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- W4386819228 abstract "Power systems encounter frequent challenges related to imbalances between load and generation, prompting the exploration of Demand Side Management (DSM) techniques, notably through the adoption of Demand Response Programs (DRPs). Nevertheless, integrating DRPs into smart grids presents complexities. This research paper proposes an enhanced Weighted Fuzzy Average (WFA) K-means clustering algorithm to effectively group consumers' load patterns. Furthermore, the behaviors of DRP implementations for each consumption cluster are modeled in both linear and nonlinear fashions, utilizing the Coefficient of Participation (CoP) as the foundation for these models. To identify the most optimum DRP program, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is employed, with decision indicators weighted using Shannon entropy. The proposed method is then evaluated by simulating a 33-bus Microgrid (MG) with uncertain generation, incorporating wind turbine, photovoltaic, and Battery Energy Storage System (BESS) components. The outcomes demonstrate that through the optimal application of DRPs in a microgrid, diverse objectives of consumers and utility companies can be successfully attained." @default.
- W4386819228 created "2023-09-19" @default.
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- W4386819228 date "2023-12-01" @default.
- W4386819228 modified "2023-09-27" @default.
- W4386819228 title "Optimal implementation of consumer demand response program with consideration of uncertain generation in a microgrid" @default.
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- W4386819228 doi "https://doi.org/10.1016/j.epsr.2023.109859" @default.
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