Revenue Optimization For Micro-grid Systems Based On Monte Carlo Simulation And Bio-inspired Algorithm

The concept and applications of micro-grid have attracted wide concern in applications owing to its unique nature.Micro-grid is a relatively concept of large traditional power grid,it is network of a number of distributed power supply and its related load in a certain topology.A micro-grid consists of distributed power like wind power,photovoltaic power,energy storage,diesel generator,and user loads in the given area.The rapid development of the micro-grid accelerates the application trend of multi-microgrid systems,and it is of great significance to study the optimal allocation of multi-microgrid systems.The energy storage is an essential module in micro-grid,and is usually used to smooth the user load and improve the power supply reliability and power quality.Thus it is necessary to study the characteristics of different types of energy storage devices considering the economic factor in energy systems.First,this thesis introduces the current research status and development trend of the micro-grid,multi-microgrid,and Monte Carlo algorithm.The basic principles and mathematical model of the multi-microgrid system are analyzed in detail,and this lays theoretical foundation for the following research on the hybrid system optimization.Second,the basic principles and flow of the Monte Carlo method and Fruit Fly optimization algorithm are introduced.Considering the simplicity merit of the Monte Carlo method in simulating the complex experiment process and the great robustness and high computational efficiency of the Fruit fly optimization algorithm,this thesis blends the two methods to simulate the charging and discharging process of the energy storage device in the micro-grid system with calculating the upper boundary of revenue.The objective function is set to maximize the energy storage revenue,while the economic revenue is analyzed and modeled based on the charging and discharging characteristics.Similarly,the upper boundary of revenue is calculated based on the parameters of various energy storage devices and the spot market price of electricity.Besides,the operation strategy and economy of three typical energy storage devices are analyzed.The results show that the economic revenues of lead-acid batteries are the biggest for the micro-grid operation period.Correspondingly,according to the characteristics of the off-grid micro-grid energy storage device,a suitable energy storage device is selected for the revenue analysis of the off-grid multi-microgrid.Third,the improved Monte Carlo method is introduced.Considering the fact that parallel Monte Carlo simulations are preferable owing to the better time index for optimization in existing financial and engineering fields,this thesis blends the MC-FOA with parallelization mechanism to solve the optimal allocation of each module in the multi-microgrid system.Based on the reliability and economic indexes,an optimization model of the line power control is established.The model calculates the overall minimum cost of multi-microgrid system by using the parallel MC-FOA and the forecasting data of distributed generation and user loads.By adjusting the capacity of diesel generators and lines,together with controlling the failure rate of the energy storage device,the system can be optimized in configuration,with more stable operation of power supply and higher system revenues.The contributions and potential issues of this work are summarized and presented.