Operation and control of multiple electric vehicle load profiles in bipolar microgrid with photovoltaic and battery energy systems. (January 2023)

• Record Type: Journal Article
• Authors: K.S., Nisha; Gaonkar, Dattatraya N.; N.S., Jayalakshmi
• Is Part Of: Journal of energy storage. Volume 57(2023)
• Publication Date: 2023-01
• Subjects: EV charging profile -- Bipolar DC microgrid -- Voltage unbalance mitigation -- Model predictive control; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.106261
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: Charging of electric vehicles is going to be a major electrical load in the near future, as more and more population shift to electric auto-motives from conventional internal combusted engine-powered vehicles. Integration of electric vehicle charging stations (EVCS) might even burden the existing grid to a point of collapse or grid failure. Establishing charging stations interfaced with bipolar DC microgrids along the roads and highways is the most realistic and feasible solution to avoid the overburdening of the existing power system. The bipolar DC microgrid is a far better microgrid structure than the unipolar microgrid structure in many aspects like reliability, flexibility, and controllability. It can provide multiple voltage level interfaces according to the load demands, which is very apt for different charging levels of electric vehicles (EVs). Operation of multiple sources and multiple loads connected to bipolar DC microgrid will affect DC voltage regulation, capacitance-voltage balancing, and overall stable operation of the grid. In order to mitigate these power quality problems arising in multi-node bipolar DC microgrids, a decentralized model predictive control is proposed in this paper. EV charging load profiles are modeled and developed by considering standard driving cycles, state of charge, and power demand of multiple vehicles to study the effect of unpredictable varying EV loads in the bipolar DC microgrid. EVCS thus modeled are connected to solar photovoltaic-battery energy storage fed bipolar DC microgrid with three-level/bipolar converters and analyzed under dynamic conditions for capacitance–voltage unbalance mitigation, voltage regulation, and the stability of operation with model predictive control. Simulation studies are carried out in MATLAB/Simulink to verify the effectiveness of the system. Highlights: Emphasize the concept of bipolar DC microgrid as the best solution to power EV charging stations Development of EV load profile model considering driving cycle and vehicle dynamics of multiple EVs Incorporation of vehicle to grid (V2G)/grid to a vehicle (G2V) power flow in bipolar DC microgrid Faster voltage balancing, grid voltage regulation, MPPT and power sharing in transient conditions Effective decentralized model predictive control of bipolar microgrid with EV charging loads.