizing Modbus TCP/IP protocol for data transmission at local level and Internet of Things (IoT) protocols (MQTT) for the global communication level. A communication operation algorithm is proposed to manage the MMG EMS under different communication operation modes and communication failure conditions. Furthermore, a monitoring system is developed to collect the data from different devices in the MG. The data is processed in the MG EMS and the commands are sent to components through the communication infrastructure. The link between MGs and MMGs is through the proposed two-level communication system, where the expansion of MGs to a MMG is investigated. In the MMG, MGs are functioning as a unit while having different priorities and operating under different policies. Each MG has its own MG EMS and the EMSs transfer information through the communication system between each other in either centralized, decentralized, distributed, or no communication modes under the MMG EMS. The forecasting system is required in the EMS to predict the future MG characteristics such as power generation and consumption. The forecasted data is the input to the optimization and scheduling system of EMS. Employing the forecasting system in the EMS would increase the accuracy of the optimization and scheduling systems. In this thesis, the timeseries-based forecasting algorithms are employed to predict next day’s active power using the load data, generation data, weather data and temperature data as the inputs. The heart of EMS is the scheduling and optimization system. The purpose of the scheduling system is to define the amount and the time of energy flow in the MG for different generation sources and consumption loads. Furthermore, scheduling system is responsible for peak load shaving and valley filling. On the other hand, the optimization system has the task of minimizing the operation costs of the MGs. The role of market in the scheduling and optimization is important. Time of Use (ToU) tariff is the pricing system, which determines the peak and off peak hours for energy usage pricing. In order to apply the optimization system, a model of the system, an objective function and systems constraints are defined, where aging of battery energy storage system (BESS), operational cost of components and MG cost benefits are considered. To operate the EMS scheduling and optimization system, IBM CPLEX Optimization Studio solver conducts the optimization while for the scheduling system, objective function and constraints are defined in MATLAB. In this thesis, a rule-based, MILP and MIQP optimization system for commercial MGs including electric vehicles (EVs) are proposed to investigate performance of MG EMS for different case studies. In this thesis, the literature for different scheduling and forecasting systems is investigated and different optimization algorithms are analysed. The communication protocols utilized in this research are described and compared to other protocols in the literature. In different chapters of this thesis, the modelling of MGs and MMG EMS, different modules of EMS, forecasting, optimization, scheduling and communication systems are described and analysed. A novel communication system for MMG EMS operation is proposed for commercial buildings. The performance of MG EMS and MMG EMS is examined for power and neutral current sharing, operation cost optimization, and demand peak shaving applications and results are compared to investigate the performance of proposed algorithms.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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Paniagua, Sánchez-Mateos Jesús. "Reliability-Constrained Microgrid Design." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187715.

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Microgrids are new challenging power systems under development. This report presents a feasibility study of microgrid development. This is an essential task before implementing microgrid systems. It is extremely important to know the number and size of distributed energy resources (DERs) needed and it is necessary to compare investment costs with benefits in order to evaluate the profitability of microgrids. Under the assumption that a large number of DERs improves the reliability of microgrids an optimization problem is formulated to get the accurate mix of distributed energy resources. Uncertainty in physical and financial parameters is taken into account to model the problem considering different scenarios.  Uncertainty takes place in load demanded, renewable energy generation and electricity market price forecasts, availability of distributed energy resources and the microgrid islanding. It is modeled in a stochastic way. The optimization problem is formulated firstly as a mixed-integer programming solved via branch and bound and then it is improved formulating a two stage problem using Benders’ Decomposition which shortens the problem resolution. This optimization problem is divided in a long-term investment master problem and a short-term operation subproblem and it is solved iteratively until it reaches convergence. Bender’s Decomposition optimization problem is applied to real data from the Illinois Institute of Technology (IIT) and it gives the ideal mix of distributed energy resources for different uncertainty scenarios. These distributed energy resources are selected from an initial set. It proves the usefulness of this optimization technique which can be also applied to different microgrids and data. The different solutions obtained for different scenarios are explained and analyzed. They show the possibility of microgrid implementation and determine the most favorable scenarios to reach the microgrid implementation successfully.  Reliability is a term highly linked to the microgrid concept and one of the most important reasons of microgrid development. Thus an analysis of reliability importance is implemented using the importance index of interruption cost (  ) in order to measure the reliability improvement of developing microgrids. It shows and quantifies the reliability improvement in the system.
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Milani, Neil Patrick. "PERFORMANCE OPTIMIZATION OF A HYBRID WIND TURBINE-DIESEL MICROGRID POWER SYSTEM." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-11062006-173005/.

