Application of Minimum Reward Risk Model in Reservoir Generation Scheduling

Ming Zhang (), Fei Yang, Jing-Xiu Wu, Zi-Wu Fan and Ying-Ying Wang

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 4, 1345-1355

Abstract: Discrete time Markov decision process is studied and the minimum reward risk model is established for the reservoir long-term generation optimization. Different form the commonly used optimization criterion of best expected reward in reservoir scheduling, the probability that the expected generation of the whole period not exceeding the predete reward target to be smallest is chosen as the optimizing target for this random process. For the hydropower tends to operate as peak-clipping mode in Market-based model to gain more profits, the function of electricity price and output can be founded by analyzing on the typical day load course of the electricity system. Compared with the generally used criteria of the largest expectation power generation model, this model is fitted for the decision-making in which the risk is needed to be limited to reflect the risk preference of the policy makers. Stochastic dynamic programming method is adopted to solve the model and the model is tested on the Three Gorges Hydropower Station. Copyright The Author(s) 2016

Keywords: Markov decision process; Minimum risk criteria; Peak-clipping operation mode; The optimal scheduling strategy; Risk preference (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11269-015-1218-1

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