A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations
The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. The CHIO algorithm was enhanced by adopting two strategies: the Latin hypercube strategy for generating...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Pearl River
2025-01-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails?columnId=100469473&Fpath=home&index=0 |
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| Summary: | The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. The CHIO algorithm was enhanced by adopting two strategies: the Latin hypercube strategy for generating initial population solutions and dynamic social distance and adaptive threshold strategies. These improvements balanced global search and local search, preventing premature convergence while accelerating the convergence speed. Simulation results for four cascade hydropower plants in a region in southwest China show that the difference between the results of CHIO and LCHIO and the dynamic programming POA-DDDP is less than 1%, and the variation coefficients are 0.13% and 0.11%, which verify the rationality and effectiveness of CHIO to solve the cascade reservoir group scheduling problem and the improvement effect of LCHIO algorithm on CHIO. Further analysis of multiple objective function models for the equivalent grid reveals issues such as the coexistence of power shortages and curtailment, difficulties in renewable energy absorption, and weak generation capacity during dry periods. These challenges highlight the need for the development of pumped storage. |
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| ISSN: | 1001-9235 |