Reactive Power Optimization Method of Power System Based on Clone-Particle Swarm Hybrid Algorithm

Abstract

The invention relates to a method for reactive power optimization of an electric power system on the basis of a clone-particle swarm hybrid algorithm. The method comprises the following steps of: solving a trend by adopting a Newton-Laphson algorithm; superimposing network losses of each branch to obtain the network losses of a whole system; and introducing a clonal operator of a clonal algorithminto a standard particle swarm algorithm. The clone-particle swarm hybrid algorithm has stronger capacity of searching the globally optical solution; and compared with a method for the reactive poweroptimization of the electric power system on the basis of the standard particle swarm algorithm, the method for the reactive power optimization of the electric power system on the basis of the clone-particle swarm hybrid algorithm obtains a smaller system network loss value, and can reduce the running cost of an electric network to a greater degree.

Description

technical field [0001] The invention relates to a power system control method, in particular to a power system reactive power optimization method based on a clone-particle swarm hybrid algorithm. Background technique [0002] The disordered flow of reactive power flow in the power system will increase the active power loss of the system. Optimizing the allocation and control of reactive power can improve the system voltage quality, reduce active power loss, save operating costs, and achieve the goal of "energy saving and emission reduction". Purpose. Commonly used reactive power / voltage regulation methods include generator voltage, transformer tap position, shunt capacitor group switching group number, etc. By adjusting the voltage of the generator, the gear position of the transformer tap, and the number of switching groups of parallel capacitor banks, under the conditions of satisfying various constraints of the system operation, the optimal configuration of reactive powe...

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Problems solved by technology

[0004] Although the standard particle swarm optimization algorithm is easy to implement and can achieve a certain optimization effect in reactive power optimization problems, in this algorithm, the particles are easy to fall into the local optimal solution, and once trapped in the local optimal solution, it is difficult to jump out, which is not conducive to finding A more ideal global optimal solution cannot achieve a better effect of reducing network loss

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