Micro-power-grid scheduling method based on quantum-behaved particle swarm optimization

Abstract

The invention discloses a micro-power-grid scheduling method based on quantum-behaved particle swarm optimization. The invention aims at a grid-connected wind and light storage micro power grid power balance constraint problem. Currently, a penalty term is added in a target function; the penalty term is added in a corresponding target function value of particles deviating power balance so that a function value is increased; and through algorithm optimization, the particles are filtered. In this case, a quantity of the particles is reduced and searching performance of the algorithm is influenced. In the invention, a storage battery is taken as a direct optimization variable and microgrid and large power grid exchanging power is taken as an indirect optimization variable; through the above mode, particle dimensions are reduced; reinitialization and loop iteration are performed on particles which do not satisfy a charged state constraint and particles which do not satisfy a large power grid exchanging power constraint so that the searching performance of the particles is guaranteed and a convergence speed can be correspondingly increased.

Description

technical field [0001] The invention belongs to the technical field of micro-grids, and in particular aims at the optimal scheduling of wind-solar-storage grid-connected micro-grids, and relates to a micro-grid scheduling method based on quantum behavior particle swarm algorithm. Background technique [0002] The microgrid is composed of various DGs (distribution generation), energy storage units, loads, and control and protection systems. By coordinating each DG, it provides power or heat load requirements for a community or island. The technical characteristics of the microgrid make it suitable for Some outlying areas are powered. As a typical microgrid, the grid-connected wind-solar-storage microgrid has great room for development in the future. During grid-connected operation, due to the implementation of peak and valley electricity prices in the large power grid, this allows the grid-connected microgrid to start at low electricity prices. The large grid purchases elect...

AI Technical Summary

Problems solved by technology

The microgrid optimal scheduling problem is a multi-dimensional nonlinear optimization problem. It is difficult to apply the traditional optimal solution method by solving equations to solve the microgrid optimal scheduling problem.

In addition, the prematurity and non-convergence of stochastic intelligent algorithms also bring certain difficulties to the solution of multi-dimensional nonlinear problems, and the global search ability and local search ability of the algorithm also have a certain impact on the optimization of nonlinear problems. And how to balance the two to make the algorithm suitable for practical problems is also a problem that needs to be studied at present.

Images