Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm

Hongbo Zou, Jiehao Chen, Fushuan Wen (), Yuhong Luo, Jinlong Yang and Changhua Yang
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Hongbo Zou: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Jiehao Chen: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Fushuan Wen: Hainan Institute, Zhejiang University, Sanya 572025, China
Yuhong Luo: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Jinlong Yang: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Changhua Yang: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China

Energies, 2025, vol. 18, issue 2, 1-26

Abstract: In recent years, the global power industry has experienced rapid development, with significant advancements in the source, network, load sectors, and energy storage technologies. The secure, reliable, and economical operation of power systems is a critical challenge. Due to the stochastic nature of intermittent renewable energy generation and the coupled time-series characteristics of energy storage systems, it is essential to simulate uncertain variables accurately and develop optimization algorithms that can effectively tackle multi-objective problems in economic dispatch models for microgrids. This paper proposes a pelican algorithm enhanced by multi-strategy improvements for optimal generation scheduling. We establish eight scenarios with and without pumped storage across four typical seasons—spring, summer, autumn, and winter—and conduct simulation analyses on a real-world case. The objective is to minimize the total system cost. The improved pelican optimization algorithm (IPOA) is compared with other leading algorithms, demonstrating the validity of our model and the superiority of IPOA in reducing costs and managing complex constraints in optimization.

Keywords: renewable energy; economic dispatch; multi-objective optimization; power system cost reduction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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