Effect of Load Contribution Factor on Multinodal Load Forecasting

This paper discusses a load contribution factor (LCF) based multinodal load forecasting technique. The dynamic nature of the electrical load in any distribution network is the reason behind the need for simultaneous forecasting of load at all the nodes. In a small distribution system, the load at different nodes is interdependent to each other, and also all the nodes are located at similar physical locations and hence loads cannot be distinguished based on weather parameters. Due to this, multinodal load forecasting becomes a tough job. This problem is solved by using LCF for training the load forecasting model along with the other exogenous factors. LCF is calculated for each node depending upon the past trend of load at that node at any particular instant and the total load of the system. Results of the proposed method produce accurate and consistent multinodal load forecasting performance for the real-time smart-metered data available at the residential academic campus grid.