Journal of Advances in Developmental Research

E-ISSN: 0976-4844     Impact Factor: 9.71

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 17 Issue 1 January-June 2026 Submit your research before last 3 days of June to publish your research paper in the issue of January-June.

Advanced Hybrid HHO–SCA Algorithm for Optimal Allocation of EV Charging Stations and Renewable Energy Sources

Author(s) Anup Kumar Mahto, Sandip Kumar
Country India
Abstract The rapid growth of electric vehicles (EVs) and renewable energy sources (RES) is transforming modern power distribution networks. However, uncoordinated integration of EV charging stations and renewable generation may lead to voltage instability, increased power losses, and degradation of power quality. This paper proposes an advanced hybrid optimization algorithm combining Harris Hawks Optimization (HHO) and the Sine Cosine Algorithm (SCA) to determine the optimal allocation and sizing of EV charging stations and renewable energy sources in distribution systems. The hybrid HHO–SCA algorithm improves global search capability and convergence speed while avoiding premature convergence. The optimization objective minimizes total power losses, voltage deviation, and operational cost while satisfying network constraints. The proposed method is tested on the IEEE 33-bus distribution system. Simulation results demonstrate significant improvements in voltage profile, reduced system losses, and enhanced system reliability compared with conventional optimization techniques.
Keywords Renewable Energy Systems (RES), Electric Vehicles (EVs), Harris Hawks Optimization (HHO), Sine Cosine Algorithm (SCA), IEEE 33-bus distribution system.
Field Engineering
Published In Volume 17, Issue 1, January-June 2026
Published On 2026-03-16
Cite This Advanced Hybrid HHO–SCA Algorithm for Optimal Allocation of EV Charging Stations and Renewable Energy Sources - Anup Kumar Mahto, Sandip Kumar - IJAIDR Volume 17, Issue 1, January-June 2026.

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