Optimal Operation of Reservoir Systems Considering the Water Quality: Application of Stochastic Sequential Genetic Algorithms

Author(s):  
M. Karamouz ◽  
R. Kerachian
2021 ◽  
Vol 7 ◽  
pp. 3703-3725
Author(s):  
Mohammad Ehteram ◽  
Fatemeh Barzegari Banadkooki ◽  
Chow Ming Fai ◽  
Mohsen Moslemzadeh ◽  
Michelle Sapitang ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 625
Author(s):  
Xinyu Wu ◽  
Rui Guo ◽  
Xilong Cheng ◽  
Chuntian Cheng

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.


2017 ◽  
Vol 31 (14) ◽  
pp. 4505-4520 ◽  
Author(s):  
Seyed Mohammad Ashrafi ◽  
Alireza Borhani Dariane

Author(s):  
Alex Takeo Yasumura Lima Silva ◽  
Fernando Das Graças Braga da Silva ◽  
André Carlos da Silva ◽  
José Antonio Tosta dos Reis ◽  
Claudio Lindemberg de Freitas ◽  
...  

 Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using statistics and the design of experimental tools and software. The proposed technique was applied to a theoretical network developed for the study. Preliminary simulations were accomplished using EPANET, representing the main causes of water and energy inefficiency in Brazilian sanitation companies. Some parameters were changed in applying this model, such as reservoir level, pipe diameter, pumping pressures, and valve-closing percentage. These values were established by the design of experimental techniques. As output, we obtained the equation of response surface, optimized, which resulted in values of established hydraulic parameters. From these data, the obtained parameters in computational optimization algorithms were applied, resulting in losses of 26.61%, improvement of 16.19 p.p. with regard to the network without optimization, establishing an operational strategy involving three pumps and a pressure-reducing valve.  We conclude that the association of optimization and the planning of experimental techniques constitutes an encouraging method to deal with the complexity of water-distribution network optimization.


2019 ◽  
Vol 19 (5) ◽  
pp. 1396-1404 ◽  
Author(s):  
Edris Ahmadebrahimpour

Abstract Optimizing hydropower plants is complex due to nonlinearity, complexity, and multidimensionality. This study introduces and evaluates the performance of the Wolf Search Algorithm (WSA) for optimizing the operation of a four-reservoir system and a single hydropower system in Iran. Results indicate WSA could reach 99.95 and 99.91 percent of the global optimum for the four-reservoir system and single reservoir system, respectively. Comparing the results of WSA with a genetic algorithm (GA) also indicates WSA's supremacy over GA. Thus, due to its simple structure and high capability, WSA is recommended for use in other water resources management problems.


2015 ◽  
Vol 30 (2) ◽  
pp. 523-540 ◽  
Author(s):  
Wang Zhang ◽  
Pan Liu ◽  
Xizhen Chen ◽  
Li Wang ◽  
Xueshan Ai ◽  
...  

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