| Issue |
E3S Web Conf.
Volume 694, 2026
Third International Conference on Green Energy, Environmental Engineering and Sustainable Technologies 2025 (ICGEST 2025)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 11 | |
| Section | Green Energy Systems & Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202669403003 | |
| Published online | 16 February 2026 | |
Integration of Renewable energy sources with Battery Energy Storage for Line Loss Reduction in Distribution Networks using HALACBO algorithm
School of Energy & Environment Studies, Devi Ahilya Vishwavidhyalay, Indore, India
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Abstract
Line loss is a critical indicator of energy management efficiency in low-voltage power systems, with transformer areas contributing significantly to overall distribution losses. It is vital to reduce these losses to enhance efficiency, minimize wastage of energy, and enable sustainable power distribution. A new hybrid optimization method, HALACBO, which combines the Artificial Lemming Algorithm (ALA) with Coyote and Badger Optimization (CBO), is presented in this research. The method emphasizes finding the best location and size of distributed generation (DG) units and solving voltage profile enhancement and harmonic distortion constraints. Renewable energy sources (RES) like photovoltaic (PV) systems, wind turbines, and battery energy storage systems (BESS) are integrated in order to improve grid performance. Simulation results based on the IEEE 33-bus test system implemented in MATLAB confirm that the devised model effectively mitigates line losses providing better results. The results validate HALACBO's capability to improve efficiency and integration of renewables. When compared to other existing algorithm, the proposed technique has low fitness value at 20 iterations.
Key words: Distribution Networks / HALACBO algorithm / line loss / BESS / Solar / wind and Renewable energy sources
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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