Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/10692
Title: Energy management of a photovoltaic–wind–battery energy storage microgrid using linear programming and grey wolf optimization techniques
Authors: Mojela, Nteka Maletsie 
Krishnamurthy, Senthil 
Keywords: Battery energy storage;Energy Management;Grey Wolf Optimization;Linear Programming;Microgrids;Photovoltaic system;Renewable Energy;Wind Energy
Issue Date: 2025
Publisher: The Scientific Club of Al Manahil Association
Source: Mojela, N.M. & Krishnamurthy, S. 2025. Energy management of a photovoltaic–wind–battery energy storage microgrid using linear programming and grey wolf optimization techniques. International Journal of Energetica, 10(2): 29-48. [https://www.ijeca.info/index.php/IJECA/article/view/288]
Journal: International Journal of Energetica 
Abstract: This study presents a comprehensive optimization analysis of a renewable energy–based hybrid microgrid integrating photovoltaic (PV), wind generation, and battery energy storage systems (BESS). The microgrid energy dispatch problem is formulated through detailed cost models for PV generation, wind power production, and battery charging–discharging operations. Two optimization techniques—Linear Programming (LP) and Grey Wolf Optimization (GWO) are applied to minimize operational and maintenance costs while improving overall system efficiency. The performance of LP and GWO is systematically evaluated through six operational case studies involving different combinations of PV, wind, battery storage, and grid interaction. For the LP-based optimization, the total operating costs are $14,090.91 for Case Study 1 (Wind–PV–Battery–Grid), $9,761.02 for Case Study 2 (Wind–Grid), and $16,074.56 for Case Study 3 (PV–Battery–Grid). In contrast, the GWO-based optimization yields operating costs of $5,802.44 for Case Study 4 (Wind–PV–Battery–Grid), $6,605.37 for Case Study 5 (Wind–Grid), and $15,668.82 for Case Study 6 (PV–Battery–Grid). A comparative analysis of the results demonstrates that the GWO technique consistently achieves lower operating costs than the LP approach, particularly for the Wind–PV–Battery–Grid configuration, where the minimum cost is $5,802.44. These findings highlight the superior capability of metaheuristic optimization in handling the nonlinear and complex nature of hybrid microgrid energy management problems. Overall, the results provide valuable insights into cost-effective microgrid operation and underscore the potential of advanced optimization techniques for enhancing the economic viability and sustainable integration of renewable energy resources. Results not only reveal the implications for optimizing microgrid operations but also provide indispensable insights for developing cost-effective strategies that emphasize the sustainable integration of renewable energy resources. This study is a valuable resource for researchers and stakeholders seeking to expand the operational efficiency and economic viability of hybrid microgrid systems.
URI: https://www.ijeca.info/index.php/IJECA/article/view/288
http://hdl.handle.net/11189/10692
ISSN: 2543-3717 (Online)
Appears in Collections:Eng - Journal articles (DHET subsidised)

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