Application of Minimum Reward Risk Model in Reservoir Generation Scheduling

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.

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

“…Tang et al [185,186] Heihe River Basin Li and Guo [107], Li et al [109,111] and Zhang et al [231] Heshui River Basin Li et al [117], Liu et al [128,132] and Xu et al [212] Huai River Basin Gu et al [73] and Li et al [112] Hun River Xu et al [215,216] Kaidu-Kongque River Basin Huang et al [88,90], Li et al [125], Zeng et al [222,224,[226][227][228][229] and Zhou et al [242] Lake Tai Watershed Liu et al [134] and Xu and Huang [217] Miyun Reservoir Han et al [81] and Rong et al [175] Nansihu Lake Basin Xie et al [207,209] Tarim River Basin Huang et al [88][89][90] Three Gorges Reservoir Feng et al [58], Han et al [79], Han et al [87], Huang et al [91], Li et al [126], Xu et al [211], Yuan et al [220] and Zhang et al [236] Xiangxi River Basin Han et al [79], Hu et al [86,87], Huang et al …”

Water-richness evaluation method and application of clastic rock aquifer in mining seam roof

“…After calculating the subjective and objective weights using AHP and improved rough set theory, to balance the subjectivity and objectivity of the weight indicators and complement each other’s strengths and weaknesses, a combination weighting method based on minimum deviation was adopted to fuse the subjective and objective weights, reduced the errors caused by a single weighting method, and obtained a more scientific and reasonable comprehensive weight 37 , 38 .…”

Planning of Cascade Hydropower Stations with the Consideration of Long‐Term Operations under Uncertainties

“…Among the five hydropower station candidates, at least two of them should be chosen in the plan. Unit construction fee (e) and unit profit of power generation (f ) in Table 1 are set to be 5.09 (RMB/m 3 ) and 0.25 (RMB/KWh), respectively [46]. Related parameters regarding five candidates are displayed in Table 3.…”