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Nearly all off-grid, remote cold-weather facilities utilize diesel-only systems for both thermal and electrical power generation. In areas of minimal to moderate wind resources, these facilities could substantially decrease diesel fuel usage and could additionally provide for thermal energy production via the integration of a wind turbine system combined with resistance heating into the facility. Voltage and frequency grid stabilization could be obtained by using the diesel electrical generating unit as a synchronous condenser and by using incremental resistive load control, respectively. For systems following medium to high wind penetration guidelines, control components are required but no energy storage mechanisms are needed. This thesis investigates a High-Penetration, No Storage Wind Diesel (HPNSWD) system that can utilize available wind resources to minimize diesel fuel costs for the Scott Base facility ? all without implementing expensive and maintenance-intensive energy storage devices.
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Wang, Baochao. "Intelligent control and power flow optimization of microgrid : energy management strategies." Thesis, Compiègne, 2013. http://www.theses.fr/2013COMP2122/document.

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La production intermittente et aléatoire des énergies renouvelables, sources photovoltaïques et éoliennes, est toujours un problème pour leur intégration massive dans le réseau public. L'une des solutions est de grouper des sources renouvelables, des sources traditionnelles, des dispositifs de stockage et des charges locales, et les traiter comme une seule unité dans le réseau public. Il s'agit du concept "micro-réseau". Un micro-réseau a des potentiels pour mieux répondre aux besoins de l'utilisateur final et du réseau public, et il facilite la mise en œuvre de futur smart grid, soit le réseau intelligent.Basé sur un micro-réseau représentatif en zone urbaine et intégré aux bâtiments, cette thèse propose une supervision multicouche, afin d'effectuer une étude systémique en mettant en exergue un verrou scientifique concernant l'implémentation d'une optimisation dans l'exploitation en temps réel.La supervision traite un ensemble d’opérations telles que : l'équilibré des puissances,l'optimisation des coûts énergétiques, utilisation de métadonnées, et échange d'informations avec le réseau intelligent et avec l'utilisateur final. Cette supervision a été validée par des tests expérimentaux. Malgré les incertitudes concernant les prévisions météorologiques, la faisabilité d'implémentation de l'optimisation dans l'exploitation réelle est vérifiée. La supervision proposée est en mesure de gérer efficacement les flux en assurant l'équilibre des puissances dans tous les cas. Néanmoins, la performance d'optimisation est liée aux précisions de prédiction. Ce problème peut être amélioré dans les travaux futurs par la mise à jour des résultats d'optimisation en temps réel
The intermittent and random production of renewable sources, such as photovoltaic and wind turbine, is always a problem for their large-scale integration in the utility grid. One of the solutions is to group renewable sources, traditional sources, storage and local consumption and treat it as a single unit in the utility grid. This is the concept of microgrid. A microgrid has the potentials of better responding both grid and end-user requirement, it facilitate the implementation of future smart grid. Based on a representative microgrid in urban area and integrated in buildings, this thesis proposes a multi-layer supervision, in order to realise a systemic study while particularly attempting to cover the research gap of implementing optimisation in realtimeoperation. The supervision handles together power balancing, energetic cost optimisation, metadata using, and information exchanges from both end-users and the smart grid. The supervision has been validated by experimental tests. The feasibility of implementing optimisation in real-time operation is validated even with uncertainties. The supervision is able to manage efficiently the power flow while maintaining power balancing in any case. Nevertheless, optimization effect relies on prediction precision. This problem can be improved in future works by updating optimization in real-time
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Pacaud, François. "Decentralized optimization for energy efficiency under stochasticity." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1147/document.

