Research On Multi-Time Scale Optimal Dispatch In Active Distribution Network Based On Model Predictive Control

With the problem of environment pollution and global energy shortage become more and more serious,it is important to improve the permeability of renewable distributed energy and optimize the operation of power system.High permeability of distributed energy has a profound impact on distributed power network,for example:improve the utilization of energy resources,reduce the environment pollution,reduce the active power losses caused by power flow and have diverse impact on the power quality and the reliability of power supply of distribution network.Therefore,in order to coordinated optimize the controllable distributed generations in distribution networks to maximize accommodate intermittent renewable energy resources,it is in emergency to narrowly coordinate control and manage the distributed generators?energy storage systems and flexible loads in active distribution network.With increasing presence of intermittent energy resource in active distribution network,it is so difficult to precisely predict the output of renewable resources that the predictions of outputs of distributed energy in active distribution network are inapplicable.Therefore,in order to maximize accommodate intermittent renewable energy resources,a model predictive control(MPC)based multi-time scale coordinated control of distributed generators in active distribution network was proposed to narrowly coordinated control and manage the distributed generators?energy storage systems and flexible loads.In the long time scale,firstly,establish local autonomy area including the small capacity distributed generations and renewable energy resources according to the network topology,and equivalent to controllable distributed generation by calculating the power supply and storage capacity Index of local autonomy area;secondly,set the optimal dispatch cost as optimization objective function,solving the optimal power flow problem by original dual interior point algorithm.The long-time-scale results treated as reference values,the MPC based short-time-scale optimization utilize multi-step dynamic roll optimization to compute the active power outputs and smooth the control process.The simulation is based on the IEEE33 node example to verify the proposed model.In the simulation section,comparative analysis the tradition open loop optimization and the model predictive control based multi-time scale optimization scheduling method in the case of wind power?photovoltaic power gently change and the case that the wind power and photovoltaic power rapidly fluctuation.Results obtained from simulation and comparative analysis demonstrate the feasibility and effectiveness of the proposed dynamic optimization strategy.