Particle Swarm Optimization Solving Nonlinear Programming Problems in Power System

Abstract:

In order to improve the control capability of the power system voltage stability and to enhance spatial and temporal coordination of voltage control means, it is essential to establish the model of emergency voltage control that can globally mobilize reactive power support and voltage control potential. Focus on the long-term voltage stability of power system, the paper introduce nonlinear programming into emergency voltage control, settle the problem that how to establish the model of emergency voltage control. Based on detailed models of power system, the receding optimization model of long-term voltage stability control is established under framework of model predictive control. In order to improve the computational efficiency and reduce feedback delays, nonlinear programming sensitivity algorithm is proposed to solve receding optimization model. The proposed method can improve computational efficiency significantly which creates the condition for the emergency voltage control application to large-scale systems.

• Periodical: Advanced Materials Research (Volumes 760-762)
• Pages: 1183-1186
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.760-762.1183
• Online since: September 2013
• Authors: Li Kang, Xiao Guang Li
• Keywords: Multi-Objective Optimization (MOP), Nonlinear Programming, Particle Swarm Algorithm, Power System

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