Optimal Allocation of Water Resources Based on Differential Evolution Algorithm

Abstract: Differential evolution algorithm (differential evolution DE) is a multi-objective evolutionary algorithm based on groups， which instructs optimization search by swarm intelligence produced by co-operation and competition among individuals within groups. This paper presents it to the research of optimal allocation of water resources. Accord to the application of the example, the results shows that reasonable and effective.

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OPTIMAL ALLOCATION AND SIZING OF FACTS CONTROLLERS USING DIFFERENTIAL EVOLUTION ALGORITHM

Control and Intelligent Systems ◽

10.2316/journal.201.2013.3.201-2491 ◽

2013 ◽

Vol 41 (3) ◽

Author(s):

Vanitha Rajendran ◽

Sudhakaran Mahalingam

Keyword(s):

Differential Evolution ◽

Optimal Allocation ◽

Differential Evolution Algorithm ◽

Facts Controllers ◽

Evolution Algorithm

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Optimal Allocation of Multi-DG on Distribution System Reliability and Power Losses Using Differential Evolution Algorithm

Energy Procedia ◽

10.1016/j.egypro.2017.11.068 ◽

2017 ◽

Vol 141 ◽

pp. 512-516 ◽

Cited By ~ 6

Author(s):

Pathomthat Chiradeja ◽

Suntiti Yoomak ◽

Atthapol Ngaopitakkul

Keyword(s):

Differential Evolution ◽

System Reliability ◽

Distribution System ◽

Optimal Allocation ◽

Differential Evolution Algorithm ◽

Power Losses ◽

Evolution Algorithm ◽

Distribution System Reliability

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Water Resources Optimal Allocation Based on Multi-Objective Differential Evolution Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.278-280.1271 ◽

2013 ◽

Vol 278-280 ◽

pp. 1271-1274 ◽

Cited By ~ 2

Author(s):

Ke Peng Feng ◽

Jun Cang Tian

Keyword(s):

Water Resources ◽

Differential Evolution ◽

Optimal Allocation ◽

Search Algorithm ◽

Differential Evolution Algorithm ◽

Population Based ◽

Allocation Model ◽

Multi Objective ◽

Regional Water ◽

Water Resources Optimal Allocation

Differential evolution is a simple and powerful globally optimization new algorithm. It is a population-based, direct search algorithm, and has been successfully applied in various fields. Optimal allocation of water resources is an important part of the planning of water resources. Traditional planning methods prove insufficient for the multi-objective system of water resources. In this paper, multi-objective differential evolution(MODE) algorithm applied to the regional water resources optimal allocation, through definition of economic, social, Eco-environmental three objective function and the constraints, the regional water resources optimal allocation model has been established, and then multi-objective genetic algorithm is used to solve the model .The model gets different results for optimal allocation water resources of Ningxia in 2030(Guarantee rate of water supply 50% and 75%). The result of example proves that the method is reasonable and feasible in the application of region water resources optimal allocation.

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Developing a shuffled complex evolution algorithm using a differential evolution algorithm for optimizing hydropower reservoir systems

Water Science & Technology Water Supply ◽

10.2166/ws.2017.179 ◽

2017 ◽

Vol 18 (3) ◽

pp. 1081-1092 ◽

Cited By ~ 1

Author(s):

Omid Bakhtiari Nezhad ◽

Mohsen Najarchi ◽

Mohammad Mahdi NajafiZadeh ◽

S. Mohammad Mirhosseini Hezaveh

Keyword(s):

Water Resources ◽

Differential Evolution ◽

Differential Evolution Algorithm ◽

Mathematical Function ◽

Complex Issue ◽

De Algorithm ◽

Shuffled Complex Evolution ◽

Reservoir Systems ◽

Evolution Algorithm ◽

Hydropower Reservoir

Abstract The aim of this study is to improve the performance of the shuffled complex evolution (SCE) algorithm used in the optimization of hydropower generation in reservoirs as a complex issue in water resources. First, the SCE algorithm is merged with the differential evolution (DE) algorithm to form the SCE-DE algorithm. Then, a complex mathematical function is used as a benchmark to evaluate the performance and validate the SCE-DE algorithm and the outcomes are compared with the original SCE algorithm to show the superiority of the proposed SCE-DE algorithm. In addition, the two-reservoir system of Dez-Gotvand is considered as a real optimization problem to evaluate the performance of the SCE-DE algorithm. It is revealed that optimization by SCE-DE is much better than SCE. In conclusion, the results show that the proposed SCE-DE algorithm is a reasonable alternative to optimizing resource systems and can be used to solve complex issues of water resources.

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