Decarbonising the GB Power System via Numerous Electric Vehicle Coordination

The increasing penetration of renewable energy has promoted fast decarbonisation of the GB power system. However, low-carbon transitions should be considered from a whole energy system perspective, such as through localised vehicle-to-grid (V2G) techniques. Despite the potential benefits of utilising decentralised V2G flexibility for decarbonisation, the absence of an appropriate incentive mechanism has limited its effectiveness. This paper aims at studying the carbon-aware electric vehicle (EV) power scheduling problem by introducing a carbon emission flow model. The model enables EVs to be cognisant of carbon intensity (CI) signals, thereby enabling them to provide carbon services. To solve this problem, a novel decentralised control approach is proposed to coordinate numerous EVs in a computationally efficient manner with privacy perseverance. Case studies on a 14-node GB power network with a large population of 556,733 EVs are conducted to validate its efficacy in simultaneously maximising the EVs' carbon service provision and decarbonising the GB power system by intelligently linking local behaviours with global interest. Finally, the proposed control approach shows its generalisation performance for various day and season scenarios as well as evidence for realising the GB's decarbonisation ambitions by 2030 and 2050.