Determination of the Load Restoration Plans Based on Genetic Simulated Annealing Algorithms
Chen Xiaoping, Gu Xueping
Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control under Ministry of Education North China Electric Power University Baoding 071003 China
Abstract：The ultimate goal of system restoration after blackout is to restore load fully and rapidly. One of the most important things in load recovery is to control system frequency, and the effective method to keep the frequency stability is to control the balance between load recovery speed and the generator’s responses. A method using genetic simulated annealing algorithms is proposed for determination of load restoration plans on the basis of network reconfiguration, in which system frequency is calculated by extended power flow analysis and the various system constraints are treated by penalty functions. Through the calculation of the genetic group fitness, the optimal recovery path and the maximum load step can be determined. The efficiency and effectiveness of the proposed method are verified by the numerical results on the IEEE 30 and IEEE 118 systems.
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2009, Vol. 24 
