Research On Optimal Dispatch Of Microgrid Segmented Hybrid Strategy Considering Power Quality Coefficient

The uncertainty of distributed energy output will have a certain impact on the power grid.Researches at home and abroad generally use energy storage devices to stabilize power quality and store power.However,the scale of the energy storage system expands with the expansion of the scale of distributed energy,and the construction cost of the microgrid project also increases.In order to ensure the economic efficiency of microgrid operation and user satisfaction,this paper combines photovoltaic output characteristics and demand response,and proposes a segmented hybrid strategy that takes into account the high-quality coefficient of electricity consumption,and reduces energy storage devices through reasonable regulation of controllable loads.The equipment.The main content of the paper is as follows:1)In view of the fact that the existing user satisfaction model does not consider the different impacts of the load after the transfer due to the different power supply characteristics,an improved power quality coefficient model is proposed.The model uses different levels of load as the basic unit,and calculates the power quality coefficient including economy and comfort,according to the regulation conditions under various scheduling strategies,so that it is more in line with the actual power consumption situation,and is the best choice.The optimal scheduling strategy plays an important role.2)In order to achieve the goal of reducing the installation scale of energy storage devices without affecting reliable power supply,a segmented hybrid microgrid optimized dispatch strategy is proposed.The strategy includes a PVP&LS(photovoltaic priority & load shifting)segmented hybrid scheduling strategy.First,the PVP strategy adjusts the controllable load based on the predicted photovoltaic output to minimize the light-wasting rate;then the LS strategy reduces the peak-to-valley difference rate The purpose is to shift the peak and fill the valley of the remaining controllable load in the previous stage,and make full use of the demand response to increase the flexibility of the scheduling strategy.3)In order to avoid using traditional genetic algorithms to fall into local optimal solutions and affect the selection of optimal strategies,this paper uses dynamic crossover and mutation factors,and compares them with genetic algorithms to determine the feasibility and superiority of the method,And designed the visualization platform of the scheduling system.Finally,reasonable case parameters are set,and the traditional strategy,the segmented mixed scheduling strategy,the simulation of the power quality coefficient and the comparison of two different algorithms are carried out respectively.Through simulation and comparison,the optimization results show that the operating cost of the segmented hybrid scheduling strategy has been reduced by 12.72%,the power quality coefficient has increased by 7.59%,and the light abandonment rate has decreased by 10.2%.The rationality of the segmented mixed scheduling strategy and the power quality coefficient model is verified,and the improved IPM genetic algorithm has a better solution.