QAOA-based Day-ahead Clearing Model for Electricity Spot Market

The high degree of uncertainty in the operation of new power systems with large-scale access to new energy sources has increased the difficulty of clearing spot transactions in the power market, and the computational volume and complexity of model solving have become higher and higher. The rapid development of quantum computers provides a new idea for the future power market spot trading model solution. In this paper, we propose a model for day-ahead clearing in the electricity spot market using a quantum approximation optimization algorithm. The original day-ahead security constrained unit combination model of the electricity spot market is decoupled into a discrete-variable model and a continuous-variable model by the alternating direction multiplier method. The discrete-variable model is solved by the quantum approximation optimization algorithm, and the continuous-variable model is solved by the solver, and the start-stop state solutions of the units are obtained by constant alternating iterations. Based on the optimized unit start-stop solution, the winning power and node marginal tariff of the unit are solved by the security constrained unit combination model. Simulation examples based on the IEEE 39 -node system are performed to verify the validity of the proposed model.