Research On Risk Control Model Of Micro-grid Based On Advanced Information Technology

With the deepening of sustainable green development and the damage of fossil energy to the environment,the research of distributed energy has been paid more and more attention.The microgrid is dominated by new energy generation,which can greatly reduce environmental pollution.Compared with fossil energy power generation,microgrid power generation has the characteristics of low cost,low pollution,easy operation and high flexibility.These characteristics have prompted the rapid development of microgrid.Although the microgrid has many advantages,due to the randomness of new energy fluctuations,human factors,and the influence of the development level of information technology,the development of microgrid faces many risks.The innovative technologies such as big data,cloud computing,the Internet of Things,and artificial intelligence have been widely used in power systems.However,applications in the microgrid are currently relatively lacking.Therefore,this dissertation takes microgrid as the research object and uses advanced information technology as the technical support to quantitatively analyze the key risk factors in the microgrid.The specific research contents are as follows:(1)The definition of risk control,microgrid,key technologies and advanced information technology are summarized.Firstly,it summarizes the theories of risk management and control and the definitions of microgrid in the United States,the European Union and the State Power Grid Corporation Electric Power Research Institute,and draws a schematic diagram of the basic structure of the microgrid.At the same time,in order to better understand the microgrid,the distributed generation technology,energy storage technology,protection technology,operation and control technology,and power electronics technology are summarized.Secondly,in order to study the application of advanced information technology in microgrid,a conceptual analysis is made on the current popular information technology,such as big data technology,artificial intelligence technology,Internet of Things technology,etc.,and the application of these technologies inmicro grid is summarized.(2)The risk identification model of micro grid is established.Firstly,risk factors involved in the microgrid are summarized from four aspects including generation side,management side,demand side and human factors.Secondly,in order to clarify the importance of each risk factor of the microgrid and the perturbation relation,this dissertation adopts the risk factor identification method based on D number theory and DEMATEL method.Finally,the method divides all factors into cause factors and result factors,and ranks the importance of all factors.(3)The risk factors of power generation side of microgrid are sorted out.The power prediction models of wind power generation and photovoltaic power generation are constructed.Firstly,the risk factors of power generation side are identified to clarify the research object.Secondly,based on big data and artificial intelligence,a wind power generation power prediction algorithm based on data mining technology and improved SVM algorithm and a photovoltaic power prediction algorithm based on deep neural network are established.After that,the algorithms are compared with other algorithms to prove the effectiveness of big data and artificial intelligence.Finally,the risk control measures of power generation side are proposed(4)The risk factors of the management side of the microgrid are analyzed,and the dispatching risk and the state maintenance risk of power equipment are analyzed.Firstly,all risk factors on the management side are identified.Based on the centrality,the research object is selected as microgrid scheduling risk and power equipment state maintenance risk.Then,on the theoretical basis of big data data fusion technology and artificial intelligence multi-agent system,evolutionary algorithm and fuzzy logic theory,a micro grid scheduling risk management and control model based on MAS and DCPSO algorithm and a power equipment state maintenance strategy development model based on cloud model and gray D-S evidence theory are constructed.Then,the proposed algorithm is compared and analyzed to prove the validity of the model.Finally,some suggestions on risk management and control are put forward based on the analysis results.(5)The risk factors on the demand side of the microgrid are sorted out,and the risk analysis model for the power consumption safety of microgrid power users and the monitoring and warning platform for the power supply safety of microgrid power users based on the Internet of things are proposed.Firstly,risk factors are sorted according to their importance,and the key research objects of this section are clarified.Secondly,based on artificial intelligence and Internet of Things technology,the security analysis method for power supply and consumption of microgrid power users based on rough set and CS-SVM and the framework and function analysis of microgrid power users' electricity safety monitoring and warning platform based on Internet of Things are constructed.Finally,based on the analysis results,the demand-side risk management and control measures of microgrid are developed.