scholarly journals Optimal operation of reservoir systems with the symbiotic organisms search (SOS) algorithm

2017 ◽  
Vol 19 (4) ◽  
pp. 507-521 ◽  
Author(s):  
Omid Bozorg-Haddad ◽  
Ali Azarnivand ◽  
Seyed-Mohammad Hosseini-Moghari ◽  
Hugo A. Loáiciga
Keyword(s):  
Optimization Problem ◽  
Water Cycle ◽  
Optimal Solution ◽  
Global Optimum ◽  
Optimal Operation ◽  
Symbiotic Organisms Search ◽  
Water Cycle Algorithm ◽  
Reservoir Optimization ◽  
Reservoir Systems ◽  
Symbiotic Organisms

This work introduces the symbiotic organisms search (SOS) evolutionary algorithm to the optimization of reservoir operation. Unlike the genetic algorithm (GA) and the water cycle algorithm (WCA) the SOS does not require specification of algorithmic parameters. The solution effectiveness of the GA, SOS, and WCA was assessed with a single-reservoir and a multi-reservoir optimization problem. The SOS proved superior to the GA and the WCA in optimizing the objective functions of the two reservoir systems. In the single reservoir problem, with global optimum value of 1.213, the SOS, GA, and WCA determined 1.240, 1.535, and 1.262 as the optimal solutions, respectively. The superiority of SOS was also verified in a hypothetical four-reservoir optimization problem. In this case, the GA, WCA, and SOS in their best performance among 10 solution runs converged to 97.46%, 99.56%, and 99.86% of the global optimal solution. Besides its better performance in approximating optima, the SOS avoided premature convergence and produced lower standard deviation about optima.

Optimal operation of reservoir systems using the Wolf Search Algorithm (WSA)

2019 ◽  
Vol 19 (5) ◽  
pp. 1396-1404 ◽  
Author(s):  
Edris Ahmadebrahimpour
Keyword(s):  
Genetic Algorithm ◽  
Water Resources Management ◽  
Simple Structure ◽  
Search Algorithm ◽  
Global Optimum ◽  
Optimal Operation ◽  
Resources Management ◽  
Reservoir System ◽  
Hydropower Plants ◽  
Reservoir Systems

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.

scholarly journals Introducing modified version of penguins search optimization algorithm (PeSOA) and its application in optimal operation of reservoir systems

2017 ◽  
Vol 18 (4) ◽  
pp. 1484-1496 ◽  
Author(s):  
Afshin Mansouri ◽  
Babak Aminnejad ◽  
Hassan Ahmadi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Real World ◽  
Global Optimum ◽  
Optimal Operation ◽  
The Other ◽  
Reservoir System ◽  
Search Optimization ◽  
Real World Problem ◽  
Reservoir Systems

Abstract In the current study, modified version of the penguins search optimization algorithm (PeSOA) was introduced, and its usage was assessed in the water resources field. In the modified version (MPeSOA), the Gaussian exploration was added to the algorithm. The MPeSOA performance was evaluated in optimal operation of a hypothetical four-reservoir system and Karun-4 reservoir as a real world problem. Also, genetic algorithm (GA) was used as a criterion for evaluating the performance of PeSOA and MPeSOA. The results revealed that in a four-reservoir system problem, the PeSOA performance was much weaker than the GA; but on the other hand, the MPeSOA had better performance than the GA. In the mentioned problem, PeSOA, GA, and MPeSOA reached 78.43, 97.46, and 98.30% of the global optimum, respectively. In the operation of Karun-4 reservoir, although PeSOA performance had less difference with the two other algorithms than four-reservoir problem, its performance was not acceptable. The average values of objective function in this case were equal to 26.49, 23.84, and 21.48 for PeSOA, GA, and MPeSOA, respectively. According to the results obtained in the operation of Karun-4 reservoir, the algorithms including MPeSOA, GA, and PeSOA were situated in ranks one to three in terms of efficiency, respectively.

