NDLI: Optimal scheduling of demand response events using options valuation methods

Content Provider	IEEE Xplore Digital Library
Author	Tyagi, R. Black, J.W. Petersen, J.
Copyright Year	2011
Description	Author affiliation: GE Global Research, Niskayuna, NY 12309 USA (Tyagi, R.; Black, J.W.) \|\| Georgia Tech, Atlanta, GA 30332 USA (Petersen, J.)
Abstract	Several demand response (DR) programs, such as critical peak pricing (CPP), stipulate that electric utilities may schedule events only a limited number of times per year. Utilities must therefore use these events judiciously in order to maximize their benefits from the DR program. Traditionally, they have used rather simple decision rules to schedule such events (e.g., when temperature exceeds a certain threshold). In this paper, we present an option value approach for determining when to invoke these events. This approach calculates a dynamic threshold value, which represents the option value of deferring the use of one the events for use at any future point in the planning horizon (typically a year or cooling season). This threshold enables utilities to make the decision on whether or not to call an event based on the expected current benefits versus potential future benefits. This paper presents an example based on an actual DR program, which uses a simple, temperature based threshold, and compares it with our option based approach. Our approach can also be applied to any other criteria besides temperature such as reserve margins and generation cost.
Starting Page	1
Ending Page	5
File Size	837594
Page Count	5
File Format	PDF
ISBN	9781457710001
ISSN	19449925
e-ISBN	9781457710025
e-ISBN	9781457710018
DOI	10.1109/PES.2011.6039344
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load management Temperature measurement Pricing Weather forecasting Temperature distribution Schedules Time measurement Option Value Analysis Critical Peak Pricing Demand Response
Content Type	Text
Resource Type	Article

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