Study On Intelligent Energy Management Modeling And Optimization Of Electricity For Commercial And Industrial Loads

Energy is an important foundation for the survival of a nation and the key tosustainable development. In the background context of climate change and energycrisis around the whole world, more and more attention is attached to developingclean energy and improving energy efficiency. Commercial and industrial load occupyan important position in the national load constitution which means that itsmanagement level is directly related to the quality of the energy economy.This article is based on the status quo of China’s industrial and commercialelectricity usage and makes an exploratory research to achive several kinds of smartenergy management methods by integrating distributed generation and demandresponse technologies within smart power system. First of all, this paper analyzes thespecific characteristics of commercial and industrial electricity loads and obtainssome typical curves and representative loads through cluster analysis. Then thesetypical loads are divided into three categories and modeled by their demand responsecharacteristics: task-continuous transferable load, individual thermostaticallycontrolled transferable load, aggregated thermostatically controlled adjustable load.Combining with the installed distributed power output characteristics, integratedoptimization strategies based on the three loads are designed and their potentialeffects are analyzed through simulation study.Simulation results show that the three optimization methods proposed reduce theload of the high price period. The load is transferred to the periods when large amountof distributed energy is generated. What’s more, part of the distributed generatingcapacity is transfered through energy storage device so that the excess electricity isavoided to be passed to the grid and the proportion of self-occupied energy isincreased. Thus better economy and greater grid stability is achieved.