Hydro Unit Commitment via Mixed Integer Linear Programming: A Case Study of the Three Gorges Project, China

• Published in: IEEE transactions on power systems Vol. 29; no. 3; pp. 1232 - 1241
• Main Authors: Xiang Li, Tiejian Li, Jiahua Wei, Guangqian Wang, Yeh, William W-G
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: China; Computational modeling; Hydro unit commitment; Hydroelectric plants; Hydroelectric power generation; hydropower; Integer programming; Linear programming; Mathematical analysis; Mathematical model; Mathematical models; Mixed integer; Mixed integer linear programming; Nonlinearity; Power generation; Reservoirs; Three Gorges Project (China); Unit commitment
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2013.2288933

This paper develops a methodology for optimizing the hydro unit commitment (HUC) for the Three Gorges Project (TGP) in China. The TGP is the world's largest and most complex hydropower system in operation. The objective is to minimize the total operational cost. The decision variables are the startup or shutdown of each of the available units in the system and the power releases from the online units. The mathematical formulation must take into account the head variation over the operation periods as the net head changes from hour to hour and affects power generation. Additionally, the formulation must consider the operation of 32 heterogeneous generating units and the nonlinear power generation function of each unit. A three-dimensional interpolation technique is used to accurately represent the nonlinear power generation function of each individual unit, taking into account the time-varying head as well as the non-smooth limitations for power output and power release. With the aid of integer variables that represent the on/off and operation partition statuses of a unit, the developed HUC model for the TGP conforms to a standard mixed integer linear programming (MILP) formulation. We demonstrate the performance and utility of the model by analyzing the results from several scenarios for the TGP.