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Minimizing energy import cost for load demand with optimal penetration of renewable energy generation sources by using an efficient Walrus optimization algorithm

2026-06-10 · Springer Link (Chiba Institute of Technology)

One-line summary

A solar energy research paper on Minimizing energy import cost for load demand with optimal penetration of renewable energy generation sources by using an efficient Walrus optimization algorithm.

Engineering notes

Engineering notes will be added by the Power for Solar editorial team.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original 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.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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