Title :
Load Forecasting in Demand Response
Author :
Jiang, Haihao ; Tan, Zhenyu
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
This paper establishes a robust model to adjust the hourly load level in response to hourly electricity price of a given consumer .The objective of the model is to maximize the utility of the consumer subject to a minimum daily energy supply level, maximum and minimum hourly demand levels, and ramping limits on such demand levels. Unknown price is forecasted through neural network with a confidence interval. A simple bidirectional communication device between the power supplier and the consumer enables the achievement of the proposed model. Numerical simulations are provided.
Keywords :
demand side management; forecasting theory; load forecasting; neural nets; numerical analysis; power markets; bidirectional communication device; confidence interval; demand response; hourly electricity price; hourly load level adjustment; load forecasting; maximum hourly demand levels; minimum daily energy supply level; minimum hourly demand levels; neural network; numerical simulations; power supplier; robust model; unknown price forecasting; utility maximization; Electricity; Forecasting; Load management; Load modeling; Predictive models; Robustness; Smart grids;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0545-8
DOI :
10.1109/APPEEC.2012.6307716
