Application of Artificial Neural Network in Power System with Examples A Review - Singh, Anamika; Srivastava, M.K (International Journal of Computer Sciences and Engineering, 2018)
Forecasting Power load is a prime function of power system planning and management. However, it has proved to be a complicated task because of many unstable factors. There are a substantial growth rate and application levels of neural network (NN) in the power system. This review paper explores the forecasting methodology derived from the specific neural network. The electric power industries are presently undergoing transformations and extraordinary reforms. The most exciting and probably profitable developments in recent times are growing Artificial Intelligence (AI) usage of techniques. Therefore, this paper takes an overview of NN techniques and their application in power sectors. According to NN growth rate statistics, in certain power system issues, this paper considers the load forecasting, security assessment, economic dispatch, fault diagnosis, and harmonic analysis. The various disadvantages and advantages of NN applications in this aspect, envisaging the major challenges in this field are explained while considering NN applications in the power system operations and control. The comparison is made regarding several published IEEE papers from 1990 onwards until the present date, which clearly showed that this subject has attracted the maximum awareness in the last one decade, concerning; Load forecasting; Fault diagnosis and fault location; Economic Dispatch; Security Assessment; and Transient Stability.