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Multi-Objective Optimization Method for Proper Configuration of Grid-Connected PV-Wind Hybrid System in Terms of Ecological Effects, Outlay, and Reliability

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Abstract

The assessment of the performance of grid hybrid frameworks depends primarily on the costs and reliability, associated with reduced greenhouse gas (GHG) emissions of the system. In this work, with objectives based on the minimization of two optimization features, namely loss of power supply probability (LPSP) and cost of energy (COE), multi-objective optimization of a grid-connected PV/wind turbine framework was implemented in the Faculty of Engineering in Gharyan, Libya, with the aim of providing adequate electricity, while optimizing the system’s renewable energy fraction (REF) was the third objective. This research also aimed to estimate the resulting amount of power produced by the hybrid system and mathematical models were submitted. The results showed the share of the total energy supplying the electricity demand for each part of the network. This study subsequently explored the interrelationship of the grid and the proposed hybrid system in relation to the capacity of the network to sell or obtain electricity from the hybrid system. In addition, multi-objective bat algorithm (MOBA) findings were divided into three dominant regions: the first region was the economically optimal solution (lowest COE), the second region was the conceptual perspective of utilizing renewable energies (highest REF), and the final region was the optimal solution with optimal environmental effects (lowest GHG emissions).

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Karabuk University, Karabuk, 78100, Turkey

    Abdurazaq Elbaz & Muhammet Tahir Guneser

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  1. Abdurazaq Elbaz
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  2. Muhammet Tahir Guneser
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Correspondence to Abdurazaq Elbaz.

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Elbaz, A., Guneser, M.T. Multi-Objective Optimization Method for Proper Configuration of Grid-Connected PV-Wind Hybrid System in Terms of Ecological Effects, Outlay, and Reliability. J. Electr. Eng. Technol. 16, 771–782 (2021). https://doi.org/10.1007/s42835-020-00635-y

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  • DOI: https://doi.org/10.1007/s42835-020-00635-y

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