Maximizing EV profit and grid stability through Virtual Power Plant considering V2G - Tuerkoglu, A. Selim; Guldorum, H. Cihan; Sengor, Ibrahim; Cicek, Alper; Erdinc, Ozan; Hayes, Barry P. (ELSEVIER, 2024)
The electrification of transportation through the widespread adoption of electric vehicles (EVs) has raised substantial concerns within the realm of power grid operations. This concern predominantly stems from the elevated electricity demand brought about by the surging population of EVs, consequently exerting strain on the power grid infrastructure which can be reduced with vehicle-to-grid (V2G) technology integration. To address this issue, this paper delves further into the realm of grid integration by introducing a Virtual Power Plant (VPP) concept to enhance the synergy between EVs and power grid. This study aims to compare different realistic objectives, ranging from total active power loss and voltage drop minimization to EV profit maximization and then optimize the balance between the distribution grid power quality and VPP profit through bi-level modeling. The presented model is devised as mixed-integer quadratically constrained programming (MIQCP) and incorporates Temporal Convolutional Network (TCN) based forecasting to handle the uncertain behavior of the residential loads using historical data. The experiments are conducted in IEEE 33 -Bus and real -world 240 -Bus distribution networks. The results indicate that enabling bidirectional power flow between the grid and VPP can yield significant profits for EV users while only marginally impacting the active power loss, approximately around 5%. This validation underscores how V2G not only presents various advantages for power system operators but also benefits EV users simultaneously.
Keywords: Electric vehicle; Optimal power flow; Vehicle-to-grid; Virtual power plant; IN ELECTRIC VEHICLE; MANAGEMENT; SUPPORT; ALGORITHM; SYSTEM; Energy & Fuels