Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm
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...
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| Format: | Article |
| Language: | English |
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2025-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/2/365 |
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| author | Hongbo Zou Jiehao Chen Fushuan Wen Yuhong Luo Jinlong Yang Changhua Yang |
| author_facet | Hongbo Zou Jiehao Chen Fushuan Wen Yuhong Luo Jinlong Yang Changhua Yang |
| author_sort | Hongbo Zou |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c5665c3c95794db0b638944891346210 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-c5665c3c95794db0b6389448913462102025-01-24T13:31:13ZengMDPI AGEnergies1996-10732025-01-0118236510.3390/en18020365Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican AlgorithmHongbo Zou0Jiehao Chen1Fushuan Wen2Yuhong Luo3Jinlong Yang4Changhua Yang5College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaHainan Institute, Zhejiang University, Sanya 572025, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaIn 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.https://www.mdpi.com/1996-1073/18/2/365renewable energyeconomic dispatchmulti-objective optimizationpower system cost reduction |
| spellingShingle | Hongbo Zou Jiehao Chen Fushuan Wen Yuhong Luo Jinlong Yang Changhua Yang Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm Energies renewable energy economic dispatch multi-objective optimization power system cost reduction |
| title | Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm |
| title_full | Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm |
| title_fullStr | Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm |
| title_full_unstemmed | Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm |
| title_short | Optimal Scheduling of Multi-Energy Complementary Systems Based on an Improved Pelican Algorithm |
| title_sort | optimal scheduling of multi energy complementary systems based on an improved pelican algorithm |
| topic | renewable energy economic dispatch multi-objective optimization power system cost reduction |
| url | https://www.mdpi.com/1996-1073/18/2/365 |
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