Medium-Term Hydro Generation Scheduling (MTHGS) with Chance Constrained Model (CCM) and Dynamic Control Model (DCM)

Jianzhong Zhou (), Mengfei Xie (), Zhongzhen He, Hui Qin and Liu Yuan
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Jianzhong Zhou: Huazhong University of Science and Technology
Mengfei Xie: Huazhong University of Science and Technology
Zhongzhen He: Huazhong University of Science and Technology
Hui Qin: Huazhong University of Science and Technology
Liu Yuan: Huazhong University of Science and Technology

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2017, vol. 31, issue 11, No 17, 3543-3555

Abstract: Abstract Medium-Term Hydro Generation Scheduling (MTHGS) plays an important role in the operation of hydropower systems. In the first place, this paper presents a Chance Constrained Model for solving the optimal MTHGS problem. The model recognizes the impact of inflow uncertainty and the constraints involving hydrologic parameters subjected to uncertainty are described as probabilistic statements. It aims at providing a more practical technique compared to the traditional deterministic approaches used for MTHGS. The stochastic inflow is expressed as a simple discrete-time Markov chain and Stochastic Dynamic Programming is adopted to solve the model. Then in order to use the information of long-term inflow forecast to improve dispatching decisions, a Dynamic Control Model is developed. Short-term forecast results of the current period and long-term forecast results of the remaining period are treated as inputs of the model. Finally, the two methods are applied to MTHGS of Xiluodu hydro plant in China. The results are compared to those obtained from Deterministic Dynamic Programming with hindsight and advantages and disadvantages of the two methods are analyzed.

Keywords: Medium-term hydro generation scheduling; Chance constrained model; Stochastic inflow; Stochastic dynamic programming; Dynamic control model (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11269-017-1683-9

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