Reactive Power Optimization In Power System Based On Multi-agent Seeker Optimization Algorithm

With the rapid development of electric power system, the grids become larger and larger. How to guarantee the power system running economically, safely and stably become a focus in the world. The two standards of frequency and voltage is a measure of power systems stability, and the system voltage stability is usually achieved by regulating the reactive power balance Reactive power optimization is the basis of power system voltage and reactive power control and scheduling, it can take full advantage of the power system reactive power to improve the voltage quality, reduce network losses and improve voltage stability. Reactive power optimization is a discrete problem, there is a bound non-linear combinatorial optimization problem, in this area of research has a number of ways, and swarm intelligence optimization algorithm for its unique advantages to solve reactive power optimization of such large scale complex problems has provided new ways and means.A multi-agent seeker optimization algorithm (MASOA) is proposed for optimal reactive power dispatch and voltage control of power system which is a typical non-linear problem. According to the more arbitrary partition of neighborhood region for SOA, the algorithm has combined with agent technology and has increased the accuracy of particles optimization with improving the rationality of partition of neighborhood region for SOA. By adopting the evolutional mechanism of SOA to import adaptive method, it has been manifested that the novel algorithm has possessed good nonlinear search capability and has better effective for the optimization problem of reactive power.This paper introduces the present research and development of reactive power optimization. After researched kinds of methods for reactive optimization, the advantages and disadvantages and application of these methods are analyzed. A mathematical model based on the standard model for reactive power optimization is established to obtain minimization of networkloss with satisfying constraints of power flow and security. Generator voltage, transformer tap and capacitor tank forms initial matrix in reactive power optimal modeling. MASOA applied for optimal reactive power is evaluated on an IEEE 30 bus and an IEEE 57 bus power system. It is shown that the proposed approach converges to better solutions than the earlier four reported approaches and the algorithm can make effectively use in reactive power optimization.