Techno-economic analysis of G2V and V2G charging systems: A case study based on the Monash microgrid

The electrification of the transport sector has gained significant attention as a key factor in reducing global carbon emission. Consequently, global electric vehicle (EV) adoption is projected to rise steadily. However, despite the environmental benefits of EVs, the lack of sophisticated control systems to regulate and optimize EV charging pose substantial downsides to grid stability and efficiency. To address these challenges, smart charging technology enables EV fleets to transition from passive consumers to active prosumers, effectively functioning as distributed Battery Energy Storage Systems (BESS). This study presents a proposed smart parking and charging system within the Monash microgrid, integrating both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) charging schemes. A Mixed Integer Linear Programming (MILP) approach is employed to maximize the aggregator’s revenue through electricity spot price arbitrage while ensuring compliance with the Monash microgrid operational standards. The primary objective of this paper is to compare the economic efficiency and investment value of G2V and V2G chargers from an investor’s perspective, providing insights into the commercialization of smart charging systems. In particular, this study offers an in-depth analysis of the economic feasibility of smart chargers when considering EV users’ behavior, specifically their preferences for charger types (power levels). The simulation results reveal that in the context of the Monash microgrid, despite the technical advantages of the V2G system, achieving superior economic profitability over G2V systems through discharging power for spot price arbitrage remains challenging. Therefore, this study explores various conditions to identify factors that could enhance the investment value of V2G systems compared to G2V systems from a techno-economic perspective. • Presents a novel Smart Parking System integrating G2V and V2G functionalities. • G2V systems outperform V2G systems in terms of investment profitability. • High capital costs and limited discharging value reduce V2G’s investment value. • Optimizes EV charging schedules with a Mixed Integer Linear Programming approach. • Analyzes G2V and V2G systems’ profitability for investors with a techno-economic focus.