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Les réseaux électriques doivent absorber une production d'énergie renouvelable croissante, de façon décentralisée. Leur gestion optimale amène à des problèmes spécifiques. Nous étudions dans cette thèse la formulation mathématique de tels problèmes en tant que problèmes d'optimisation stochastique multi-pas de temps. Nous analysons plus spécifiquement la décomposition en temps et en espace de tels problèmes. Dans la première partie de ce manuscrit, Décomposition temporelle pour l'optimisation de la gestion de microgrid domestique, nous appliquons les méthodes d'optimisation stochastique à la gestion de microgrid de petite taille. Nous comparons différents algorithmes d'optimisation sur deux exemples: le premier considère une microgrid domestique équipée avec une batterie et une centrale de micro-cogénération; le deuxième considère quant à lui une autre microgrid domestique, cette fois équipée avec une batterie et des panneaux solaires. Dans la seconde partie, Décomposition temporelle et spatiale de problèmes d'optimisation de grande taille, nous étendons les études précédentes à des microgrids de plus grandes tailles, avec différentes unités et stockages connectés ensemble. La résolution frontale de tels problèmes de grande taille par Programmation Dynamique s'avère impraticable. Nous proposons deux algorithmes originaux pour pallier ce problème en mélangeant une décomposition temporelle avec une décomposition spatiale --- par les prix ou par les ressources. Dans la dernière partie, Contributions à l'algorithme Stochastic Dual Dynamic Programming, nous nous concentrons sur l'algorithme emph{Stochastic DualDynamic Programming} (SDDP) qui est actuellement une méthode de référence pour résoudre des problèmes d'optimisation stochastique multi-pas de temps. Nous étudions un nouveau critère d'arrêt pour cet algorithme basé sur une version duale de SDDP, qui permet d'obtenir une borne supérieure déterministe pour le problème primal
New energy systems are designed to absorb a large share of renewableenergy in a decentralized fashion. Their optimized management raises specificissues. We study mathematical formulation as large scale multistagestochastic optimization problems. We focus on time and space decompositionmethods in a stochastic setting.In the first part of this manuscript, Time decomposition inoptimization and management of home microgrids, we apply stochasticoptimization algorithms to the management of small scale microgrids. We compare different optimization algorithms on two examples:a domestic microgrid equipped with a microCombined Heat and Power generator and a battery;a domestic microgrid equipped with a battery and solar panels.In the second part, Mixing time and spatial decomposition inlarge-scale optimization problems, we extend the previous studies tolarger microgrids, where different units and storage devices are connected together. As a direct resolution by Dynamic Programming of such large scale systemsis untractable, we propose original algorithms mixing time decomposition on the one hand, and price and resource spatial decomposition on the other hand.In the third part, Contributions to Stochastic Dual Dynamic Programming,we focus on the Stochastic Dual Dynamic Programming (SDDP) algorithm,a well-known algorithm to solve multistage stochastic optimizationproblems. We present a new stopping criteria based on a dual versionof SDDP which gives a deterministic upper-bound for the primal problem
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Omara, Ahmed Mohamed Elsayed. "Predictive Operational Strategies for Smart Microgrid Networks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40101.

