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论文类型：期刊论文

发表时间：2018-04-01

发表刊物：WATER RESOURCES RESEARCH

收录刊物：SCIE

卷号：54

期号：4

页面范围：2834-2850

ISSN号：0043-1397

摘要：This paper proposes a practical procedure for optimizing the daily operation of a large-scale hydrothermal system. The overall procedure optimizes a monthly model over a period of 1 year and a daily model over a period of up to 1 month. The outputs from the monthly model are used as inputs and boundary conditions for the daily model. The models iterate and update when new information becomes available. The monthly hydrothermal model uses nonlinear programing (NLP) to minimize fuel costs, while maximizing hydropower production. The daily model consists of a hydro model, a thermal model, and a combined hydrothermal model. The hydro model and thermal model generate the initial feasible solutions for the hydrothermal model. The two competing objectives considered in the daily hydrothermal model are minimizing fuel costs and minimizing thermal emissions. We use the constraint method to develop the trade-off curve (Pareto front) between these two objectives. We apply the proposed methodology on the Yunnan hydrothermal system in China. The system consists of 163 individual hydropower plants with an installed capacity of 48,477 MW and 11 individual thermal plants with an installed capacity of 12,400 MW. We use historical operational records to verify the correctness of the model and to test the robustness of the methodology. The results demonstrate the practicability and validity of the proposed procedure.