Optimization method of electric power system

Abstract

The invention discloses an optimization method of an electric power system and relates to the technical field of electric power system reactive power optimization. The method includes the steps of (1)reading electric power system parameters and setting particle population parameters; (2) initializing the velocity and positions of population particles; (3) calculating load flow and fitness values;(4) calculating the dimensional diversity and inertia weight vectors; (5) performing iterative calculation and updating the velocity and position of a particle swarm; (6) calculating the load flow and the fitness values; (7) checking whether or not convergence conditions are satisfied; (8) determining whether or not an variation occurs; (9) performing a variability operation on a dimension the diversity of which is the worst. Through improvement of existing particle swarm optimization algorithms, the inertia weight vectors are introduced, the dimension diversity is calculated, dimension searching is refined, and the problem that the existing algorithms have a low convergence speed is solved. The active power network loss is effectively reduced, and a better global searching capability isachieved.

Description

technical field [0001] The invention belongs to the technical field of power system reactive power optimization, and in particular relates to an optimization method of a power system. Background technique [0002] With the rapid development of social economy, the load of the system is increasing day by day, the topological lines of the distribution network are becoming more and more complex, and the network loss of the distribution network is also increasing. Reasonable allocation of reactive power in the distribution network can balance the power flow distribution of the distribution network and reduce the network loss of the distribution network. , plays a vital role in stabilizing the voltage at the central load. [0003] Particle swarm optimization algorithm is an optimization algorithm for dealing with nonlinear optimization problems. It belongs to a kind of evolutionary algorithm. It has the advantages of fast convergence speed, simple calculation, high precision, and ...

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Problems solved by technology

[0004] The purpose of the present invention is to provide an optimization method for power systems. By improving the existing particle swarm optimization algorithm, the inertia weight vector and the diversity of calculation dimensions are introduced, the search of dimensions is refined, and the slow convergence speed of the existing algorithm is solved. problem; the present invention effectively reduces active network loss and has better global search capability

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