基于需求侧管理的专线用户节能诊断研究-电气工程专业论文.docx

广东工业大学硕士学位论文AB 广东工业大学硕士学位论文 ABSTRACT Demand side management(DSM)Can enhance both the flexibility of load response and interaction between power suppliers and users，as well as reduce peak demand and make the whole system more efficient and reliable．Meanwhile，DSM Can balance demand side with supply side more effectively and save power by improving energy efficiency and optimizing the resources，finally,achieve the purpose of saving energy．Industrial users consumed most electricity from power grid，SO energy-saving reconstruction research for dedicated users under the framework of DSM Can supplement DSM wi廿1 a microscopic aspect and has great contribution for building a clean，low carbon，efficient modem energy system to a safe and resource—saving society． A comprehemive research on the background，hislrioy and current ststus of domestic and foreign DSM and dedicated users in energy—saving reconstruction were made．The artificial intelligence theories and the main content of demand response(DR)were analyzed．DR is the most economic part of DSM and would be classified into three types based on evolutionary algorithms，artificial neural network(ANN)and multi-agent system theories．Classified DR technologies have diffirerent impact and effect in enerey-saving．Simulation models were built by Gridlab software and the results show that DR had positive impact for energy·saving management． The basic technology and theoretical formulas of dedicated users in energy-saving diagnosis were analysed，including：Fourier transformation for data acquisition and processing， relatived electric power parameters，main electrical equipment such as transformer and eleetrict motor．etc．with energy—saving technologies．Relevant processes and equipment requirements for dedicated users in energy-saving diagnosis were illustrated．On this basis， energy—saving diagnoses were made for the dedicated user entrpraise A，electrical parameters and related information were measured in scene．The final energy-savi