4.6 Article

Long-, Medium-, and Short-Term Nested Optimized-Scheduling Model for Cascade Hydropower Plants: Development and Practical Application

期刊

WATER
卷 14, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/w14101586

关键词

cascade hydropower plants; reservoir operation; optimized-scheduling model; genetic algorithm; dynamic programming

资金

  1. Beijing Natural Science Foundation [JQ21029]
  2. 2022 Qing Lan Project of Jiangsu province, China
  3. High level introduction of talent research start-up fund [YB20200501]
  4. Natural Science Foundation of Nanjing Vocational College of Information Technology [YK20190401]

向作者/读者索取更多资源

This paper presents a nested approach for generating long-term, medium-term, and short-term reservoir scheduling models based on the actual needs of the Three Gorges-Gezhouba cascade reservoirs. The study also introduces various solving algorithms used in the multi-time scale coordinated and optimized scheduling model and compares their performance. The results show that the proposed models have better efficiency and good convergence, achieving maximization of the power generation benefits without violating any scheduling regulations.
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-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)-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-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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