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Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response
This paper presents a new robust scheduling model for an islanded microgrid (MG) considering demand response. The model is expressed as a min–max bilevel optimization problem that tries to minimize the total costs of MG including operation cost of conventional distributed generators, energy storages, renewable energy sources (RES), cost of load shifting, and interruptible/non-interruptible load shedding in the worst situation of uncertainties. The uncertainties associated with renewable power generations and MG demand are modeled via robust optimization method. A hybrid method based on the genetic algorithm (GA) and mixed-integer programming technique is utilized to solve the bilevel optimization problem. The proposed model is utilized on a typical MG, and the outcomes are analyzed to show the effectiveness of the proposed method.
Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response
This paper presents a new robust scheduling model for an islanded microgrid (MG) considering demand response. The model is expressed as a min–max bilevel optimization problem that tries to minimize the total costs of MG including operation cost of conventional distributed generators, energy storages, renewable energy sources (RES), cost of load shifting, and interruptible/non-interruptible load shedding in the worst situation of uncertainties. The uncertainties associated with renewable power generations and MG demand are modeled via robust optimization method. A hybrid method based on the genetic algorithm (GA) and mixed-integer programming technique is utilized to solve the bilevel optimization problem. The proposed model is utilized on a typical MG, and the outcomes are analyzed to show the effectiveness of the proposed method.
Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response
Monir Sadat AlDavood (Autor:in) / Abolfazl Mehbodniya (Autor:in) / Julian L. Webber (Autor:in) / Mohammad Ensaf (Autor:in) / Mahdi Azimian (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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