| Issue |
Sci. Tech. Energ. Transition
Volume 81, 2026
|
|
|---|---|---|
| Article Number | 17 | |
| Number of page(s) | 14 | |
| DOI | https://doi.org/10.2516/stet/2026016 | |
| Published online | 10 June 2026 | |
Regular Article
Minimizing energy import cost for load demand with optimal penetration of renewable energy generation sources by using an efficient Walrus optimization algorithm
Faculty of Electrical and Electronics Engineering, Thuyloi University, Hanoi 11515, Vietnam
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
19
June
2025
Accepted:
11
May
2026
Abstract
This paper presents a novel and effective approach for determining the optimal penetration of Renewable distributed Energy Resources (RESs) in Radial Distribution Networks (RDNs) considering time-varying generation and consumption. Walrus Optimization Algorithm (WaOA), which is inspired by the intelligent behaviors of walruses in the wild, is introduced to solve this optimization problem. The main target is to minimize the electricity generation cost by the main power source and the total power loss of the network. By determining appropriate installation parameters of access location, sizing, and operating power factor for solar Photovoltaics (PVs) and Wind Turbines (WTs), the cost from electricity purchase of the primary grid through the substation is reduced by 79.57%, and the power loss is cut by 95.06% compared to the original network. In addition, the bus voltage improvement and congestion reduction on branches are also greatly enhanced, with the weakest voltage being pulled from 0.9090 to 0.9785 pu, and the largest branch current also being sharply decreased from 387.1941A to 163.7125A. Moreover, the collected simulation results also prove the superiority of WaOA over other methods of particle swarm optimization algorithm (PSO) and Bacterial Foraging Optimization Algorithm (BFOA) in addressing the above problem under the same conditions.
Key words: Walrus optimization algorithm / Metaheuristic algorithms / Renewable energies / Solar photovoltaics / Wind turbines / The distribution network
© The Author(s), published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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