A posteriori multiobjective approach for techno-economic allocation of PV and BES units in a distribution system hosting PHEVs
Matta Mani Sankar and
Kalyan Chatterjee
Applied Energy, 2023, vol. 351, issue C, No S0306261923012151
Abstract:
This paper proposes a posteriori multiobjective approach to effectively integrate photovoltaic (PV) units into the distribution network. PV units are inherently non-dispatchable sources due to the intermittent nature of solar irradiance. To address this limitation, battery energy storage (BES) units are employed to support the PV units, thereby transforming them into dispatchable sources. The objective of this study is to optimally allocate dispatchable PV-BES units within a distribution network that accommodates plug-in hybrid electric vehicles (PHEVs). The PHEVs are modelled considering stochastic parameters at three different demand response levels. A multiobjective optimization problem is formulated to address the conflicting technical and economic objectives associated with the allocation of PV-BES units. The multiobjective manta ray foraging optimizer algorithm is utilized for solving the multiobjective optimization problem. Additionally, the technique for order of preference by similarity to ideal solution is used to identify the best trade-off solution, and multiple solutions are presented based on the decision-makers preferences regarding the conflicting objectives under consideration. The proposed approach is validated on 33-bus and 69-bus distribution networks, and extensive case studies are conducted to showcase the advantages of the proposed methodology.
Keywords: Distributed energy resources; Photovoltaic units; Battery energy storage units; Plug-in hybrid electric vehicles; Multiobjective optimization; Technique for order of preference by similarity to ideal solution (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:351:y:2023:i:c:s0306261923012151
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DOI: 10.1016/j.apenergy.2023.121851
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