Optimal electricity rate structures for peak demand reduction using economic model predictive control

Wesley J. Cole; David P. Morton; Thomas F. Edgar

doi:10.1016/j.jprocont.2014.04.014

Optimal electricity rate structures for peak demand reduction using economic model predictive control

Wesley J. Cole^*, David P. Morton, Thomas F. Edgar

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

Economic model predictive control (EMPC) has recently gained popularity for managing energy consumption in buildings that are exposed to non-constant electricity prices, such as time-of-use prices or real-time prices. These electricity prices are employed directly in the objective function of the EMPC problem. This paper considers how electricity prices can be designed in order to achieve a specific objective, which in this case is minimizing peak electricity demand. A primal-dual formulation of the EMPC problem is presented that is used to determine optimal prices that minimize peak demand. The method is demonstrated on a simulated community of 900 residential homes to create a pricing structure that minimizes the peak demand of the community of homes. The pricing structure shows that homes should be given a 1-h peak demand duration, and that the peak prices given to the homes should be spread unevenly across 6 h of the afternoon.

Original language	English (US)
Pages (from-to)	1311-1317
Number of pages	7
Journal	Journal of Process Control
Volume	24
Issue number	8
DOIs	https://doi.org/10.1016/j.jprocont.2014.04.014
State	Published - Aug 2014

Funding

The authors thank the Pecan Street Research Institute for the smart grid demonstration research data used in creating the community of homes, and Bo Lu, Josh Rhodes, and Matt Walters for helpful discussions. This material is based upon work supported by the National Science Foundation (NSF) Graduate Research Fellowship under Grant no. DGE-1110007 and NSF Grant no. 1162328 . Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Keywords

Critical peak pricing
Demand response
Duality
Economic model predictive control
Inverse optimization
Peak demand
Residential air conditioning

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Computer Science Applications
Industrial and Manufacturing Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jprocont.2014.04.014

Cite this

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title = "Optimal electricity rate structures for peak demand reduction using economic model predictive control",

abstract = "Economic model predictive control (EMPC) has recently gained popularity for managing energy consumption in buildings that are exposed to non-constant electricity prices, such as time-of-use prices or real-time prices. These electricity prices are employed directly in the objective function of the EMPC problem. This paper considers how electricity prices can be designed in order to achieve a specific objective, which in this case is minimizing peak electricity demand. A primal-dual formulation of the EMPC problem is presented that is used to determine optimal prices that minimize peak demand. The method is demonstrated on a simulated community of 900 residential homes to create a pricing structure that minimizes the peak demand of the community of homes. The pricing structure shows that homes should be given a 1-h peak demand duration, and that the peak prices given to the homes should be spread unevenly across 6 h of the afternoon.",

keywords = "Critical peak pricing, Demand response, Duality, Economic model predictive control, Inverse optimization, Peak demand, Residential air conditioning",

author = "Cole, {Wesley J.} and Morton, {David P.} and Edgar, {Thomas F.}",

note = "Funding Information: The authors thank the Pecan Street Research Institute for the smart grid demonstration research data used in creating the community of homes, and Bo Lu, Josh Rhodes, and Matt Walters for helpful discussions. This material is based upon work supported by the National Science Foundation (NSF) Graduate Research Fellowship under Grant no. DGE-1110007 and NSF Grant no. 1162328 . Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Copyright: Copyright 2014 Elsevier B.V., All rights reserved.",

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N2 - Economic model predictive control (EMPC) has recently gained popularity for managing energy consumption in buildings that are exposed to non-constant electricity prices, such as time-of-use prices or real-time prices. These electricity prices are employed directly in the objective function of the EMPC problem. This paper considers how electricity prices can be designed in order to achieve a specific objective, which in this case is minimizing peak electricity demand. A primal-dual formulation of the EMPC problem is presented that is used to determine optimal prices that minimize peak demand. The method is demonstrated on a simulated community of 900 residential homes to create a pricing structure that minimizes the peak demand of the community of homes. The pricing structure shows that homes should be given a 1-h peak demand duration, and that the peak prices given to the homes should be spread unevenly across 6 h of the afternoon.

AB - Economic model predictive control (EMPC) has recently gained popularity for managing energy consumption in buildings that are exposed to non-constant electricity prices, such as time-of-use prices or real-time prices. These electricity prices are employed directly in the objective function of the EMPC problem. This paper considers how electricity prices can be designed in order to achieve a specific objective, which in this case is minimizing peak electricity demand. A primal-dual formulation of the EMPC problem is presented that is used to determine optimal prices that minimize peak demand. The method is demonstrated on a simulated community of 900 residential homes to create a pricing structure that minimizes the peak demand of the community of homes. The pricing structure shows that homes should be given a 1-h peak demand duration, and that the peak prices given to the homes should be spread unevenly across 6 h of the afternoon.

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KW - Peak demand

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Optimal electricity rate structures for peak demand reduction using economic model predictive control

Abstract

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Keywords

ASJC Scopus subject areas

UN SDGs

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