Forecasting of Chinese Hydropower Generation Using WASD-Neuronet

Abstract

Hydropower resource is one of the renewable energy sources. With the increasing Chinese economy, people are paying much more attention to sustainable development. The increasing hydropower load is the basis of the development of power industry. Due to the characteristics of electrical energy, predicting the hydropower accurately is a potentially beneficial way to plan hydropower reasonably. This paper presents a neural network method to predict hydropower generation whose data is influenced by several factors such as social economic, population and climate. By using the past 52-year rough data, a 3-layer feedforward neuronet equipped with the weights and structure determination (WASD) method is constructed for the prediction of the Chinese hydropower generation in this paper. By processing mass of data, we could basically predict the hydropower generation using such a WASD neuronet. To a large extent, the trend of developing Chinese hydropower generation in the next years will keep growing.