Scheduling optimization based on assessment of adjustable potential of large-scale industrial loads

As clean energy generation grows, power systems require greater flexibility to ensure safe operation. As a critical emerging entity that assists the power grid in balancing peak and valley load fluctuations, virtual power plants can provide flexible real-time power through demand response and coordinate reasonable dispatch responses among all participants to alleviate the contradiction between supply and demand during peak electricity consumption periods. Large industrial loads have the characteristics of a large load base. Currently, there is a lack of research on accurately analyzing the adjustable potential of power users in large industrial industries and then integrating them into virtual power plant operation dispatching. This paper introduces a multi-time-scale demand response assessment method, analyzes the response load characteristics of the steel and electrolytic aluminium industries, and proposes an optimal dispatch method based on assessing the adjustable potential of large industrial loads to optimize the load aggregator's cost benefits. Taking maximization as the goal, taking the data of Xinjiang Province as an example, the planning declaration curve of a large industrial load is solved, and the economic dispatch of a large industrial load is realized.