Optimal solar–wind hybrid systems with EVs in distribution networks: AC/DC comparative analysis

This paper presents and compares two mixed-integer second-order cone programming (MISOCP) models to minimize the operating cost of a distribution network through the optimal management of AC- and DC-coupled hybrid systems (HSs) integrating photovoltaic (PV) and wind (W) generation with electric vehicles (EVs). The HS modeling distinguishes the power exchanges among renewable generation (RG), EVs, and the grid. EV charging and discharging are scheduled according to the available RG, feeder demand, energy prices, and network operating constraints. The models also incorporate a linearized representation of the on-load tap changer (OLTC). The exactness of the conic relaxation of the AC power flow was evaluated through feasibility gaps and confirmed by solving the nonlinear models with the binary decisions obtained from the MISOCP models kept fixed. Results for the IEEE 33-bus radial system show that both configurations utilize all available RG, avoid curtailment, reduce line loadability, and satisfy the state-of-charge requirements of the EV fleets. However, the coupling configuration influences fleet participation in energy arbitrage and, consequently, the feeder operating cost. Under AC coupling, energy arbitrage is economically advantageous only when the difference between low- and high-price periods offsets the discharging cost. In contrast, DC coupling allows renewable energy to be supplied directly to the EV batteries, promoting energy arbitrage despite limited price variation. This configuration also reduces the energy supplied by the main substation and avoids OLTC operations. A sensitivity analysis comprising 44 scenarios shows that DC coupling retains its operational advantages, whereas EV discharging under AC coupling occurs only with increases in demand, wind generation, or conversion efficiency.