Paper
Field Programmable Gate Array based Smart System for Short Term Electric Load Forecasting and Load Scheduling for Smart Grid Applications
- Authors:
- Shubhajit Roy Chowdhury; Varun Ramchandani
- Abstract
- The paper proposes Field Programmable Gate Array (FPGA) implementation of a novel algorithm for short term electric load estimation and hardware implementation of load scheduling algorithm from the dataset generated by load estimation algorithm. The algorithm proposed in this paper uses load consumption and temperature of previous few days as parameters for estimation and this forecasted data is used for scheduling purpose. The information of load consumption can be obtained from smart meters already installed in smart grid. Estimation is done separately for Weekdays & Weekends/Public Holidays. The approach proposed applies all these parameters as coefficients for Kalman Filter algorithm to estimate hourly loads. Using the proposed algorithm the load was estimated with absolute mean percentage error of as low as 1%, which is better than using Artificial Neural Network technique where the absolute mean percentage error has been found to be around 2.2%, and the algorithm for load scheduling has been successfully implemented on the logic of FPGA.
- Keywords
- Load Forecasting; Load Scheduling; Kalman Filter; Mean Absolute Percentage Error (MAPE); Smart Grid; FPGA
- StartPage
- 127
- EndPage
- 140
- Doi