Hamed Aliyari1 , Reza Effatnejad2 , Mehdi Izadi 3 and Seyed Hossein Hosseinian4
1Faculty of Electrical and Biomedical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2Department of Electrical Engineering, Karaj Branch, Islamic Azad University, Alborz, Iran
3Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran
4Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
Received:
June 27, 2016
Accepted:
January 9, 2017
Publication Date:
June 1, 2017
Download Citation:
||https://doi.org/ 10.6180/jase.2017.20.2.01
ABSTRACT
This paper presents a novel stochastic optimization approach to determine a feasible optimal solution for the economic dispatch (ED) problems, considering various generator constraints. Many practical constraints of generators, such as ramp rate limits and prohibited operating zones are investigated. In order to improve the performance of the particle swarm optimization (PSO) algorithm. These constraints alter the ED problem to a non-smooth minimization problem with constraints, an innovative approach based on PSO is chosen to solve the load-flow problem by combining the genetic algorithm (GA), i.e. some of the answers were found by the PSO algorithm itself; after that two possible procedures are studied: one is utilizing the PSO algorithm to find the optimum answer among the primary guesses and the other is using a GA implementation by means of the arithmetic crossover operators. The last step is choosing the best answer among the obtained results (GA, PSO). To show its efficiency and effectiveness, the proposed algorithm (GPSO) is applied to some types of ED problems containing non-smooth cost functions of 13 and 40 generating units systems (large scale systems). The experimental results show that the GPSO approach is comparatively capable to obtain higher quality solution.
Keywords:
Particle Swarm Optimization, Genetic Algorithm, Economic Load Dispatch, Stochastic Search Algorithm
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