Online Adaptive Learning in Energy Trading Stackelberg Games with Time-Coupling Constraints

An energy trading mechanism is proposed between a selfish energy broker (aggregator) and her selfish energy customers (prosumers). The proposed design is a Stackelberg game where the aggregator trades energy bidirectionally between the prosumers and the wholesale electricity market for profit. For the purpose of satisfying the prosumers' desired energy consumption, time-coupling constraints are introduced. The described game does not admit closed form equilibrium strategies and therefore an online adaptive learning algorithm is proposed to mitigate this challenge. The latter is scalable with the number of prosumers and does not require explicit knowledge of the prosumers' decision-making mechanisms. Experimental results that utilize real-world data from the California market are provided to demonstrate the performance of the proposed approach.