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There have been significant advances in communication technologies over the last decade, such as cellular networks, Wi-Fi, and optical communication. Not only does the technology impact peoples’ everyday lives, but it also helps cities prepare for power outages by collecting and exchanging data that facilitates real-time status monitoring of transmission and distribution lines. Smart grids, contrary to the traditional utility grids, allow bi-directional flow of electricity and information, such as grid status and customer requirements, among different parties in the grid. Thus, smart grids reduce the power losses and increase the efficiency of electricity generation and distribution, as they allow for the exchange of information between subsystems. However, smart grids is not resilient under extreme conditions, particularly when the utility grid is unavailable. With the increasing penetration of the renewable energy sources (RES) in smart grids, the uncertainty of the generated power from the distributed generators (DGs) has brought new challenges to smart grids in general and smart microgrids in particular. The rapid change of the weather conditions can directly affect the amount of the generated power from RES such as wind turbine and solar panels, and thus degrading the reliability and resiliency of the smart microgrids. Therefore, new strategies and technologies to improve power reliability,sustainability, and resiliency have emerged. To this end, in this thesis, we propose a novel framework to improve the smart microgrids reliability and resiliency under severe conditions. We study the transition to the grid-connected operational mode in smart microgrids,in the absence of the utility grid, as an example of emergency case that requires fast and accurate response. We perform a comparative study to accurately predict upcoming grid-connected events using machine learning techniques. We show that decision tree models achieve the best average prediction performance. The packets that carry the occurrence time of the next grid-connected transition are considered urgent packets. Hence, we per-form an extensive study of a smart data aggregation approach that considers the priority of the data. The received smart microgrids data is clustered based on the delay-sensitivity into three groups using k-means algorithm. Our delay-aware technique successfully reduces the queuing delay by 93% for the packets of delay-sensitive (urgent) messages and the Packet Loss Rate (PLR) by 7% when compared to the benchmark where no aggregation mechanism exists prior to the small-cell base stations. As a mitigation action of the utility grid unavailability, we use the electrical vehicles (EVs) batteries as mobile storage units to cover smart microgrids power needs until the utility grid recovery. We formulate a Mixed Integer Linear Programming (MILP) model to find the best set of electrical vehicles with the objective of minimum cost. The EVs participating in the emergency power supply process are selected based on the distance and throughput performance between the base station and the EVs
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Trigueiro, dos Santos Leonardo. "Contribution on the day-ahead and operational optimization for DC microgrid building-integrated." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2352/document.

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Cette recherche se concentre sur l'optimisation d'un micro-réseau en interaction avec le réseau électrique intelligent. Il s'agit de la recherche de solutions optimales pour la conception d'un micro-réseau afin de minimiser les coûts, d'une part, et la possibilité augmenter 1'utilisation des sources renouvelables, d'autre part. La supervision, doit traiter la prise en compte des incertitudes dans la gestion prédictive optimisée des flux de puissance
This thesis study focuses on a DC microgrid building-integrated satisfying the power balance at the local level and supplying DC loads during both, grid-connected and isolated operation modes. Considering that energy management can be defined as a group of different control strategies and operational practices that together with the new physical equipment and software solutions aims to accomplish the objectives of energy management, the main objective of this thesis is to define the energy management strategies for the building-integrated DC microgrid, aiming to keep the bus voltage stable as well as to reduce the energy cost to the end users and the negative impact to the main grid. Therefore, this research work focuses to optimize and develop the implementation of the designed controller of building-integrated DC microgrid. The proposed DC microgrid consists of PV building-integrated sources, a storage system, a main grid connection for the grid-connected mode and a micro turbine for the off-grid or isolated mode, and a DC load (electric appliances of a tertiary building). The bidirectional connections with the main grid and the storage aim to supply the building’s DC appliances, and sell or store the energy surplus. The results validate the operation of the whole system, ensuring the capability of the proposed supervisory control to manage the energy power flow while ensuring voltage stability. Other goals concern the analyze of the proposed separation between optimization and real time power balance and the usage of the proposed load shedding/restoration algorithm in the microgrid environment are also validate. Regarding the technical contributions, the work of this thesis allowed the creation and the practical development of a test bench for microgrid based on PV sources emulator, which allows the repeatability conditions (closeness of the agreement between the results of successive measurements of the same solar irradiance and air temperature carried out under the same conditions of measurement) and reproducibility (closeness of the agreement between the results of measurements of the same solar irradiation and air temperature carried out under changed conditions of measurement). Numerous experimental tests were carried out and allowed the validation of the proposed concepts
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Books on the topic "Microgrid optimization"

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Ding, Lei, Qing-Long Han, and Boda Ning. Distributed Control and Optimization of Networked Microgrids. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95029-3.

