A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm
| Autor: | Wanxing Sheng, Ke-yan Liu, Yongmei Liu, Xiaoli Meng, Xiaohui Song |
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| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | Journal of Applied Mathematics, Vol 2013 (2013) |
| Druh dokumentu: | article |
| ISSN: | 1110-757X 1687-0042 |
| DOI: | 10.1155/2013/643791 |
| Popis: | A distribution generation (DG) multiobjective optimization method based on an improved Pareto evolutionary algorithm is investigated in this paper. The improved Pareto evolutionary algorithm, which introduces a penalty factor in the objective function constraints, uses an adaptive crossover and a mutation operator in the evolutionary process and combines a simulated annealing iterative process. The proposed algorithm is utilized to the optimize DG injection models to maximize DG utilization while minimizing system loss and environmental pollution. A revised IEEE 33-bus system with multiple DG units was used to test the multiobjective optimization algorithm in a distribution power system. The proposed algorithm was implemented and compared with the strength Pareto evolutionary algorithm 2 (SPEA2), a particle swarm optimization (PSO) algorithm, and nondominated sorting genetic algorithm II (NGSA-II). The comparison of the results demonstrates the validity and practicality of utilizing DG units in terms of economic dispatch and optimal operation in a distribution power system. |
| Databáze: | Directory of Open Access Journals |
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