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Adaptive Particle Swarm Optimization Algorithm with Guiding Strategy for Reactive Power Optimization of Rural Power Grids

JIANG Feng-li;ZHANG Yu;WANG Hui;College of Information and Electrical Engineering, Shenyang Agricultural University;  
Particle swarm optimization(PSO) is widely used in reactive power optimization of rural power grids. However, it has disadvantages, for example it is easy to fall into local minima. The particle update modes and the inertia weight in the algorithm are the key factors that affect the search ability. An adaptive particle swarm algorithm with guiding strategy(GSAPSO) was proposed. The particle update modes and the inertia weight in the algorithm were the key factors that affect the search ability.An adaptive particle swarm algorithm with guiding strategy(GSAPSO) was proposed Four kinds of particles which were the main particles, double center particles, cooperative particles and chaos particles were introduced into the population of the algorithm through guiding particle position updating to decrease the randomness and improve search efficiency. Moreover, the cluster focus distance changing rate was introduced. The inertia weight was adjusted dynamically by the size of the focus distance changing rate, which was to improve the convergence speed and accuracy of the algorithm. The effectiveness of the search for the global optimal solution was greatly improved by the combination of the both modes. The algorithm was applied in IEEE 30-bus system,the optimal loss reduction rate could reach to 18.966%, the minimum node voltage was 1.0091 p.u., the iterations of optimal solution were 45 and the average iterations were 64.6. Compared with the PSO, wPSO and LDWPSO algorithm, the proposed GSAPSO was more efficient. Calculation results showed that higher quality solutions were obtained, convergence speed and accuracy were significantly higher with the proposed algorithm. It was meant that the proposed algorithm had better optimization ability and convergence performance than the other three kinds of algorithms.
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