Improving flexible optimal scheduling of virtual power plants considering dynamic line rating and flexible supply and demand

Global warming, air pollution, and the need for energy has led to the growth of renewable energy sources (RESs) around the world. Despite the fact RESs offer less expensive energy to customers, uncertainty in their output power, along with other sources of uncertainty inherent in power systems operations such as market price and load forecast, creates an imbalance between demand and supply. The virtual power plant (VPP) has been recognized as a solution that can integrate RESs into the power system to help deal with uncertainty. VPP operators require a flexible power system to address the supply and demand imbalance by rescheduling energy resources. In this study, coordinated scheduling of flexible resources in the form of a VPP participating in a day-ahead (DA) market is presented. Flexible resources and components include fast ramping conventional generators (CGs), battery energy storage systems, dispatchable wind turbines equipped with compressed air tanks, lines equipped with dynamic line rating (DLR) technology, and a flexible demand response program. In addition, flexibility indices (FI) are provided for each flexible component to capture each component’s impact on system flexibility. The proposed model is a mixed integer linear program (MILP) implemented on the IEEE standard 33 bus system. The result of the study show that the system equipped with DLR technology increases VPP profit when compared to the system with static line rating by 23%. The 24-hour average system’s FI indicated an increase in operational flexibility by the proposed model. Finally, the energy generated by each flexible resource is compared for different cases. The results indicates an increase in power sold to the upstream network by the VPP and a decrease in the need for load shedding. •The modeling of flexible scheduling problem in VPP in day ahead market.•The calculation of the VPP benefits by using DR, ESS, and CA-WT, and DLR.•The introduction of flexibility index for real-time capacity of the line.•The computation of system’s normalized FI to quantify the system’s flexibility.•The effect of DLR in the VPP benefits and flexibility index.