Extended short-term load forecasting of power system based on cloud computing

Extended short-term load forecasting of power system based on cloud computing

Wang Huizhong Hou Yingkun Zhaokai Li Chunxia

In the electricity market environment, the development and adjustment of the day load planning cycle shortened, especially the rolling generation plan, so that the existing load forecasting method can not meet the demand for the accuracy and speed of the Ministry of Electric Power, so some people put forward to extend the concept of short-term load forecasting to solve this problem, But this method causes the dimensionality of learning machine to be difficult to avoid. The method is improved by cloud computing technology, and the prediction precision and speed are improved while avoiding the dimensionality disaster, and the effectiveness of the method is validated by using the power grid operation data provided by distribution company East-slovakia.

Extended short-term load forecasting of power system based on cloud computing