Study on the peak shaving operation of cascade hydropower stations based on the plant-wide optimal curve
A large number of renewable energy sources (RESs), such as wind and photovoltaics (PV), have increased the importance of hydropower stations with regulating capacity in peak shaving operation. However, optimizing load distribution among cascade hydropower units remains challenging. This study propos...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525004685 |
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| Summary: | A large number of renewable energy sources (RESs), such as wind and photovoltaics (PV), have increased the importance of hydropower stations with regulating capacity in peak shaving operation. However, optimizing load distribution among cascade hydropower units remains challenging. This study proposes a novel method to enhance RES and hydropower utilization through: 1) Establishing a plant-wide optimal output-water level-outflow relationship curve based on the output-head-flow relationship and the flow-head loss and outflow-tailwater level relationship curves for each unit; 2) Developing a short-term peak shaving model for cascaded hydropower stations that incorporates wind and PV power which defines minimum coefficient of variation of residual load as objective functions, and improving discrete differential dynamic programming successive approximation (DDDPSA) method to solve it; 3) Analyzing the peak shaving capacity of the cascade hydropower station by varying water consumption for power generation. A case study on the Hongshui River demonstrates the practicality and effectiveness of the proposed method. The computation time is reduced by over 98% in typical scenarios, and the proposed algorithm maintains convergence even when the traditional method fails. The model provides technical support for the integrated scheduling of hydropower, wind, and PV systems. |
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| ISSN: | 0142-0615 |