Micro Grid Optimal Scheduling Based On Improved Particle Swarm Optimization

The world is facing the pressure of fossil energy crisis and environmental pollution,and countries around the world begin to focus on renewable clean energy such as wind energy and photovoltaic.Therefore,the micro grid technology is an important measure to use renewable energy for power generation.As a new generation system,micro grid is widely used because of its advantages of high energy efficiency,less feeder loss and high reliability of power supply.The construction of micro grid plays an important role in the construction of smart grid in the current power system.The main research contents are as follows:(1)Operation characteristics of wind,light,storage,micro-gas turbine and micro-grid fuel cell are analyzed,and corresponding mathematical models are established;Wind,light and load power prediction is the prerequisite for optimal system scheduling.In this paper,an improved prediction model is constructed for short-term power prediction of wind,light and load.Compared with the traditional model,the improved prediction model can improve the prediction accuracy.(2)The optimal operation of micro-grid is a multi-objective,multi-constraint and multi-variable nonlinear optimization problem.Intelligent algorithms have attracted much attention due to their advantages,such as particle swarm optimization and genetic algorithm.Among them,particle swarm optimization has the advantages of simplicity and good convergence.An improved particle algorithm is proposed to solve the problem of multi-objective particle swarm optimization.The results show that the solution set of the improved particle algorithm has better distribution and global search performance,and can determine the optimal solution.(3)For the grid-connected microgrid system,a functional model and constraints aiming at economic cost,environmental cost and system operation risk are established,and a scheduling strategy for grid-connected system operation is given.On the basis of the improved model to predict the short-term power data of wind,light and load,the improved particle algorithm is used to solve the model,and the effectiveness of the model is verified by an example simulation..