Research On Multi-objective Energy Optimization Scheduling Of Active Distribution Network Based On Multi-time Scale

The large scale infiltration of distributed power supply facilitated the local compensation of active power and reactive power,and reduced the loss of power on transmission line.To fully absorb distributed power,stabilize renewable energy uncertainty,the development of active distribution network,establishing of the source load interaction and power supply&demand coordination system for the distribution system is very important.The core of this paper is integrating the existing resources(access capacity and DG address,network topology),using flexible dispatching technique network and intelligent equipment communication technology of active power distribution,by coordinated control of the distributed power,energy storage and flexible load,fully optimize and absorb the large-scale accessed DG to especially clean energy(photovoltaic,wind power and so on),and ensure multiple targets such as the quality of power supply distribution network,the optimal network loss,economic operation.This paper used a combination optimization method of long time scale optimization and short time scale regional autonomy,differential evolution algorithm improved by chaos idea and particle swarm optimization algorithm is compared and analyzed.And the chaos differential algorithm wass used to solve the whole network optimization problem.The whole network was optimized to reduce the loss of the whole network and ensured the economic operation of the whole network,and issued the running target to each autonomous region,regional internal integrated its own adjustable active and reactive resources,controllable load,real-time electricity prices,SOC of energy storage,renewable energy output,etc.three flexible load control technologies can be adopted if necessary,responding to changes in load and renewable energy output in a short time scale,coordinated tracking the whole network,and made the whole area and the whole network running in the optimum state.Finally,this paper took IEEE33 node example and network topology as model,combined with 24 hours' wind energy,PV and load data obtained by load forecast,carried out the simulation of the whole stage,and the validity of the optimization scheme is verified.