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Incentive design for demand-response based on building constraints: a utility perspective

Authors:

Kundan Kandhway,

Arunchandar Vasan,

Srinarayana Nagarathinam,

Venkatesh Sarangan,

Anand SivasubramaniamAuthors Info & Claims

BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments

Article No.: 29, Pages 1 - 10

https://doi.org/10.1145/3137133.3137142

Published: 08 November 2017 Publication History

Abstract

Electrical utilities offer incentives to their customers to reduce their demand during temporary supply-demand mismatches. While customers would prefer a higher incentive to participate, utilities would prefer to minimize the incentive while achieving a target reduction. Because the incentive affects the bottomline of the utility, identifying the optimal incentive reflecting this trade-off is important.

Several works have focused on how to implement DR in a building, but there has been little work on identifying the optimal incentive from the utility's perspective. We complement existing work with an approach on how a utility can identify the optimal incentive for a set of buildings that it serves, while meeting individual buildings' constraints. To this end, we build Demand-Response Potential (DRP) models that give the economically rational demand reduction of a building as a function of the utility's offered incentive. For handling scalability at the utility level, we approximate the DRP using regression based approach.

We evaluate our approach on the PLUTO dataset of building types and sizes. We find that the DRP varies with building types (from 19% for restaurants to 54% for warehouses). It is typically low for buildings with high thermal inertia; and building types with low individual DRP can contribute significantly in aggregate due to their numbers. Offering non-uniform incentives to different buildings can improve the utility's DR benefit by up to 19% compared to offering uniform incentives.

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Cited By

Frahm MZwickel PWachter JLangner FStrauch PMatthes JHagenmeyer VLehnhoff SIrwin DWang D(2022)Occupant-oriented economic model predictive control for demand response in buildingsProceedings of the Thirteenth ACM International Conference on Future Energy Systems10.1145/3538637.3538864(354-360)Online publication date: 28-Jun-2022
https://dl.acm.org/doi/10.1145/3538637.3538864
Nagarathinam SVasan ASarangan VJayaprakash RSivasubramaniam A(2021)User Placement and Optimal Cooling Energy for Co-working Building SpacesACM Transactions on Cyber-Physical Systems10.1145/34328185:2(1-24)Online publication date: 4-Jan-2021
https://dl.acm.org/doi/10.1145/3432818
Kandhway KSudarsanam DVasan ASarangan V(2019)Optimizing Viral Marketing for Demand Response2019 11th International Conference on Communication Systems & Networks (COMSNETS)10.1109/COMSNETS.2019.8711364(714-719)Online publication date: Jan-2019
https://doi.org/10.1109/COMSNETS.2019.8711364

Index Terms

Incentive design for demand-response based on building constraints: a utility perspective
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis

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Published In

cover image ACM Conferences

BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments

November 2017

292 pages

ISBN:9781450355445

DOI:10.1145/3137133

General Chair:
Kamin Whitehouse
University of Virginia
,
Program Chairs:
Prabal Dutta
University of California, Berkeley
,
Hae Young Noh
Carnegie Mellon University

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 November 2017

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BuildSys '17: The 4th ACM International Conference on Systems for Energy-Efficient Built Environments

November 8 - 9, 2017

Delft, Netherlands

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Cited By

Frahm MZwickel PWachter JLangner FStrauch PMatthes JHagenmeyer VLehnhoff SIrwin DWang D(2022)Occupant-oriented economic model predictive control for demand response in buildingsProceedings of the Thirteenth ACM International Conference on Future Energy Systems10.1145/3538637.3538864(354-360)Online publication date: 28-Jun-2022
https://dl.acm.org/doi/10.1145/3538637.3538864
Nagarathinam SVasan ASarangan VJayaprakash RSivasubramaniam A(2021)User Placement and Optimal Cooling Energy for Co-working Building SpacesACM Transactions on Cyber-Physical Systems10.1145/34328185:2(1-24)Online publication date: 4-Jan-2021
https://dl.acm.org/doi/10.1145/3432818
Kandhway KSudarsanam DVasan ASarangan V(2019)Optimizing Viral Marketing for Demand Response2019 11th International Conference on Communication Systems & Networks (COMSNETS)10.1109/COMSNETS.2019.8711364(714-719)Online publication date: Jan-2019
https://doi.org/10.1109/COMSNETS.2019.8711364

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