Probabilistic approach to multi-objective Volt/Var control of distribution system considering hybrid fuel cell and wind energy sources using Improved Shuffled Frog Leaping Algorithm
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DOI: 10.1016/j.renene.2011.08.004
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- Niknam, Taher & Firouzi, Bahman Bahmani & Ostadi, Amir, 2010. "A new fuzzy adaptive particle swarm optimization for daily Volt/Var control in distribution networks considering distributed generators," Applied Energy, Elsevier, vol. 87(6), pages 1919-1928, June.
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Cited by:
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- Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
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- Samimi, Abouzar & Nikzad, Mehdi & Siano, Pierluigi, 2017. "Scenario-based stochastic framework for coupled active and reactive power market in smart distribution systems with demand response programs," Renewable Energy, Elsevier, vol. 109(C), pages 22-40.
- Mortazi, Mohammad & Moradi, Ahmad & Khosravi, Mohsen, 2020. "Simultaneous optimization of transformer tap changer and network capacitors to improve the distribution system’s static security considering distributed generation sources," MPRA Paper 109052, University Library of Munich, Germany, revised 01 Jul 2020.
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- Fengli Jiang & Yichi Zhang & Yu Zhang & Xiaomeng Liu & Chunling Chen, 2019. "An Adaptive Particle Swarm Optimization Algorithm Based on Guiding Strategy and Its Application in Reactive Power Optimization," Energies, MDPI, vol. 12(9), pages 1-14, May.
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Keywords
Wind farms; Fuel cell power plant; Stochastic optimization; Volt/Var control; Probabilistic power flow;All these keywords.
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