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A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

Vardakas, John S., Zorba, Nizar, Verikoukis, Christos V.·2015·IEEE Communications Surveys & Tutorials
DOI 10.1109/comst.2014.2341586
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Abstract

The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

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Metadata

Authors
Vardakas, J. S., Zorba, N., & Verikoukis, C. V.
Venue
IEEE Communications Surveys & Tutorials
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2015
Volume
17
Issue
1
Pages
152-178
ISSN
  • 1553-877X (ISSN-L)
  • 2373-745X
DOI
10.1109/comst.2014.2341586
OpenAlex
W2082291889
Cited by
953
References
10
FWCI
35.73
Type
journal article
Language
en
Open access
closed
Licence
Funders
  • E2SG project
  • ENIAC Joint Undertaking (296131)
  • Smart-NRG (612254)

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Vardakas, J. S., Zorba, N., & Verikoukis, C. V. (2015). A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/comst.2014.2341586

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