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- W2027107332 abstract "An evolutionary iteration particle swarm optimisation (EIPSO) approach for optimal wind–battery coordination in a power system is proposed. The up-spinning reserve and down-spinning reserve are introduced into the wind–battery coordination problem to improve system security and the wind utilisation factor. The optimal operating schedule for a battery energy storage system (BESS) and thermal unit was reached while minimising the total operating cost. Taiwan Power Company System is used as a numerical example to test the new algorithm. The feasibility of the new algorithm is demonstrated by the numerical example, and the EIPSO solution quality and computation efficiency are compared with those of other algorithms. The results are used to evaluate the effects of the wind turbine generator and BESS on power system operations." @default.
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- W2027107332 date "2008-01-01" @default.
- W2027107332 modified "2023-09-25" @default.
- W2027107332 title "Optimal wind–battery coordination in a power system using evolutionary iteration particle swarm optimisation" @default.
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- W2027107332 doi "https://doi.org/10.1049/iet-gtd:20070245" @default.
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