Energy Optimization Of Distributed Energy Resources In Microgrids For Ev Charging Stations

Authors

  • Mihir K. Patel

Keywords:

Microgrid, Distributed Energy Resources (DERs) Artificial Intelligence (AI), Energy Management System (EMS) Optimization, Load Forecasting, Renewable Energy, Smart Grid.

Abstract

It is imperative that more study be done on energy optimization in microgrids with distributed energy resources (DERs), especially as renewable energy sources like solar and wind power grow in popularity. There is a lot of promise for increasing grid reliability, cutting costs, and improving efficiency by incorporating artificial intelligence (AI) tools into this process. The intricate optimization challenge in DER management is resolved by AI approaches including ant colony optimization (ACO), particle swarm optimization (PSO), and genetic algorithms (GA). It is still difficult to manage and optimize DERs when there are sporadic renewable energy sources present. The use of artificial intelligence (AI) approaches for microgrid energy distribution optimization is thoroughly reviewed and analysed in this work. The energy sources' cost-priority based energy management strategy (CEMS) for the SWEG model has been developed to charge the EVs.  The proposed methodology is compared with that of the PSO and GA algorithms. The outcome shows that PSO optimization gives the best cost compared to GA. The amount of grid power used to drop by 37%, resulting in a 27.86 kg carbon dioxide reduction throughout the day. In this work, the use of a novel bio-inspired optimization method called the Zebra Optimization Algorithm (ZOA) for energy optimization in microgrids with distributed energy resources (DERs) is examined. The simulation analysis is done in MATLAB tool to see the effectiveness of the system accompanied with power loss, voltage imbalance and THD analysis. Case study is based on microgrid integrated with RES and BESS

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Published

2025-04-07

How to Cite

1.
K. Patel M. Energy Optimization Of Distributed Energy Resources In Microgrids For Ev Charging Stations. J Neonatal Surg [Internet]. 2025 Apr. 7 [cited 2026 Oct. 14];14(14S):965-86. Available from: https://jneonatalsurg.com/index.php/jns/article/view/10579

Issue

Vol. 14 No. 14S (2025): Journal of Neonatal Surgery

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Original Article

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