Abstract

Load aggregators play a pivotal role in demand-side regulation by coordinating flexible resources between electricity retailers and end users. However, existing studies have rarely considered their dual-role attribute, namely acting as followers of electricity retailers while serving as leaders of end users. Moreover, most studies assume fully rational user behavior, which may not accurately reflect practical decision-making processes under heterogeneous preferences. To address these gaps, this paper proposes a coordination strategy for EV and air-conditioning loads based on a Stackelberg–evolutionary game framework. A three-layer Stackelberg–evolutionary game model is first constructed, with the electricity retailer serving as the leader and the load aggregator acting both as a follower and a leader, thereby revealing the interest interactions among multiple stakeholders. Subsequently, an evolutionary game based on the Logit protocol is introduced to establish a dynamic evolution equation for users’ collective strategy choices, which captures users’ heterogeneous trade-offs between electricity costs and thermal comfort, as well as their strategic interactions. Next, a genetic algorithm was used to solve the problem. Finally, case study results demonstrate that, compared with the pure Stackelberg game, the proposed strategy increases the aggregator’s profit by 57.9% while reducing users’ electricity costs by 41.2%, thereby validating its effectiveness.

IPC Classification

Keywords