Load Peaking Method And Dynamic Control Strategies For Microgrids With Hydro-wind-solar-storage Energy

With the continuous exhaustion of traditional fossil energy,in order to ensure the long-term stable supply of electricity,the power grids of many countries are incorporated into a large number of renewable energy,so that the peak-valley difference of the power grid increased a lot,which has an impact on the operation of power system.Micro grid is an important way to consume renewable energy,which transfers the peak load-regulating pressure generated by the consumption of renewable energy to the micro grid,which brings great challenges to the auxiliary services such as peak regulation and standby.Therefore,it is necessary to put forward a new load peaking method with source-load coordination and corresponding dynamic control strategy in microgrid.In this paper,the load peaking method and dynamic control strategy of hydro-wind-solar-storage microgrid are studied,and the main work is summarized as follows:(1)In order to explore the influence of distributed power supply and demand-side resources on the peak regulation and dispatching mode of microgrid,the paper analyzes the output and peak-regulating characteristics.In power-side resources,both hydropower generation and energy storage devices have good peak-regulating characteristics,while wind power generation and solar power generation need peak-regulating power to adjust their peaks.In demand-side resources,peak-valley time-of-use electricity price and load reduction management can effectively guide users to change the power consumption mode,and can cooperate with each other to jointly improve the effect of peak load cutting and valley filling in response to demand-side response,relieving the peak load adjustment pressure of power system.(2)To solve peak load pressure form micro power grid with high penetration of renewable energy,the paper puts forward a kind of peak-load regulation mode with source-load coordination for hydro-wind-solar-storage microgrid and corresponding multi-objective peak-shaving resource control model,which combine small hydropower,wind turbines and photovoltaic cells by means of energy storage to improve the stability and controllability of output power and reduce the peak-valley difference of equivalent load of micro-grid.At the same time,the model takes load reduction and interruptible loads into control,so that the power side and load side of the microgrid can participate in peak adjustment together,and further enhance the peak adjustment ability of the microgrid.An improved nsga-2 algorithm was used to solve the model.Economically,the peaking cost of the source-load peak regulation mode of the complementary micro grid is 38.88% lower than that of thenon-complementary micro grid,and 28.52% lower than the traditional peak regulation mode of the complementary micro grid.In terms of peak-shaving effectiveness,its peak-valley difference is 16.45% lower than the source-load peak regulation mode of non-complementary microgrid,and 27.98% lower than the traditional peak regulation mode of complementary microgrid,which verifies the rationality and effectiveness of the proposed peak regulation mode and the improved algorithm.(3)Considering the prediction errors of wind output,solar output and system load,the paper proposes a multi-time-scale dynamic control strategy of peak-shaving resources based on the proposed peak regulation mode,and constructs corresponding multi-time-scale peak-shaving resource dynamic control model.With the real-time data from advanced metering infrastructure and the result of day-ahead and intraday optimization results,the strategy individually optimized for a short period of time and control peak-shaving resources to track prediction errors of output and load dynamically,which can give full play to the rapid response ability of source-load peak regulation mode,meet dynamic peak regulation demand of hydro-wind-solar-storage microgrid,reduce the peak-valley difference of equivalent load and save the cost of peak shaving.The improved nsga-2 algorithm was used to solve the model.Economically,the peak-shaving cost of the multi-time-scale dynamic control strategy is 11.72% lower than that of the day-ahead time-scale control strategy,and its peak-valley difference is 10.87% lower than that of the day-ahead time-scale control strategy in terms of peak-shaving effectiveness,which verifies the rationality and effectiveness of the proposed dynamic control strategy of peak-shaving resources.