Research On Peak Cutting And Valley Filling Technology Based On Flexible Interconnected Distribution Network

With the continuous increase of controllable loads such as distributed power supply and electric vehicles,in order to meet users' urgent needs for environmental protection,power supply reliability,power quality,and quality services,a multi-layer ring network,AC/DC hybrid flexibility Interconnected power distribution networks and microgrid-based multiple power supply will be the main form of future power distribution networks.The construction of domestic power grids is ahead of the demand for existing load development,making the average load rate and utilization rate of power distribution equipment relatively low;at the same time,the feeder load is extremely uneven in spatial distribution and the load difference between peaks and valleys is large.On the basis of the introduction of large-capacity energy storage equipment,the use of flexible interconnected power electronic switches to improve the controllability of the distribution network and the ability to absorb renewable energy is a hot topic in the current research of distribution networks.This article takes the peakcutting and valley-filling technology based on flexible interconnected distribution network as the research object,constructs a peak-cutting and valley-filling model that takes into account the randomness of renewable energy and the storage capacity configuration,and conducts research on related optimization algorithms.The specific research content as follows:1.Based on the analysis of the power supply structure of the flexible interconnected distribution network,a stochastic output probability model of renewable power sources such as wind/light is established;taking into account the continuous net load curve,a minimum energy storage model based on stochastic production simulation is established;A random output probability model and a minimum energy storage model for regenerative power sources,and a multi-objective economic optimization model based on flexible interconnected distribution networks is established by considering the peak-cutting and valley-filling indicators and economic operation indicators.2.Using the normalization method,the peak-cutting and valley-filling optimization objectives and economic operation optimization objectives are dimensionlessly processed,and the weight coefficient method is introduced to convert the multi-objective optimization model into a single-objective optimization model;the dynamic optimization inertia weight and small probability are introduced A method of mutative secondary optimization,a particle swarm optimization algorithm to prevent local optimization from being used to solve a multi-objective economic optimization model based on flexible interconnected distribution networks,and a detailed algorithm flow is given.The random output probability of the wind/light unit is analyzed,and the minimum energy storage capacity is optimized based on the stochastic production simulation.According to the different weight coefficients,the rationality and effectiveness of the multi-objective economic optimization results of the flexible interconnected distribution network under the three scenarios of load curve peak valley difference optimization,economy optimization and trade-off optimization are verified and analyzed.3.Use Pareto's external archive maintenance and congestion ordering strategy to optimize the MOPSO algorithm to solve the Pareto optimal solution set of the abovementioned peak-cut and valley-filling economic optimization model.Compare the Pareto front-line verification optimization strategy before and after improvement to the Pareto optimal solution set diversity and convergence.Then,the fuzzy membership function analysis method is used to solve the optimal compromise solution on the Pareto front,and the scheduling results of the working conditions under different weights are compared with other solutions on the Pareto front.Grain filling indicators and economic indicators can be well balanced.