Evolutionary Game Analysis Between Large Power Consumers and Power Sellers in the Context of Big-Data-Driven Value-Added Services

As power system reforms deepen, direct trading with large power consumers has emerged as a crucial aspect of opening up the power sales market. In light of this trend, power sales enterprises should accelerate their digital transformation in response to the growing demand for personalized services from large consumers and continuous advancements in energy digitalization and smart technologies. In particular, big data technology is critical for power enterprises to satisfy users and increase profitability as it can help enterprises gain deeper insights into user needs and behavioral characteristics. The application of big data to provide customized value-added services for large power consumers has become a key development focus. In this paper, we develop a two-party evolutionary game model involving power sellers using big data technology to profile large consumers and offer them customized value-added power packages. We conduct a detailed analysis of the local stability of equilibrium points and employ MATLAB.R2021a to examine the impact of changes in the benefits of value-added services for large consumers and the cost coefficients associated with big data on the system’s evolutionary outcomes. The study results indicate that big data technology can enhance the competitiveness of power sellers in the market. Value-added services based on user-profiling using big data have become a crucial factor in influencing the decision-making behavior of large consumers. Additionally, the investment cost in big data infrastructure by power sellers impacts system evolution, with the cost coefficient being inversely proportional to their willingness to offer customized services.