Research On Day-ahead Optimal Dispatch Of Micro Grid Included In Battery

Electric energy is one of the indispensable energies of modern human beings,and the traditional power generation methods,including thermal power generation,will produce a large number of environmental pollution gases,which goes against the concept of green development proposed in the new era.Therefore,the micro grid with renewable energy as the main way of generating power has been widely concerned.Micro Grid(MG)is a unified and controlled Micro Grid system consisting mainly of clean energy power generation equipment and supplemented by other power generation equipment.Due to the freedom and diversity of equipment units,the bundle of energy supply at the load end has important social value for the renewal and progress of the micro grid.This paper mainly studies the optimization of the economic benefits of power supply equipment under the grid-connected mode.Considering that wind power generation and photovoltaic power generation have intermittent and fluctuating characteristics,they are the main power supply forms of micro grid.The thesis starts from two perspectives.First,the uncontrollable green energy generation mechanism is regarded as a stable output source without considering the floating of new energy.Secondly,the potential errors between the predicted data of the green power generation mechanism and the actual measured parameters are fuzzy treated with the non-parametric confidence interval estimation method,and then the objective optimization is carried out,and the optimization results under the two models are compared.Based on this,this paper mainly studies the economic optimization of micro-grid,and the main research contents are as follows:(1)Describes the characteristics of each energy output mechanism and constructs relevant mathematical expressions,providing a theoretical basis for economic operation research.The objective function and constraint function of economic optimal dispatch were constructed by taking the time-of-use price of power purchase and the price of electricity sold to the power grid,the charge-discharge characteristics and cost of battery,the effect of starting and stopping of diesel generator on output and pollutant emission.(2)Under the deterministic optimization model,a new Dragonfly algorithm(DA)and a non-dominated Sorting Genetic algorithm ?(NSGA-II)are adopted in this paper to optimize under specific practical cases to maximize the benefits of the micro-grid system.According to the comparison of power generation costs optimized by the two algorithms in this paper,DA is more economically efficient than NSGA-? in the deterministic optimization model.(3)In the case of certain errors between the predicted data of wind,light and load and the actual monitoring data,this paper proposes a non-parametric confidence interval fuzzy estimation method to establish a stochastic optimization model.When the lower limit of confidence interval is 0.8,NSGA-II and the objective function under DA optimization interval are used.By comparing the results of examples,it is found that the optimization results of the two algorithms in random model optimization are more economical than that of the deterministic model.