Intelligent Microgrid Multi-time Scale Scheduling Basing On Generation-load Interaction

With the continuous development of China's economy and science and technology,the increasing demand of electricity has resulted in the rapid consumption of fossil energy.Various types of renewable energy are constantly being developed,but the uncertainty of renewable energy makes it difficult to integrate into the microgrid on a large scale.With the continuous improvement of intelligent microgrid,the demand side load becomes a schedulable resource.How to use demand-side load and power-side resources for effective source-charge interaction is of great significance to the large-scale integration of renewable energy.Generation-load interaction can use the load characteristics of various distributed power sources and demand-side resources of the microgrid to reasonably formulate the output of various types of microgrid generators,and distributed power sources and demand-side loads have characteristics on different time scales.By analyzing generation-load side resources at different time scales and establishing microgrid multi-time-scale generation-load interactive scheduling,more effective scheduling strategies can be further formulated.This thesis focuses on the multi-time scale scheduling of microgrid and studies the following:Firstly,the microgrid structure including thermal power unit,gas turbine,wind power unit,incentive-based and price-based demand response load is given,and the output characteristic model of each micro source is established.Analyze the mechanism of incentive-based demand response and price-based demand response participating in microgrid scheduling under generation-load interaction.The principle of multi-time scale scheduling strategy and genetic algorithm are introduced.Secondly,a day-ago comprehensive dispatch model including electricity price optimization is proposed,and incentive-based and price-based demand response load models are established.Use historical data to calculate the user's baseline load,and introduce the predicted load to modify it.Using the revised baseline load and marginal benefits,the incentive-based demand response cost model is established.Based on the characteristics of price-based demand response affected by price,the load change law with the introduction of price elasticity coefficient is analyzed,and the price-guided cost modeling of forecasted load is established.Combined the established demand response cost models with the generation-side operating cost models to establish a microgrid integrated scheduling model basing on generation-load interaction,optimizing the output of microgrid distributed power sources,the amount of load reduction,and adjust the time-of-use electricity price of microgridThirdly,in day-intra scheduling,analyzing the time-scale characteristics of resources on both sides of the generation and load,considering the day-intra deviation of incentive demand response load solved by the day-ago dispatch and the power generation.,establish day-intra and real-time scheduling models to realize the real-time adjustment of microgrid distributed power output and load reductionFinally,the genetic algorithm is used to solve the different time scale scheduling models.The analysis results of the calculation example show that the day-ago scheduling can reduce the operating cost of microgrid,reduce energy consumption,and formulate effective time-of-use electricity prices;and that day-intra scheduling can optimize the scheduling results of the day-ago,and further develop the role of demand-side resources to ensure the accuracy of scheduling results.