An IGDT-based decision model for industrial users participating in electricity and carbon markets considering differentiated power quality services

The gradual increase in the penetration rate of distributed renewable energy has become a new situation. Under the new situation, industrial users with high energy consumption need to make reasonable decisions in electricity and carbon markets while ensuring power quality. This is a real problem that needs to be solved for high energy consumption industrial users. Therefore, we propose a decision model for industrial users participating in electricity and carbon markets considering differentiated power quality based on information gap decision theory (IGDT). Firstly, we analyze the impact of users' installation of distributed renewable energy on their power quality and carbon emissions. Considering the differentiated power quality services in the future electricity market, the carbon emissions when the user chooses different levels of power quality are quantified. Secondly, a decision-making model of industrial users participating in electricity market and carbon market considering differentiated power quality services is established. The objective function is the maximum profit of the user participating in the double market trading performance period. Thirdly, the IGDT theory is used to describe the uncertainty of distributed renewable energy generation, which reduces the decision-making risk of industrial users. Finally, we take a steel production enterprise as an example to analyze. The numerical results show that the proposed model can reduce carbon emissions and obtain maximum benefits for industrial users. The proposed model can realize the coordination and optimization of monthly electricity purchase and carbon quota trading volume. Moreover, it can help industrial users rationally arrange the access capacity of distributed renewable energy devices and select the improved power quality level.