Optimal Dispatch Of Microgrid Based On Improved Particle Swarm Algorithm

At present,with the development of economy,the demand for energy is increasing.New energy sources such as wind energy and solar energy have become the main sources of energy that can be used.These energy sources alone have very significant intermittent fluctuations.The power output is full when connected to the power system.Uncertainty is not conducive to full economic optimization and dispatching.Moreover,the cost of these uncertain distributed generators(DG)into the power system is also high.In order to solve the problems introduced by DG access to the power system,give full play to DG Output and realize economic operation,micro-grid is proposed,micro-grid can solve this problem well.The microgrid can combine uncontrollable energy,controllable energy,and energy storage,and realize power demand to participate in the operation of the power system through unified control,thereby realizing economically optimized operation.Therefore,in-depth research on the optimal dispatch strategy of microgrids is beneficial to the development of green grids,improving the energy utilization rate of distributed power sources connected to the power system,and at the same time conducive to environmental protection.This paper considers the problem of battery loss to carry out the research on microgrid dispatching.The specific research work is as follows:(1)Determination of the model of each unit of the microgrid.Microgrid systems generally include uncontrollable wind power units,controllable micro gas turbines and other units,as well as energy storage units.According to the selected microgrid structure,analyze the characteristics of each unit and construct the mathematical model of each energy unit in the microgrid system.(2)The establishment of a multi-objective micro-grid optimal dispatch model.Normally,considering the goals of economy,environment,and benefits,firstly,multiple goals based on the cost and environmental governance costs of power supply operation in the microgrid and the economic benefits of the microgrid system are established;secondly,the goals are fully analyzed based on the goals.Various boundary conditions that need to be met for function optimization operation,including power exchange constraints,energy storage device constraints,power balance constraints,power supply output power constraints,pollutant emissions,etc.;finally,considering the economy and environmental protection,the battery loss problem is considered,Established a multi-objective micro-grid optimal dispatch model.(3)Research on multi-objective optimization algorithms.First of all,analyze the multi-objective problem;then,select the multi-objective problem solving algorithm.Multi-objective optimization mostly uses artificial intelligence algorithms.This paper selects the particle swarm optimization algorithm for the microgrid optimization dispatching algorithm according to each intelligent algorithm.Considering that the basic particle swarm algorithm is easy to be locally optimized Advantages and disadvantages,the performance of the algorithm is improved by improving the inertia weight and particle velocity of the particle swarm algorithm.Finally,two classic functions are selected to test the performance of the improved particle swarm algorithm,and the multi-objective optimization steps of the improved particle swarm algorithm and the process of application in microgrid optimization are designed.The function simulation test results show that the performance of the improved particle swarm algorithm has been improved to a certain extent.(4)Analysis of calculation examples of micro-grid optimization dispatching.Based on the consideration of price factors,energy flow direction and battery loss model,four different simulation schemes are designed,and the improved particle swarm algorithm is used for optimal dispatch.The simulation results show that the improved particle swarm algorithm has good performance in the optimal dispatch of microgrid Performance...