Impacts to Local Crops of Wind Farms in Zhangbei, China

Wind power is a major contributor to the solution of energy crisis, air pollution and global warming by reducing the consumption of fossil fuel. However, the increasing deployment of wind farms may have unnoticed effects on environment, especially the local crop yields, which is largely ignored in the existing research. Based on the analyses of data collected from a typical area, Zhangbei in China, which is one of the seven greatest wind power bases in China with more than 5 million KW potential wind energy generation, interesting relations in terms of the wind power capacity and crop yields are revealed in this paper. Specifically, we found that the newly built wind power capacity is negatively related with all the main crop yields in this typical area, but the total wind power capacity is positively related with local crop yield. Furthermore, based on the data of wind power capacity and crop yields, an improved artificial neural network named the particle swarm optimization-radial basis function (PSO-RBF) algorithm is applied to predict the local annual oat yield. Our results prove the effectiveness and efficiency of the proposed algorithm with a mean absolute percentage error (MAPE) of less than 15.