Forecasting the urban power load in China based on the risk analysis of land-use change and load density

Abstract

Abstract Along with the increasing development of the urban society and economy, urban power is facing an increasing number of risk factors. The conventional load forecasting methods cannot guarantee the accuracy of the prediction; however, scientific urban load forecasting has a greatly significant meaning to urban power planning and supply. This paper firstly analyzes the risk factors that affect the fluctuation of the power load. From the perspective of the spatial load, the factors influencing the fluctuation of the urban power load are mainly determined by the change in land use and load density per unit area. Secondly, based on the basic principle of cellular automata, the rules and model of land-use change are established by considering the risk factors. From the aspect of land-use change, the cellular change rules of the land use with the risk factors are proposed and the methods of land classification change are presented by combining them with geographic information system (GIS) technology. Meanwhile, after comprehensively considering the effect of the risk factors on the load density fluctuations, the power load forecasting model is established based on the risk analysis of the land-use change and load density. Finally, taking a specific city as an example, the case study results show that this model is scientific.