A Day-Ahead Dynamic Pricing Model for the Collaborative Optimal Clearing of Renewable Energy and Industrial Load

The collaborative operation of renewable energy and industrial loads is considered as an effective method to promote the local utilization of renewable energy and decrease the carbon emission. In this paper, a local green power market is proposed, and a collaborative operation model based on green power trading for the renewable energy and industrial loads is formulated as a centralized optimization from the perspective of social welfare maximization. Then, a dynamic green power pricing method is proposed to keep the supply and demand balance of green power, as well as coordinate the operation of renewable energy and industrial loads. A distributed iterative algorithm based on the gradient projection method is proposed to clear the local green power market and solve the operation and trading strategies. Simulation results have shown the effectiveness of the proposed collaborative operation model and the dynamic power pricing method.