A two-stage optimization decision making model of virtual power plant group considering multi-time scale
With a single virtual power plant aggregated by multiple types of distributed energy(DE)as the core unit,the industrial region is divided into groups with multiple virtual power plants(VPP),and a two-stage optimization decision making model for region-type VPP clusters considering multi-time scale was proposed.In the single-day scheduling plan of the first stage,the group was divided into upper and lower layers,and trading with external power grids was conducted by traders as representatives,thus maximizing the benefits of the group.While the lower layer was revising the day-ahead strategy of the upper layer,the operation mode of VPP in the cluster is studied and the transaction price of electric energy within the group was set independently so as to minimize the penalty cost of schedulable load correction error and the adjustment cost of electricity transaction.In the second stage,a buffer boundary constraint was introduced so that real-time correction can minimize the unbalanced cost and ensure timely load response at the same time.
distributed energyvirtual power plant groupmulti-time scalereal-time correction
万方数据
维普
