Research on multi-objective optimal operation model in EPing hydropower station

2011 ◽  
Author(s):  
Xiaohui Lei ◽  
Haichen Li ◽  
Yu Tian ◽  
Yunzhong Jiang
Keyword(s):  
Optimal Operation ◽  
Hydropower Station ◽  
Operation Model ◽  
Multi Objective

Two-stage stochastic optimal operation model for hydropower station based on the approximate utility function of the carryover stage

Energy ◽  
2019 ◽  
Vol 183 ◽  
pp. 670-682 ◽  
Author(s):  
Qiao-feng Tan ◽  
Xiao-hui Lei ◽  
Xin Wen ◽  
Guo-hua Fang ◽  
Xu Wang ◽  
...  
Keyword(s):  
Utility Function ◽  
Optimal Operation ◽  
Hydropower Station ◽  
Operation Model ◽  
Two Stage

scholarly journals Multi-objective optimal operation of reservoir group in Jialing River based on DREAM algorithm

2021 ◽  
Author(s):  
Wei Diao ◽  
Peiyi Peng ◽  
Chunze Zhang ◽  
Shuqing Yang ◽  
Xujin Zhang
Keyword(s):  
Water Supply ◽  
Optimal Operation ◽  
Evaluation Index System ◽  
Operation Model ◽  
Evaluation Indexes ◽  
Multi Objective ◽  
Operation Rules ◽  
Jialing River ◽  
Group Water ◽  
Actual Operation

Abstract With the implementation of the most stringent water resources management system and the advancement of the construction process of reservoir terrace basins, the research and application of the theory and method of joint operation of reservoir groups are becoming more and more important. The Differential Evolution Adaptive Metropolis (DREAM) algorithm is a sampling algorithm based on the Markov Chain Monte Carlo method proposed in recent years. The algorithm satisfies ergodicity and is good at handling problems with multivariate nonlinearity, high dimensionality, and multi-peaks, and as such the algorithm is a new global optimization solution. This paper elaborated the solution mechanism of the standard DREAM algorithm, and the algorithm was applied to the optimal operation model of the reservoir group in Jialing River. First, we optimized and analyzed the multi-objective supply operation model of the reservoir group water in Jialing River. Then the multi-attribute decision-making and evaluation index system of water supply operation rules for the reservoir group to assess the optimization of the operation model was adopted. Finally based on the results of the evaluation, the best water supply operation scheme for the reservoir group of Jialing River was selected. The results show that the Baozhusi Reservoir can fully meet the planned water supply requirements in dry years, while the two reservoirs, Shengzhong and Tingzikou, need to be weighed against the evaluation indexes of water supply operation. The research provides a theoretical basis for the DREAM algorithm in the optimal operation of the reservoir group and the actual operation scheme for the reservoir group of Jialing River.

The Optimal Operation of Super High Head Hydropower Station with Multiple Water Supply Modes

2014 ◽  
Vol 492 ◽  
pp. 536-543
Author(s):  
Rong Yong Ma ◽  
Jia Li Lin ◽  
Li Song ◽  
Xiao Chen Xie
Keyword(s):  
Power Generation ◽  
Water Supply ◽  
Electric Energy ◽  
High Water ◽  
Economic Benefits ◽  
Optimal Operation ◽  
Hydropower Station ◽  
Operation Model ◽  
Power Station ◽  
Small Change

In order to improve the power generation benefit of the Tianhu Hydropower Station, a optimal operation model of the water supply system of the power station is built to maximize the gross electric energy generated. The model takes into consideration that Tianhu Hydropower Station has multiple water supply modes and is characterized by its super-high water head, and that any small change on flow control may bring great impact on the output of the power station. Based on existing hydrological data and the optimal scheduling model, the optimized results are calculated and made to optimization curves. These optimization curves are used to guide the operation of the hydropower station. Years of actual practices demonstrated that operating Tianhu Hydropower Station under the guidance of the optimal reservoir group operation model presented in this paper has brought in significant economic benefits, with an annual increase in power generation income of more than eight million yuan.

scholarly journals Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 625
Author(s):  
Xinyu Wu ◽  
Rui Guo ◽  
Xilong Cheng ◽  
Chuntian Cheng
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Large Scale ◽  
Simulation Optimization ◽  
Optimal Operation ◽  
Stochastic Dynamic ◽  
Operation Model ◽  
Two Stage ◽  
Operation Rules ◽  
Reservoir Systems

Simulation-optimization methods are often used to derive operation rules for large-scale hydropower reservoir systems. The solution of the simulation-optimization models is complex and time-consuming, for many interconnected variables need to be optimized, and the objective functions need to be computed through simulation in many periods. Since global solutions are seldom obtained, the initial solutions are important to the solution quality. In this paper, a two-stage method is proposed to derive operation rules for large-scale hydropower systems. In the first stage, the optimal operation model is simplified and solved using sampling stochastic dynamic programming (SSDP). In the second stage, the optimal operation model is solved by using a genetic algorithm, taking the SSDP solution as an individual in the initial population. The proposed method is applied to a hydropower system in Southwest China, composed of cascaded reservoir systems of Hongshui River, Lancang River, and Wu River. The numerical result shows that the two-stage method can significantly improve the solution in an acceptable solution time.

Synergistic gains from the multi-objective optimal operation of cascade reservoirs in the Upper Yellow River basin

2015 ◽  
Vol 523 ◽  
pp. 758-767 ◽  
Author(s):  
Tao Bai ◽  
Jian-xia Chang ◽  
Fi-John Chang ◽  
Qiang Huang ◽  
Yi-min Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Optimal Operation ◽  
Cascade Reservoirs ◽  
Multi Objective ◽  
Upper Yellow River ◽  
Synergistic Gains
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