Open AccessMulti-time-scale nested optimal scheduling model for cascaded hydropower reservoirs
Author(s) -
Keyan Shen,
Qing Hui,
Jianzhong Zhou
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/768/1/012012
Subject(s) - hydropower , scheduling (production processes) , computer science , mathematical optimization , electricity generation , operations research , power (physics) , engineering , mathematics , physics , quantum mechanics , electrical engineering
As more hydropower plants are in operation, it is difficult to balance the medium-and long-term benefits with the short-term benefits when developing an optimal scheme for power generation from cascaded hydropower reservoirs. And traditional models have difficulty making full use of the latest runoff forecast information. To overcome these problems, a multi-time-scale nested optimal scheduling model for cascaded hydropower reservoirs is developed. This model analyzes the level-by-level control strategy and rolling update mechanism between upper and lower level submodels. An efficient algorithm for solving the model is also given. In this study, the model is applied to four cascaded hydropower reservoirs located at the Yangtze River. The case study shows that the developed model can better coordinate the medium- and long-term benefits with the short-term benefits, make full use of the latest forecast information, and enhance the power generation efficiency of the cascaded hydropower reservoirs. Compared with the results of the existing scheduling model, the total power generation from the proposed model is improved under the same boundary conditions.