Peaking Capacity And Optimization Of Power Source-load Of Microgrids In Office And Resident Parks

With the rapid development of the economy and the rapid increase of people's material needs,the types of microgrid loads have continued to increase,the load power is increasing,the number of high-power loads has increased significantly,and the daily load change has gradually increased.Brings challenges to grid shaving.The microgrid can not only solve the local consumption of renewable energy,but also meet the needs of sufficient partial load,and has good economic benefits.Due to the rich load capacity and types,the problem of peak shaving in microgrids has also emerged.The use of “source-load” cooperative peak shaving to alleviate peak shaving pressure is a subject worthy of study,and the power grid and load peak shaving capabilities of microgrids It is the key content in the research of source-load coordinated peak regulation.In this paper,in the office and living parks,the research focuses on the "source-charge" peak regulation capability and optimization in the new energy environment.The main work is summarized as follows:(1)Modeling loads in office and living parks.The paper focuses on modeling lighting loads and controllable loads.When studying lighting loads,based on the characteristics of office and living area lighting loads,a multi-factor Monte Carlo modeling method is proposed,especially for lighting loads.The detailed modeling of the influence of human factors has been carried out;the research on temperature-controlled loads,such as air-conditioning loads,water heater loads,and refrigerator loads,is based on the electricity consumption habits of the office and living parks,mainly by analyzing their working principles An influencing factor model was established,and a Monte Carlo load modeling method with office and living park characteristics was obtained.And the simulation and analysis of the office and living park load verify the validity of the model.(2)Peak power regulation of micro power.The paper modeled and analyzed the output characteristics of the micro power supply,and simulated the case of office and living parks to verify the effectiveness of the model.The peak regulation ability of the power supply side was studied,and the wind-storage and light-storage participations were established.Peak shaving capacity calculation model for peak shaving;The CCHP system was researched and analyzed,and a peak shaving capacity calculation model was established.And with the minimum load fluctuation as the objective function,during the peak and flat periods of the load,the improved PSO algorithm is used for optimization.Simulation results show that during the peak load period,when the microgrid power supply participates in peak regulation,the load fluctuation rate is reduced from 38% to 10%,a decrease of 28%;during the flatvalley period,the load fluctuation rate decreased from 42% to 28%,a decrease of 14%,which verified the effectiveness of microgrid power peak shaving.(3)Load peaking capability.On the load side,under the premise of satisfying the comfort of the human body,the calculation model of the peak regulation ability of the controllable load to participate in the peak regulation is studied.When establishing the peak regulation capability of electric vehicles,a calculation model of peak regulation capability was proposed,which took into account the influence of multiple factors such as weather,the benefits of participating in peak regulation,distance factors,and human factors.Aiming at controllable loads(refrigerator load,air-conditioning load,water heater load),a calculation model of peak shaving capacity based on the influence of temperature and power was established.And with the minimum load fluctuation rate as the objective function,optimization is performed using the improved PSO algorithm.The experimental results show that when the controllable load participates in the peak shaving optimization,the load fluctuation is reduced from 25% to 22%,which is 3% lower.Effectiveness of power peaking.(4)Load peaking capability.On the load side,under the premise of satisfying the comfort of the human body,the calculation model of the peak regulation ability of the controllable load to participate in the peak regulation is studied.When establishing the peak regulation capability of electric vehicles,a calculation model of peak regulation capability was proposed,which took into account the influence of multiple factors such as weather,the benefits of participating in peak regulation,distance factors,and human factors.For temperature-controlled loads(refrigerator load,air-conditioning load,water heater load),a calculation model for peak shaving capacity based on the effects of temperature and power was established.And with the minimum load fluctuation rate as the objective function,the Q learning algorithm is used for optimization during peak and valley loads.The simulation results show that when the controllable load participates in the peak regulation optimization,the peak load fluctuation decreases from 12% to 9%,Reduced by 3%;the fluctuation rate of the load during the flat valley period was reduced from 26% to 22%,a decrease of 4%,which verified the effectiveness of the microgrid power peak regulation.In summary,in this thesis,the output characteristics of wind power and photovoltaic power are studied on the micro-power source side.Simulation models for peak-shaving capability of wind-storage,light-storage,and CCHP systems are established,and the minimum load fluctuation rate is used as the objective function to verify This shows theeffectiveness of microgrids in which peak shaving tasks can be undertaken with renewable energy.On the load side,on the basis of studying the characteristics of controllable loads,an analytical model for peak capacity adjustment of electric vehicles,air conditioners,water heaters,and refrigerators was analyzed and established.With the minimum load fluctuation rate as the objective function,it was verified that the controllable load was undertaking the adjustment.Effectiveness of peak tasks.Combined with the research on the source-load side,a multi-objective function with the minimum output and the minimum load fluctuation rate of the main power grid was established,and the Q learning algorithm was used for optimization simulation analysis.The results show that,while meeting the smooth load fluctuations and effectively reducing the peak-to-valley difference of the load,the main power grid output can be smaller,and the output curve is smoother,which relieves part of the peak power regulation pressure of the main power grid.