DocumentCode :
2895881
Title :
Transmission network planning with N-1 security criterion based on improved multi-objective genetic algorithm
Author :
Wei, Huang ; Feng Li ; Zijun, He ; Junzhao, Cui ; Li, Zhang
Author_Institution :
Inst. of Power Transm. & Distrib. Syst., North China Electr. Power Univ., Beijing, China
fYear :
2011
fDate :
6-9 July 2011
Firstpage :
1250
Lastpage :
1254
Abstract :
Transmission network expansion planning is an essential part of power system planning, and as a multi-objective optimization programming problem, it is often turned into single objective programming problem to analyze home and abroad presently, and then plenty of methods can be applied in sovling the single objective programming problem. However, in this transformation process many human factors will inevitably be mixed into it to some extent and conflicting goals are often hard to reconcile, so that the solution which satisfies the single objective is easy to fall into local optimum and hard to achieve balance between the original objectives. In this paper, application of Pareto multi-objective genetic algorithm, which has rised in recent years, in transmission network expansion planning is proposed so as to reconcile the conflicting goals in transmission network expansion planning. With the advantage of this algorithm the "N-1" security criteria is considered as one of the objectives in the form of the penalty function to meet with the high reliability requirements of transmission network. In addition, the elites saving strategy is introduced into the multi-objective genetic algorithm in this paper to not only avoid the loss of outstanding individuals but also improve the convergence speed. Furthermore, to reduce the number of iterations and improve computational efficiency, fault ordering method is successfully adopted in "N-1" security check. Finally, IEEE Garver-6 system is simulated and the results reveal that the solution can be acquired in one step optimization and satisfy the“N-1”security criterion of transmission network when “N-1”is taken into account as an objective; and the Pareto multi-objective genetic algorithm in this paper can provide the optimal solution based on balanced multiple objectives compared to traditonal single objective genetic algorithm.
Keywords :
Pareto optimisation; genetic algorithms; power system security; power transmission faults; power transmission planning; power transmission reliability; IEEE Garver-6 system; N-1 security criterion; Pareto optimization; fault ordering method; multiobjective genetic algorithm; multiobjective programming; power system planning; transmission network planning; transmission network reliability; Genetic algorithms; Pareto optimization; Planning; Power systems; Programming; Security; “N-1” security criterion; Pareto Optimality; genetic algorithm; multiple objectives; transmission network planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
Conference_Location :
Weihai, Shandong
Print_ISBN :
978-1-4577-0364-5
Type :
conf
DOI :
10.1109/DRPT.2011.5994087
Filename :
5994087
Link To Document :
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