Spatial Load Forecasting For Distribution Network Based On Ant Colony Algorithm And Cellular Automata

A distribution network spatial load forecasting (SLF) is the foundation of the distribution network plan, which not only forecasts the quantity of the future spatial load, but also provides the spot information of the spatial load incensement. Therefore, spatial load forecasting will significantly contribute to the distribution network plan. This paper had analyzed the related factors which influenced the spatial load forecasting, and constructed the spatial load forecasting model based on the cellular automata (CA). Besides, this paper also researched the method of distribution network spatial load forecasting based on the cellular automata and ant colony algorithm (ACA). The main content is as followed:Through the process of the analysis on the related factors of spatial load forecasting, we have got that the main factors, which influence the complexity and the accuracy of the network spatial load, are district partition, district area, simultaneity factor, load curve, process of forecasting method and so on.Against the problem that using land-use based method to simulate the process of land-use type evolution in spatial load forecasting, this paper had made use of the features that cellular automata have both spatial dynamics and localization to construct the forecasting model based on the spatial load forecasting, in order to simulate the land use type evolution, divide and define the load cellular, as well as establish the basis of spatial load forecasting.Against the problem that obtaining the cellular automata transformation rules is difficult in practice, this paper had proposed transition rules mining method of cellular automata on the basis of ant colony algorithm, and obtain the cellular transition rules automatically by the classification rule mining algorithm. This algorithm had make use of the ant colony algorithm have the characteristics of self-adaptive, positive feedback and swarm intelligence, to improve the intelligence of cellular automata.A new spatial load forecasting method for distribution network based on ant colony algorithm and automata is presented, had introduced the cellular automata during the process of land-use type evolution, so as to achieve the dynamic simulation of planning the land-use type of respective district. In the whole process of spatial load forecasting, according to the idea of"from top to bottom"load distribution of land use based method, gross load will be distributed into each small-area, thus accomplish spatial load forecasting. The applicability and credibility of this method is validated by an actual example, and a novel and practical spatial load forecasting method for distribution network is presented.