Load Forecasting in Demand Response

Author

Jiang, Haihao ; Tan, Zhenyu

Author_Institution

Dept. of Electr. Eng., Tsinghua Univ., Beijing, China

fYear

2012

fDate

27-29 March 2012

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific

Conference_Location

Shanghai

ISSN

2157-4839

Print_ISBN

978-1-4577-0545-8

Type

conf

DOI

10.1109/APPEEC.2012.6307716

Filename

6307716