Centralized and Distributed Optimization for Vehicle-to-Grid Applications in Frequency Regulation

This paper proposes centralized and distributed optimization models for V2G applications to provide frequency regulation in power systems the electricity market. Battery degradation dynamic EV usages such as driving period, distance, multiple charging/discharging locations are modeled. The problem is formulated into linear programming (LP) model by introducing two sets of slack variables. However, encounters limitations privacy concerns, high complexity, central failure issues. To overcome these limitations, optimal developed decomposing subproblems using augmented Lagrangian relaxation (ALR) method. alternating direction method multipliers (ADMM) used solve iteratively. proposed evaluated real data from Independent Electricity System Operator (IESO) Ontario, Canada. Simulation results show that can aggregate EVs regulation; meanwhile, owners obtain monetary rewards. simulation also shows including battery usage increases accuracy. By approaches, cost low efficiency generation units be compensated or partially replaced EVs, which will reduce greenhouse gas emissions.