A Machine Learning Model On Bids Submission For Power Demand Response (DR) Resources In Gas Market

Abstract

With the further development of the competitive gas market, market participants such as gas selling companies and large gas users have become one of the important trading entities. In this paper, gas turbine is used as demand response (DR) resources of the power system to support the energy transfer point of the gas network, and a machine learning model for bidding for power demand response resources in the gas market is proposed. The model uses General Regression Neural Network (GRNN) to fit discrete data points to 'Cost-Capacity' bidding curve to participate in the competition of the gas market, and to achieve the optimal distribution of power demand response resources. Finally, the validity of the model is verified by relevant case.