Water cycle algorithm-based optimal control strategy for efficient operation of an autonomous microgrid

This study presents a novel water cycle algorithm (WCA)-based optimal control strategy with the purpose of obtaining an efficient operation of an autonomous microgrid. The proposed control strategy is based on the proportional–integral (PI) controllers, which are optimally designed by the WCA. The o...

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Bibliographic Details
Published inIET generation, transmission & distribution Vol. 12; no. 21; pp. 5739 - 5746
Main Authors Hasanien, Hany M, Matar, Mahmoud
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 27.11.2018
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ISSN1751-8687
1751-8695
DOI10.1049/iet-gtd.2018.5715

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Summary:This study presents a novel water cycle algorithm (WCA)-based optimal control strategy with the purpose of obtaining an efficient operation of an autonomous microgrid. The proposed control strategy is based on the proportional–integral (PI) controllers, which are optimally designed by the WCA. The optimisation process depends on the simulation-based optimisation approach and the criteria of integral squared error are chosen as an objective function. The control scheme is applied to an autonomous, decentralised, operation of a microgrid with multiple electronically interfaced distributed generation units and their local loads. In the islanded mode, the proposed controller is used to control the voltages of the islanded system despite the microgrid load and topological variability and uncertainties. The frequency of the islanded system is dictated through the use of an internal oscillator. The effectiveness of the proposed controller is compared with that obtained using the genetic algorithm-based PI controller. The validity of the proposed control strategy is extensively checked based on simulation studies in the PSCAD/EMTDC environment under different operating conditions of the microgrid. With the application of the WCA-based optimal PI control scheme, the microgrid operation can be further enhanced.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2018.5715