Research On Coordination And Optimization Strategy Of Active And Reactive Power In Active Distribution Network Considering Load Characteristics

The vigorous development of distributed energy is expected to solve the energy crisis and form an environment-friendly society.Active distribution network(ADN)can control and optimize the system with distributed generation to guarantee the efficient use of energy and system security.The active and reactive power coordination optimization step is adopted to active distribution network can make the system smooth and economic cost optimal,which is necessary to the advance of active distribution network.Firstly,the basic components of active distribution network are analyzed and modeled,and the main generation models,load models and reactive power compensation devices are explored to lay the foundation for global energy dispatch and operation optimization.According to the characteristics of component scheduling,the priority control framework and global coordination optimization control system are established.The coordinated control system of hierarchical and partitioned active distribution network is established,and the coordinated optimization control method from the system target level,overall control and regional autonomy is constructed.On the long time scale,according to the forecast data of distributed generation and loads,the coordinated control of global distributed generation is carried out.In a short time scale,multi scenario technology is used to reduce the uncertainty in the optimization process,and the optimal result of deterministic scenario output under real-time scheduling is established.Secondly,the voltage fluctuation of the active distribution network will have a serious impact on some voltage-sensitive loads.For the purpose of ensuring load safety of voltage-sensitive loads and improve its economic benefits,based on their static voltage characteristics and time-varying characteristics,a linearized model of sensitive loads is established.In order to minimize the operation cost of the system,the power flow of the system,the power purchased from the main power grid,the output of micro gas turbine,the output of wind turbine,the output range of static var compensator and the on-load transformer are restricted.An active and reactive power coordination optimization model considering sensitive load is established,linearized and solved by intelligent optimization algorithm.It is verified in an improved distribution network example that the proposed coordination optimization strategy can better reduce voltage instability of highly sensitive load nodes,ensure the minimum voltage fluctuation of the whole system,optimize the economic cost of the whole system and minimize the economic loss of sensitive load nodes.Finally,considering the uncertainty of load forecasting,an improved linearized load model was established in consideration of the uncertainty.In order to eliminate the error in day ahead scheduling,multi time scale optimization is applied to the active distribution network,and the system is optimized and controlled in the two phases of the day and in the real time.The objective function is to minimize the economic cost of day ahead and real-time.In the day ahead and real-time phases,the unit,on load tap changer,fan,flexible load and system power flow are constrained respectively.A twostage active and reactive power coordination optimization strategy considering flexible load is established.First,Latin hypercube sampling is used to fit the error,and then Kmeans clustering is used to reduce the scene,reducing the amount of calculation and calculation time.It is verified in the improved IEEE33-node system that the scheduling can better stabilize the overall voltage of different highly sensitive loads and reduce voltage fluctuations.The real-time dispatching stage can further regulate the voltage of highly sensitive loads to make the voltage more stable and have less fluctuation.In the real-time scenario,the loss ratio of highly sensitive loads is significantly lower than that in the day-ahead scheduling stage.The proposed strategy can not only effectively reduce the total cost of the entire system and intraday scheduling costs,but also significantly reduce the loss costs of highly sensitive loads caused by voltage fluctuations.