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Zhou, Yimin. Microgrid Load Optimization Based on Generalized Demand Side Resources. Nova Science Publishers, Incorporated, 2018.

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Sechilariu, Manuela. Urban DC Microgrid: Intelligent Control and Power Flow Optimization. Butterworth-Heinemann Limited, 2016.

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Sechilariu, Manuela, and Fabrice Locment. Urban DC Microgrid: Intelligent Control and Power Flow Optimization. Elsevier Science & Technology Books, 2016.

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Advanced Modeling and Research in Hybrid Microgrid Control and Optimization. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-1885-5.

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Bohre, Aashish Kumar, Sri Niwas Singh, Mohan Lal Kolhe, and Pradyumn Chaturvedi. Planning of Hybrid Renewable Energy Systems, Electric Vehicles and Microgrid: Modeling, Control and Optimization. Springer Singapore Pte. Limited, 2022.

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Zhong, Zhixiong. Modeling, Control, Estimation, and Optimization for Microgrids. CRC Press, 2019. http://dx.doi.org/10.1201/9781351032469.

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Chauhan, Rajeev Kumar, and Kalpana Chauhan. Distributed Energy Resources in Microgrids: Integration, Challenges and Optimization. Elsevier Science & Technology, 2019.

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Chauhan, Rajeev Kumar, and Kalpana Chauhan. Distributed Energy Resources in Microgrids: Integration, Challenges and Optimization. Elsevier Science & Technology Books, 2019.

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Control Estimation and Optimization for Microgrids: A Fuzzy-Model-based Method. Taylor & Francis Group, 2019.

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Book chapters on the topic "Microgrid optimization"

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Lu, Zaixin, Jd Youngs, Zhi Chen, and Miao Pan. "Novel Scheduling for Energy Management in Microgrid." In Combinatorial Optimization and Applications, 32–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71147-8_3.

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Ning, Chun-Yuan, Jun-Jie Shang, Thi-Xuan-Huong Nguyen, and Duc-Tinh Pham. "Microgrid System and Its Optimization Algorithms." In Proceedings of International Conference on Computational Intelligence, 311–19. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3802-2_26.

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Jansen, Ryan, and Rajesh Karki. "Sustainable Energy Optimization in a Smart Microgrid." In Sustainable Power Systems, 111–32. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2230-2_6.

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Sheikh, Shaya, Mohammad Komaki, Camelia Al-Najjar, Abdulaziz Altowijri, and Behnam Malakooti. "A Class of Models for Microgrid Optimization." In Big Data Analytics Using Multiple Criteria Decision-Making Models, 155–74. Boca Raton : Taylor & Francis, CRC Press, 2017. | Series: The operations research series: CRC Press, 2017. http://dx.doi.org/10.1201/9781315152653-7.

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Khandare, P. M., S. A. Deokar, and A. M. Dixit. "Protection of Microgrid with Ideal Optimization Differential Algorithm." In Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019), 712–20. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43192-1_79.

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Khan, Saadullah, Furkan Ahmad, Mohammad Saad Alam, and Mahesh Krishnamurthy. "Design and Optimization of Microgrid as EV Charging Source." In Lecture Notes in Electrical Engineering, 1139–50. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5558-9_97.

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Tang, Yongqi, Xinxin Tang, Jiawei Li, and Mingqiang Wu. "Droop Control of Microgrid Based on Genetic Optimization Algorithm." In Proceedings of the 9th International Conference on Computer Engineering and Networks, 55–65. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3753-0_6.

