NDLI: A comparison of day-ahead wholesale market: Social welfare vs industrial demand side management

Content Provider	IEEE Xplore Digital Library
Author	Bo Jiang Farid, A.M. Youcef-Toumi, K.
Copyright Year	2015
Description	Author affiliation: Eng. Syst. & Manage., Masdar Inst. of Sci. & Technol., Abu Dhabi, United Arab Emirates (Farid, A.M.) \|\| Mech. Eng. Dept., Massachusetts Inst. of Technol., Cambridge, MA, USA (Bo Jiang; Youcef-Toumi, K.)
Abstract	The intermittent nature of renewable energy has been discussed in the context of the operational challenges that it brings to electrical grid reliability. In contrast, Demand Side Management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has often been recognized as an efficient way to mitigate the variable effects of renewable energy. However, the industrial & academic literature have taken divergent approaches to DSM implementation. Academic studies often implement demand side management on the basis of a social welfare maximization. Meanwhile, industrial implementations minimize total system costs where customers are compensated for load reductions from a predefined baseline of electricity consumption that would have occurred without DSM. This paper rigorously compares these two different approaches in a day-ahead wholesale market context using the same system configuration and mathematical formalism. The comparison showed that a proper reconciliation between the dispatchable demand utility function and the load reduction cost function lead to fundamentally the same stochastic netload mitigation and the two DSM models generate the same dispatch results under specific conditions. However, while the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms, and is thus more prone to error and more likely requires more control activity in subsequent layers of enterprise control.
Starting Page	2742
Ending Page	2749
File Size	781528
Page Count	8
File Format	PDF
ISBN	9781479978007
DOI	10.1109/ICIT.2015.7125502
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-17
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Generators Mathematical model Stochastic processes Load modeling Biological system modeling Cost function
Content Type	Text
Resource Type	Article

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