Multi-time Scale Active And Reactive Coordination Scheduling Strategy For Active Distribution Network

Faced with multiple pressures such as energy depletion,environmental pollution and ecological deterioration,making full use of renewable energy sources represented by photovoltaic and wind turbines has become a global consensus.At the same time,the penetration rate of distributed generation(DG),energy storage system(ESS),flexible load(FL),on-load tap changer(OLTC)and capacitor bank(CB)in the distribution network is increasing,and the traditional distribution network is gradually evolving into active distribution network with many regulatory resources.However,the multiple randomness of source-load,the operational control characteristics of various resources and the time scale difference bring severe challenges to the overall operation-control of the system.How to realize coordinated operation and efficient use of multiple resources to ensure system security economic and efficient operation has become the focus of current research.In addition,with the rapid increase of electric vehicles,EV charging load in the future will become an important part of the grid load.The disordered charging behavior of a large number of EV will have a significant negative impact on the power system.As a flexible and controllable load,EV charging load has the potential to be flexibly scheduled,fully exploiting its schedulability,and achieving multi-party win-win for power companies,EV charging stations and EV users.Based on the above background,considering the multiple randomness of source-load,the control characteristics of various resources and the time scale difference,this paper has carried out in-depth and meticulous research on the core issues of ADN optimization strategy,coordination scheduling model establishment and solution under the premise of ensuring full consumption and efficient utilization of renewable clean energy.The main tasks completed by this paper are as follows:1)Analysis and summary of the strong coupling characteristics of active-reactive power in the distribution network.Based on the simulation analysis of the modified IEEE 123-bus test distribution system,the necessity and practicability of active-reactive joint scheduling are proved.Furthermore,the power coupling characteristics and power output characteristics of adjustable controllable equipment are analyzed,and its operation control model is established.2)Considering the multiple uncertainties of source-load fluctuation,based on the scene analysis method,ADN active-reactive coordination robust optimization strategy adapted to high proportion PV access is proposed.By screening typical scenes and taking into account the limit scene,the ADN optimization control scheme under severe scenes is obtained.The simulation results verify the robustness and practicability of the proposed method.At the same time,the practicality of the scheduling strategy proposed in different operating scenarios is analyzed in detail,and further,the performance of the convex relaxed model based on the second-order cone relaxation technique is validated;the sensitivity analysis of adjustment step and action time of the discrete adjustment devices on optimization results is also carried out in detail.3)Considering the scenario of large-scale EV charging in the charging station and accessing ADN,a multi-time scale coordinated scheduling strategy based on model predictive control(MPC)is proposed.At the distribution network level,based on MPC,the multi-level coordination and step-by-step refinement of multi-time scale refined control schemes are developed.The simulation analysis shows that the proposed strategy realizes the coordinated optimization operation of many adjustable devices in ADN and the fully absorbing and efficient utilization of renewable clean energy.At the EV charging station level,under the condition of satisfying the charging demand of EV users,considering the bilateral interests of charging station and grid company,an EV two-stage ordered charging strategy for EV cluster access for fast charging and slow charging is established under the "source-network-load" interaction mechanism.The proposed strategy can fully utilize the schedulable capability of EV cluster charging,and alleviate the negative effects such as “peak peaking” and voltage drop caused by large-scale EV charging,and provide active support for system economic and safe operation.