Robust PID Control of EV Aggregator for C-FCAS Using Sequential Multi-Objective Optimization

Integrating Electric Vehicles (EVs) charging into power grids through EV aggregator, offers promising benefits to society for reliable, sustainable, and cost-effective energy solutions. A key aspect of this integration is the possibility of provision of Contingency-Frequency Control Ancillary Services (C-FCAS). While EVs primarily serve owners' transportation needs, they must return to their idle positions with a satisfactory State of Charge (SoC) after providing frequency support following a contingency. However, real-world implementations of grid-connected EV aggregator control for C-FCAS are complex and challenging because several factors, including uncertainties, perturbation magnitude, renewable energy penetration, and the SoC of EVs need to be considered. To implement the C-FCAS considering these factors, this paper presents a robust PID control approach for an EV aggregator. The objective is to effectively manage EV units willing to participate, ensuring frequency regulation support, system stability, and smooth return to their idle position. The strategy exploits a sequential multi-objective optimization approach with two main objectives: mitigating frequency perturbations caused by contingencies and restoring EV units power discharge to zero after a critical time period. Sequential Multi-objective Optimization (SMO) algorithms optimize the control parameters under diverse scenarios and uncertainties. The simulation results validate the effectiveness of the proposed strategy. The control strategy by an EV aggregator successfully handled different market conditions and uncertainties, ensuring reliable frequency regulation. This service opportunity will enhance income of EV owners and their willingness to participate while helping to keep the integrity of system operation.