Simulation Research on Power Grid Investment Demand Forecasting Model Based on Grey Clustering Algorithm

With the rapid development of China’s national economy, the increasing demand for electricity in the whole society, and the firepower of the 13th Five-Year Plan, the investment demand of China’s power grid is constantly increasing. Accurate and effective forecasting of power grid investment (PGI) demand can not only help to make overall plans for funds, rationally arrange the investment of power grid construction funds, reduce capital costs and economic risks, but also effectively improve the operation status of grid corporation, which is crucial to ensuring the steady development of grid corporation and promoting the investment planning and construction process of grid corporation. In this paper, data mining is used as a means, and the PGI demand forecasting model is used as the research object. When the investment demand and investment capacity do not match, the grid corporation’ investment capacity and investment demand are coordinated and optimized. A new forecasting model of PGI demand based on grey clustering algorithm is proposed, and through empirical research, the validity, applicability and superiority of the model proposed in this paper for the prediction of PGI demand are proved, which provides a new method for the prediction of PGI demand.