Research On Multi-source Collaborative Optimization Scheduling Of Active Distribution Network

The multi-source development of the active distribution network has led to the rapid improvement of energy storage technology and the development of intelligent homes.At the same time,electric vehicles have gradually emerged in the social economy.This series of load-side developments has led to a gradul increase in the likelihood that flexible loads will actively participate in grid scheduling.With a large number of renewable energy sources and distributed power sources connected to the active distribution network,energy storage and flexible load participation scheduling can make grcater progress in achieving peak-shaving and valley-shaping and improving the flexible regulation of the distribution network.It is also an important part of the active distribution network "source-network-load"coordinated scheduling.In this paper,the physical characteristics of all kinds of power supply and load accepted by active distribution network are analyzed and classified,and the distribution network is decomstructed and analyzed from different power generation doevices on the "soure" side to different load types and energy storage devices on the "load" sicde.Based on the above theoretical analysis,on the premise of considering the uncertainty of wind power and.photovoltaic output,this,paper combines the idea of multi-time scale to design the pre-day and intra-day optiomal scheduling strategy for ADN.Firstly,the process frmamework of active diastribution network is constructed,and the dispatching framework is di vided into three control levels and ADN main dispatching center,and the information flow and energy flow on the scheduling day are optimized.Based on the analysis of the characteristics of "source"and"load",the.mathematical modeling of schedulable un it is carried out,and the ADN optimal scheduling model with complementary time scales is established on the basis of multi-time scale.The day-to-day scheduling is divided into 24 periods to optimize the scheduling day according to each hour,and the goal is to minimize the total operating cost of ADN on the scheduling day.Intra-day scheduling is divided into 96 periods according to every 15 minutes,the goal is the minimum adjustment of adjustable metric and the largest amount of new energy absorption,so as to promote the optimization of the in-network resources of the active distribution network.This paper uses DE-ICA as the algorithm for solving the optimal scheduling model.After the improvement of the Empire competition algorithm based on differential operators,it not only enhances the diversity of the group,but also retains the outstanding individuals in the group,reflecting the evolutionary thinking of the survival of the fittest.Under the comparison of various algorithms,it is proved that the improved algorithm has strong convergence and operation speed,and it is not easy to fall into local optimum.Finally,in the improved IEEE33 node example,the proposed scheduling model is simulated by DE-ICA.The simulation results show that the multi-source collaborative optimization scheduling strategy proposed in this paper can significantly reduce the running cost of the scheduling day,and the new energy consumption rate is significantly improved on the scheduling day.It proves the validity and practicability of the proposed model strategy.