Charge-discharge hierarchical-multi-stage decoupling optimization for large-scale EVs interacting with volt/var control in distribution systems

One of the challenges in achieving charging control for large-scale electric vehicles (EVs) is a long computational time. To address this challenge, this paper proposes a hierarchical-multi-stage charging-discharging optimization (HMSO) method for systems with a large number of EVs that decouples the optimization process in time and space. First, a hierarchical EV charging/discharging optimal control approach is constructed using the distribution network partition and EV charging/discharging load equivalence method to realize spatial decoupling. In the advanced zone optimization, the charging/discharging cost of equivalent batteries is minimized under the grid and equivalent battery power constraints. In the lowest-level zone optimization, the boundary node voltage uses the upper-level zone optimization results, and either the sum of the square deviations of the EV charging/discharging power to the upper-level equivalent battery power or the EV charging and discharging cost is minimized. Then, the hierarchical optimization period is divided into multiple periods by decoupling the battery capacity limit constraint and the depth of discharge constraint. In addition, a three-phase volt/var. control in the upper-level zone is combined with the HMSO lowestlevel zone optimization to reduce the bus voltage violation further. The results of two simulation examples verify the effectiveness and good application prospects of the proposed HMSO method. The test results indicate that the HMSO method can meet the time requirements of the online control. Namely, by using the proposed method, batteries of 1080 EVs can be charged to 85 % at the maximum depth of discharge, and the charging/discharging cost can be significantly reduced; furthermore, the three-phase voltages and neutral voltage can be constrained at a rational level.