Dynamic Partitioning Strategy Of Energy Autonomous Domain For Distributed Photovoltaics

Distributed photovoltaics have been widely used in the power market in recent years due to their high efficiency and cleanness.As an important way for grid-connected distributed photovoltaics,photovoltaic microgrids have developed rapidly.With the development of new energy interconnection networks such as the ubiquitous power Internet of Things,the microgrids are clustered to form a kind of microgrids group which is called energy autonomous domain.With the help of information and communication technologies,information exchange and energy exchange among microgrids can fully utilize the distributed photovoltaic energy in the microgrid,improve the energy utilization rate,reduce the fluctuations caused by the photovoltaic grid connection to the main power grid,and promote the reform of the electricity trading mechanism under the ubiquitous power Internet of Things.In the ubiquitous scenario of electric power IoT,clustering between microgrids is conducive to the flow of energy in a small area,reducing energy transmission losses and the impact of the microgrid on the main power grid during the process of grid connection.Unlike conventional clustering methods,clustering among microgrids is affected by the geographic distribution of the microgrids and the net energy status of the microgrids.In this thesis,a decision tree model is used to predict the distributed photovoltaic power generation in the microgrid to obtain the net energy status of the microgrid.Based on the geographic distribution of the microgrids,an energy autonomous domain partitioning method based on kmeans is proposed.Simulation results show that the proposed method increases the self-governing ability of microgrids and shortens the energy transmission distance,thus,effectively improves the energy transaction efficiency between microgrids.The effective partitioning of energy autonomous domains lays a solid foundation for subsequent energy dynamic equilibrium.After the energy autonomous domain is formed,there are still energy redundancies and deficits among microgrids,and certain energy transactions are required to achieve energy balance.This thesis analyzes the energy trading behavior among microgrids based on the actual power market,and models the microgrid energy trading as a Stackelberg game model.Through the competition and games among microgrids,the energy balance in the energy autonomous domain is dynamically realized.It also ensures that the utility function of both parties of the transaction is maximized,the energy utilization rate is improved,and the economic cost is reduced.Finally,this thesis conducts a simulation analysis of the proposed trading model.The experimental results prove that there is a Stackelberg equilibrium in the dynamic trading of the microgrids in the energy autonomous domain.