Long-, Medium-, and Short-Term Nested Optimized-Scheduling Model for Cascade Hydropower Plants: Development and Practical Application
2022
Ling Shang | Xiaofei Li | Haifeng Shi | Feng Kong | Ying Wang | Yizi Shang
This paper presents a nested approach for generating long-term, medium-term, and short-term reservoir scheduling models, which is based on the actual needs of the scheduling operation of the Three Gorges&ndash:Gezhouba (TG-GZB) cascade reservoirs. The approach has established a five-tier optimal scheduling model in which the time interval of the scheduling plan prepared by the model can be as short as 15 min, meeting the real-time scheduling requirements of the cascade hydropower station system. This study also presents a comparatively comprehensive introduction to all solving algorithms that have ever been adopted in the multi-time scale coordinated and optimized scheduling model. Based on that, some practical and efficient solving algorithms are developed for the characteristics of the scheduling model, including the coupled iterative method of alternating reservoirs (CIMAR)&mdash:the improved dynamic programming (IDP) algorithm and the improved genetic algorithm (IGA). In addition, optimized-scheduling solutions were generated by each of the three algorithms and were compared in terms of their convergence rate, calculation time, electric energy generated, and standard deviation of the algorithm. The results based on the Cascade Scheduling and Communication System (CSCS) of Three Gorges&ndash:Gezhouba, China, which includes two interlinked mega-scale reservoir projects, show that scheduling models have better efficiency and good convergence, and more importantly, the maximization of the power generation benefits of the hydropower plants has been achieved without violating any of the reservoir scheduling regulations.
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