An open-data based framework to estimate EV demand and attainable flexibility and application to the case of Singapore

Abstract

The electrification of the transport sector will have consequences that go beyond the transportation system itself, for example by also impacting power distribution networks and their operation. This both comes with potential threats and opportunities, such as sharp stochastic load changes that further burden already stressed power transmission and distribution systems. But opportunities arise from the flexibility that the vehicles batteries charging process could provide, eventually helping in better managing such infrastructures. This paper presents a framework that leverages openly available vehicles mobility-related data sources to define and simulate scenarios of electric mobility adoption, quantifying load and available demand flexibility in such scenarios. In particular, demand flexibility potential is assessed according to different charging strategies, including vehicle to grid, and different vehicles stationing behaviours. The goal is to provide a framework that is potentially of use to a set of different stakeholders, from city planners to grid operators and aggregators, to assess flexibility sources towards several applications. These range from planning for resilience by evaluating flexibility sources for provision of services to the grid, to enabling participation in ancillary services markets. The framework leverages a set of data sources, particularly carparks’ occupancy data in the form of live availability information at high temporal resolution.The framework is applied to a test case in the city of Singapore with the goal to estimate the consumption flexibility available from electric vehicles in carparks throughout the city. Maps that visualize the availability of such flexibility both in space and time are generated based on this assessment.