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Das, Vipin, P. Karuppanan, V. Karthikeyan, S. Rajasekar, and Asheesh Kumar Singh. "Energy Grid Management, Optimization and Economic Analysis of Microgrid." In Smart Energy Grid Design for Island Countries, 289–325. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50197-0_10.

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Chen, Jie, Xiu Yang, Lan Zhu, and Meixia Zhang. "Microgrid Multi-objective Economic Operation Optimization Considering Reactive Power." In Lecture Notes in Electrical Engineering, 507–16. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4981-2_56.

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Raju, More, Haritha Dhanlalji Parmar, Ankur Singh Rana, and Shailendra Kumar. "Application of Ant Lion Optimization Technique for Microgrid Infrastructure." In Studies in Infrastructure and Control, 345–57. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7956-9_12.

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Conference papers on the topic "Microgrid optimization"

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Suk, Hailie, Abhishek Yadav, and John Hall. "Scalability Considerations in the Design of Microgrids to Support Socioeconomic Development in Rural Communities." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88441.

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The interaction between technology and people is characterized by sociotechnical models. In the context of design, these types of systems are analyzed to increase productivity. The level of productivity is expected to increase as the technology evolves. Still, a lack of focus on adaptive design hinders the success of sociotechnical systems. The problem is evident in the relationship between microgrid technology and the residents of developing communities. An analysis of this type of sociotechnical system is analyzed in this paper. Rural villages in the developing world often lack access to the power grid. However, microgrids can provide electrical power in these locations. Power can be harnessed from renewable resources such as wind, solar, geothermal, and hydropower. Large batteries are used to store energy and buffer the electrical supply with the demand. The system powers security lighting, water pumps, and purification systems. Microgrids also power small machines that sustain agriculture in developing communities. The access to energy uplifts the developing community socially and economically. Still, as the community evolves, energy demand increases and the microgrid is unable to provide sufficient energy. A challenge in microgrid design involves the scalability of the system. Currently, there is no method for adapting the microgrid system to the increases in demand that occur over time. Accordingly, a mathematical framework is needed to support design decisions that could otherwise support adaptability. A demand model to predict the energy use for a composite rural village is presented. The predicted demand requirements are configured using a design optimization simulation model. These configurations are studied, and adaptive design techniques are devised through the process. The outcome of this study identifies a basic design methodology for microgrid design that is cognizant of scalability. Moreover, it identifies key attributes and relationships for the mathematical framework that supports the overarching goal of adaptable design.
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Milis, Kevin, and Herbert Peremans. "Economical Optimization of Microgrids: A Non-Causal Model." In ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/es2015-49634.

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In this paper we present an economical optimization model for a microgrid connected to the general electricity grid by minimizing the total operating cost over a given period in the presence of uncertain future grid electricity prices. The microgrid is modeled to consist of five distinct blocks, four of which make up the microgrid and the fifth one being the connection to the general electricity grid. Each of these components has various adjustable attributes, allowing for the simulation of different kinds of consumers as well as different storage and generation technologies. Consumption and intermittent generation are exogenous variables derived from existing datasets. Under uncertain future grid electricity prices, the storage component introduces a non-causal dependency into the model, to cope with this non-causality, we present various storage use strategies and analyze the resulting cost patterns using real electricity price data and Monte Carlo simulations.
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Novoselnik, Branimir, and Mato Baotic. "Coordinated microgrid control via parametric optimization." In 2016 IEEE International Energy Conference (ENERGYCON). IEEE, 2016. http://dx.doi.org/10.1109/energycon.2016.7513957.

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Kaczorowska, Dominika, and Jacek Rezmer. "Particle swarm algorithm for microgrid optimization." In 2018 Innovative Materials and Technologies in Electrical Engineering (i-MITEL). IEEE, 2018. http://dx.doi.org/10.1109/imitel.2018.8370472.

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Brown, Paul D., and Murat Gol. "Operational Optimization of an Agricultural Microgrid." In 2022 57th International Universities Power Engineering Conference (UPEC). IEEE, 2022. http://dx.doi.org/10.1109/upec55022.2022.9917806.

