Power Distribution Optimization Based on Demand Respond with Improved Multi-Objective Algorithm in Power System Planning
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Cited by:
- Zhihan Shi & Weisong Han & Guangming Zhang & Zhiqing Bai & Mingxiang Zhu & Xiaodong Lv, 2022. "Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties," Energies, MDPI, vol. 15(24), pages 1-20, December.
- Lau, Jat-Syu & Jiang, Yihuo & Li, Ziyuan & Qian, Qian, 2023. "Stochastic trading of storage systems in short term electricity markets considering intraday demand response market," Energy, Elsevier, vol. 280(C).
- Ma, Jinpeng & Wu, Shengbin & Raad, Erfan Ahli, 2023. "Renewable source uncertainties effects in multi-carrier microgrids based on an intelligent algorithm," Energy, Elsevier, vol. 265(C).
- Wang, Fei & Lu, Xiaoxing & Chang, Xiqiang & Cao, Xin & Yan, Siqing & Li, Kangping & Duić, Neven & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Household profile identification for behavioral demand response: A semi-supervised learning approach using smart meter data," Energy, Elsevier, vol. 238(PB).
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Keywords
multi-objective optimization; artificial bee colony; dynamic economic and emission dispatch; demand side management; load shifting;All these keywords.
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