Title :
Daily average load forecasting using dynamic linear regression
Author :
Azad, Salahuddin A. ; Ali, A. B. M. Shawkat ; Wolfs, Peter
Author_Institution :
Power & Energy Centre, Central Queensland Univ., North Rockhampton, QLD, Australia
Abstract :
Load forecasting plays a vital role in demand management. The primary goal of demand management strategy is to shave the peak load in order to reduce the dependency on the peaking plants and to avoid the overloading of the transmission and distribution equipment. Battery storage can also be utilized for peak shaving by storing excess energy during the off-peak and consuming battery energy during peak hours. For effective battery use, the battery management system must have the accurate forecast of the load demand. This paper proposes a dynamic regression scheme to predict the average daily load of a feeder so that the battery management system can decide the amount of charging and discharging required at each instant. Forecasting of average daily load rather than point forecast of load demand at every hour avoids the complexity of battery scheduling and reduces the computational effort. This paper uses Perth solar city data to showcase the effectiveness of dynamic regression for forecasting future loads.
Keywords :
battery management systems; demand side management; load forecasting; regression analysis; secondary cells; Perth solar city data; battery energy; battery management system; battery scheduling; battery storage; battery use; daily average load forecasting; demand management strategy; distribution equipment; dynamic linear regression; dynamic regression scheme; excess energy; off-peak; peak shaving; peaking plant; transmission equipment; Batteries; Correlation; Electricity; Forecasting; Humidity; Load modeling; Predictive models; battery storage; demand management; load forecasting; peaking shaving;
Conference_Titel :
Computer Science and Engineering (APWC on CSE), 2014 Asia-Pacific World Congress on
Print_ISBN :
978-1-4799-1955-0
DOI :
10.1109/APWCCSE.2014.7053851