With the rapid development of Chinese economy, the power industry is playing a more and more important role in the development of Chinese economy. The optimal reactive power in the power system plays an important role...
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ISBN:
(纸本)9781538694909
With the rapid development of Chinese economy, the power industry is playing a more and more important role in the development of Chinese economy. The optimal reactive power in the power system plays an important role in the voltage stability of the power system and reducing the loss of active power. The calculation results of particle swarm optimization algorithm, oriented search algorithm and PSO - OSA hybrid algorithm in reactive power optimization of power system is compared, and the performance of the proposed method has been tested on the IEEE 30-bus systems in this paper. The simulation results show that the proposed method is able to produce well distributed Pareto optimal solutions for the optimal reactive power problem.
A population-based algorithm, oriented search algorithm (OSA), is proposed to optimize functions in this paper. In OSA, the search-individual imitates human random search behavior, and the search-object simulates an i...
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ISBN:
(纸本)9783642215155
A population-based algorithm, oriented search algorithm (OSA), is proposed to optimize functions in this paper. In OSA, the search-individual imitates human random search behavior, and the search-object simulates an intelligent agent that can transmit oriented information to search-individuals. OSA is tested on thirteen complex benchmark functions. The results are compared with those of particle swarm optimization with inertia weight (PSO-w), particle swarm optimization with constriction factor (PSO-cf) and comprehensive learning particle swarm optimizer (CLPSO). The results show that OSA is superior in convergence efficiency, search precision, convergence property and has the strong ability to escape from the local sub-optima.
A novel algorithm, called oriented search algorithm (OSA), is proposed to deal with reactive power optimization problem in the paper. The optimization objective is to minimize the active power losses while maintaining...
详细信息
ISBN:
(纸本)9787564112493
A novel algorithm, called oriented search algorithm (OSA), is proposed to deal with reactive power optimization problem in the paper. The optimization objective is to minimize the active power losses while maintaining acceptable voltage profiles. In OSA, the search-individual simulates human behavior, and the search-object (Le., the optimal solution of the objective functions) works like an intelligent agent that can transmit oriented information to search-individuals. In contrast to comprehensive learning particle swarm optimizer (CLPSO), the reactive power optimization results of IEEE-30 node system by OSA show that OSA has better convergence property, convergence precision and strong ability to escape from the local sub-optima. Moreover, the active power losses are decreased obviously.
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