Medium and Long–Term Electricity Forecasting Method Based on Solow Model: A Case of Hubei Province

Accurate electricity forecasting is very significant to power system. Modern smart grid has huge data and complex structure, and the nonlinear relationship between influencing factors and electricity demand is complex, random and changeable. Only by making full use of large amounts of data, accurate, stable and reliable medium and long-term electricity prediction can be made. Based on the traditional Solow Model, this paper proposes an Extended Solow Model by analyzing a lot of economic data and extracting key influencing factors. With the real load data of Hubei power grid, the experimental results show that the Extended Solow Model proposed by this paper can effectively improve the forecasting accuracy of 1.40% compared with the traditional Solow Model.