Risk Assessment For Distribution Network With Distributed Generations And Electric Vehicles

With the growing shortage of resources and deterioration of environment, many countries began to turn focus on new energy generation and the development of the electric car industry in order to achieve the purpose of energy conservation, emission reduction, environmental protection, and promote the sustainable development of society. On the construction of power grids, the access of distributed generation and electric vehicle is the major trend of the development of the traditional power grid, which contains opportunities and challenges. On the one hand, the access of DGs and EVs can improve the power quality, reliability of power supply and reduce the network loss of power system to a certain extent, bringing greater operational benefits and economic benefits.But, on the other hand, since the uncertainty of DGs and EVs that may bring certain risks by causing fluctuations and changing the power flow, which lead to voltage out of limitation, line overload, increase loss of network and even loss of load.In view of that, This paper has carried out a series of analysis and research on power grid containing DGs and EVs, and the main work of this paper is as follows:This paper studies the characteristics of uncertainty of DGs, EVs and Load, and discusses the probability model of them.Then, based on the theory of traditional distribution network risk assessment, the CVaR risk measurement method is proposed to modify the formula of accident consequence, so, the consequence, of voltage, line load, network loss and loss of load can be convenient to calculate by the CVaR model. According to the consequence of these indicators, corresponding risk indicators are estabilished and it is calculated in IEEE33, IEEE69 and IEE118.A risk early warning method for distributed network with DGs and EVs is submitted in this paper. The probability of the risk is divided by FCM and the consequence of risk is divided by fuzzy method. At last, the rank of risk for voltage, line load, network loss and loss of load is carried out by using mamdani fuzzy reasoning method. In this paper, the above indicators were warning independently. At the end of this paper, some risk control strategies of DGs, voltage, overload and loss of load is formulated to estabilish risk control model of distribution network with DGs and EVs, and the risk control model is solved by CPSO. The validity of the optimization model is verified by the IEEE33 system.