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Backlund, Peter B., and John P. Eddy. "Autonomous Microgrid Design Using Classifier-Guided Sampling." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46107.

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Identifying high-performance, system-level microgrid designs is a significant challenge due to the overwhelming array of possible configurations. Uncertainty relating to loads, utility outages, renewable generation, and fossil generator reliability further complicates this design problem. In this paper, the performance of a candidate microgrid design is assessed by running a discrete event simulation that includes extended, unplanned utility outages during which microgrid performance statistics are computed. Uncertainty is addressed by simulating long operating times and computing average performance over many stochastic outage scenarios. Classifier-guided sampling, a Bayesian classifier-based optimization algorithm for computationally expensive design problems, is used to search and identify configurations that result in reduced average load not served while not exceeding a predetermined microgrid construction cost. The city of Hoboken, NJ, which sustained a severe outage following Hurricane Sandy in October, 2012, is used as an example of a location in which a well-designed microgrid could be of great benefit during an extended, unplanned utility outage. The optimization results illuminate design trends and provide insights into the traits of high-performance configurations.
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Vidyashree, H. K., H. B. Jagadamba, and T. Yuvaraja. "Photovoltaic incorporated in microgrid system." In 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT). IEEE, 2017. http://dx.doi.org/10.1109/iceeccot.2017.8284671.

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Micky, R. Rohikaa, R. Lakshmi, R. Sunitha, and S. Ashok. "Assessment of voltage stability in microgrid." In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7754887.

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Lainfiesta, Maximiliano, and Xuewei Zhang. "Planning a Solar-Powered Microgrid for Remote Rural Communities on Mountainous Terrain." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7525.

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Based on a real-world scenario in Central America, this work is to plan and design a solar-powered microgrid for the rural communities who have had no access to electric power due to their distance from the grid as well as the mountainous terrain. The minimum spanning tree method is used to generate the initial grid topology and the difference between the results with and without the consideration of actual terrain effects is shown. The design of solar generation and energy storage has 3 options: a centralized solar park powering all communities, each community with a solar plant, and distributed generation at household level. Using dc power flow, we develop optimization algorithm to improve the solutions and compare the designs in terms of feasibility and resilience (against power congestion) or robustness (against structural damage). Through this case, it is demonstrated that our methodology can inform and assist the planning of solar-powered microgrids for remote communities.
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Afshar, Hady, Zahra Moravej, and Mohsen Niasati. "Modeling and optimization of microgrid considering emissions." In 2013 Smart Grid Conference (SGC). IEEE, 2013. http://dx.doi.org/10.1109/sgc.2013.6733812.

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Reports on the topic "Microgrid optimization"

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Stamp, Jason E., John P. Eddy, Richard P. Jensen, and Karina Munoz-Ramos. Microgrid Design Analysis Using Technology Management Optimization and the Performance Reliability Model. Office of Scientific and Technical Information (OSTI), January 2016. http://dx.doi.org/10.2172/1235988.

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Sandia National Laboratories. Microgrid Design Toolkit (MDT) Simple Use Case Example for Islanded Mode Optimization Software v1.1. Office of Scientific and Technical Information (OSTI), August 2016. http://dx.doi.org/10.2172/1494330.

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Eddy, John P. Microgrid Design Toolkit (MDT) Simple Use Case Example for Islanded Mode Optimization Software v1.2. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1599536.

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Eddy, John P., Samuel Gilletly, and Alisa Bandlow. Microgrid Design Toolkit (MDT) Simple Use Case Example for Islanded Mode Optimization (Software v1.3). Office of Scientific and Technical Information (OSTI), July 2020. http://dx.doi.org/10.2172/1642349.

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Jimenez, Antonio. Generic Community System Specification: A Proposed Format for Reporting the Results of Microgrid Optimization Analysis. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1427357.

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