Exploring the possibility to provide black start services by using vehicle-to-grid

Abstract

Black start is one of the most important ancillary services that should be required by National Grid in the UK which traditionally has been provided by large power stations. However, the current shift towards greener technologies have opened the door to non-traditional technologies. In this study, we explored electric vehicles (EVs) and the minimum state of charge (SOC) that can be held by a fleet of EVs during a week that could potentially be used to help provide this service while providing Vehicle-to-home (V2H) services to minimise the consumers’ electricity bill. We also explored the impact of different photovoltaic (PV) penetration rates and different electricity tariffs through four different weeks of the year. In this study, we use a machine learning model classifier to predict the start and end locations of real-world EV travel data in England. These predictions are then used in an optimisation model to generate the SOC percentage and the consumers’ total electricity cost for the different scenarios. The machine learning model classifier model had an overall accuracy of over 85.80%. Final results showed that PV penetration rates and different electricity tariffs have an impact on the amount of SOC percentage that can be held during a week for all EVs that could potentially be used in the case of a shutdown and the consumers’ final weekly electricity cost. We found that using a dynamic tariff that follows the wholesale electricity market, the SOC percentages to provide black start services can be kept above 40% during the week and at the same time returning a total electricity cost under £30.00 per week.