Load forecasting and demand response

Demand response is a reduction in the consumption of electricity by customers from their expected consumption in response to reliability or price triggered signals. Enabled by advanced metering infrastructure and other smart grid technologies, it is expected to be a crucial mechanism to compensate s...

Full description

Saved in:
Bibliographic Details
Published inIEEE PES General Meeting pp. 1 - 3
Main Authors Luh, Peter B, Michel, L D, Friedland, P, Che Guan, Yuting Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2010
Subjects
advanced metering infrastructure
Artificial neural networks
demand response
Electricity
Forecasting
Load forecasting
Load management
multi-level wavelet neural network methods
online stochastic optimization
Optimization
smart grid
Weather forecasting
Online AccessGet full text

Cover

More Information
Summary:Demand response is a reduction in the consumption of electricity by customers from their expected consumption in response to reliability or price triggered signals. Enabled by advanced metering infrastructure and other smart grid technologies, it is expected to be a crucial mechanism to compensate system uncertainties and the associated risks including those related to intermittent renewable generation such as wind or solar. In this paper, challenges associated with load forecasting and demand response are discussed. To address the challenges, our key ideas are to (1) forecast load together with corresponding confidence intervals having additional price-related input variables; and (2) use online stochastic optimization together with very-short-term load forecasting results to find effective and robust solutions to manage both dispatchable and non-dispatchable demand response.
ISBN:1424465494
9781424465491
ISSN:1932-5517
DOI:10.1109/PES.2010.5590062