Optimal Operation of Multireservoir Systems by Enhanced Water Cycle Algorithm

2019 ◽  
Vol 7 (1) ◽  
pp. 27-43
Author(s):  
Yanjun Kong ◽  
Yadong Mei ◽  
Weinan Li ◽  
Ben Yue ◽  
Xianxun Wang
Keyword(s):  
Water Cycle ◽  
Water System ◽  
System Size ◽  
Optimal Operation ◽  
Test Functions ◽  
Water Cycle Algorithm ◽  
Adaptive Parameter ◽  
Fitness Value ◽  
Better Than

In this article, an enhanced water cycle algorithm (EWCA) is proposed and applied to optimize the operation of multireservoir systems. Three improvements have been made to the water cycle algorithm (WCA). They refer to high-quality initial solutions obtained by the chaos-based method, balancing of exploration of streams using a dynamic adaptive parameter, and dynamic variation of sub-water system size using the fitness value of rivers. For the purpose of verifying the improvements, three typical benchmark functions were selected as test functions. It has shown that EWCA performs better than WCA and water cycle algorithm with evaporation rate (ER-WCA). And then these three algorithms were also applied to optimize the operation of a multireservoir system with complex constrains as the case study. By comparing the results, it is found that the EWCA has higher ability to find a feasible solution in a narrow searching space. The effectiveness of the improvements is confirmed.

scholarly journals Optimal operation of multi-reservoir systems: comparative study of three robust metaheuristic algorithms

2020 ◽  
Author(s):  
Saeid Akbarifard ◽  
Mohammad Reza Sharifi ◽  
Kourosh Qaderi ◽  
Mohamad Reza Madadi
Keyword(s):  
Harmony Search ◽  
Imperialist Competitive Algorithm ◽  
Complex Problem ◽  
Global Optimum ◽  
Optimal Operation ◽  
Metaheuristic Algorithms ◽  
Reservoir System ◽  
Optimal Value ◽  
Reservoir Systems ◽  
Cpu Usage

Abstract In this study, the capability of recently introduced Moth Swarm Algorithm (MSA) was compared with two robust meta-heuristics of harmony search (HS) algorithm and imperialist competitive algorithm (ICA). First, the performance of these algorithms was assessed by seven benchmark functions having 2–30 dimensions. Next, they were compared in optimization of complex problem of 4-reservoir and 10-reservoir systems operation. Furthermore, the results of these algorithms were compared with nine other metaheuristic algorithms developed by several researchers. Sensitivity analysis was performed to determine the appropriate values of the algorithms parameters. The statistical indices of R2, RMSE, MAE, MSE, NMSE, MAPE, and Willmott's index of agreement were used to compare the algorithms performance. The results showed that the MSA was the superior algorithm in solving all benchmark functions in terms of obtaining the optimal value and saving the CPU usage. ICA and HS were placed in the next orders, respectively. It was found that by increasing the dimensions of the problem, the performance of ICA and HS dropped but the MSA has still performed extraordinary. In addition, the minimum CPU usage and the best solutions for optimal operation of four-reservoir system were obtained by MSA algorithm with values of (269.7s and 308.83) which are very close to the global optimum solution. Corresponding values for ICA and HS were (486.73, 306.47) and (638.61s, 264.61) respectively, which put them in the next ranks. Similar results were observed for ten-reservoir system; the CPU time and optimal value obtained by MSA were (722.5s, 1,195.58) while for ICA and HS were (1,421.62s, 1,136.22) and (1,963.41s, 1,060.76), respectively. The values of R2 and RMSE achieved by MSA were (0.951, 0.528) and (0.985, 0.521) for 4-reservoir and 10-reservoir systems which demonstrated the outstanding performance of this algorithm in optimal operation of multi-reservoir systems. In a general comparison, it was concluded that among the twelve investigated algorithms, MSA was the best, and it is recommended as a robust promising tool in optimal operation of multi-reservoir systems.

Optimal operation of multi-reservoirs by water cycle algorithm

2018 ◽  
Vol 171 (4) ◽  
pp. 179-190 ◽  
Author(s):  
Kourosh Qaderi ◽  
Saeid Akbarifard ◽  
Mohamad Reza Madadi ◽  
Bahram Bakhtiari
Keyword(s):  
Water Cycle ◽  
Optimal Operation ◽  
Water Cycle Algorithm
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