Quantifying the potential of electric vehicles for demand-side flexibility
Quantifying the potential of electric vehicles for demand-side flexibility
Motivation
Battery Electric Vehicles (BEVs) are promising candidates to provide flexibility to the electric grid by adjusting their charging and discharging processes. However, the magnitude of their contribution, inclusive of human mobility behaviour, remains unclear. In this work, a real-world GPS-labelled mobility dataset measured on 1000 cars across 2 years, comprising over 4 million trips is used to simulate BEV charging and quantify the unidirectional flexibility potential provided by delaying charging. Flexibility is modelled as tuples of power and time for different durations at different times of the day under varying parameters of BEV battery size, charging power, and home, work and public charging locations. Eight distinct driver groups identified by clustering techniques on driving behaviour provide insights to access the quantified flexibility from the right groups at the right times. The inclusion of BEV user range anxiety as a parameter through BEV user surveys lends a realistic perspective to the quantified flexibility potential. The results help grid operators assess the quantity of available realistic flexibility potential from BEVs for power system operation. Furthermore, to energy regulators and policymakers, the results provide a basis for the design of new business models and energy market products for flexibility provision.