Risk Analysis Of Distribution Network Injected With Distributed PV Sources

As an emerging renewable energy, solar energy is clean, widely distributed, and has huge reserves, so it is receiving more and more attention for these advantages. With the rapid development of solar photovoltaic industry, a large number of distributed photovoltaic resources are accessing to the distribution networks. While the photovoltaic output is characterized as volatility and uncertainty, which may cause adverse impact to the distribution network. The possible effects are becoming the focus of attention. Therefore, to ensure the distribution network to be operating safety and reliable after injected with numerous distributed photovoltaic resources, it is necessary to carry out the risk analysis to this kind of distribution networks.In this paper, the power system risk assessment theory is used as the guidance and the three-phase power flow calculation method is used as a tool to analysis the time-series risk of the distribution networks. Firstly, according to the basic theory of power system risk assessment, combined with the characteristics of photovoltaic output, this paper put forward the basic risk analysis steps of the distributed networks with distributed photovoltaic resources. And the possible impacts on the distribution network by the photovoltaic resources are analyzed, on this base, the overvoltage and overload severity functions are chosen to calculate the risk indicators. Secondly, the key factors which affect the photovoltaic output are analyzed in detail, and the dynamic Bayesian network theory is applied to build a photovoltaic output probabilistic model. Several access indicators are adopted to evaluate the model, and the result shows that it is correct and effective. On the basis of studying the GridLAB-D software, the time-series model of photovoltaic output and load demand are also discussed. Finally, testing system R1-12.47-3is used to perform the risk analysis by using the models and method put forward in this paper. The result demonstrates the effectiveness of the models and the method, and comes to instructive conclusion that it is safe when the amount of the photovoltaic resource injected in less than the load demand.