Abstract
This paper proposes the artificial intelligence technique based on hybrid optimization phasor particle swarm optimization and a gravitational search algorithm, called PPSO-GSA for optimal allocation of renewable energy-based distributed generators (OA-RE-DGs), particularly wind and solar power generators, in distribution networks. The main objective is to maximize the techno-economic benefits in the distribution system by optimal allocation and integration of RE-DGs into distribution system. The proposed PPSO-GSA is implemented and validated on 94-bus practical distribution system located in Portuguese considering single and multiple scenarios of RE-DGs installation. The results reveal that optimizing the location and size of RE-DGs results in a substantial reduction in active power loss and yearly economic loss as well as improving system voltage profile and stability. Moreover, the convergence characteristics, computational efficiency and applicability of the proposed artificial intelligence technique is evaluated by comparative analysis and comparison with other optimization techniques.
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The authors would like to thank the State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology for providing the essential facilities.
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Ullah, Z., Elkadeem, M.R., Wang, S. (2020). Artificial Intelligence Technique for Optimal Allocation of Renewable Energy Based DGs in Distribution Networks. In: Barolli, L., Hellinckx, P., Enokido, T. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2019. Lecture Notes in Networks and Systems, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-33506-9_36
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DOI: https://doi.org/10.1007/978-3-030-33506-9_36
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