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VPeak: exploiting volunteer energy resources for flexible peak shaving

Authors:

Phuthipong Bovornkeeratiroj,

Prashant ShenoyAuthors Info & Claims

BuildSys '21: Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

Pages 121 - 130

https://doi.org/10.1145/3486611.3486667

Published: 17 November 2021 Publication History

Abstract

Traditionally, utility companies have employed demand response for large loads or deployed centralized energy storage to alleviate the effects of peak demand on the grid. The advent of Internet of Things (IoT) and the proliferation of networked energy devices have opened up new opportunities for coordinated control of smaller residential loads at large scales to achieve similar benefits. In this paper, we present VPeak, an approach that uses residential loads volunteered by their owners for coordinated control by a utility for grid optimizations. Since the use of volunteer resources comes with hard limits on how frequently they can be used by a remote utility, we present machine learning techniques for carefully selecting which days to operate these loads based on expected peak demand. VPeak uses a distributed and heterogeneous pool of volunteer loads to implement flexible peak shaving that can either selectively target hotspots within the distribution network or perform grid-wide peak shaving. Our results show that VPeak is able to shave up to 26% of the total demand when selectively shaving peaks at local hotspots and up to 46.7% of the demand for grid-wide peak shaving.

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Cited By

Wamburu JLee SIyengar SIrwin DShenoy P(2024)Analyzing the Energy Usage of a Community and the Benefits of Energy StorageACM Journal on Computing and Sustainable Societies10.1145/36372092:2(1-23)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3637209
Deng XZhang YJiang YZhang YQi H(2024)A novel operation method for renewable building by combining distributed DC energy system and deep reinforcement learningApplied Energy10.1016/j.apenergy.2023.122188353(122188)Online publication date: Jan-2024
https://doi.org/10.1016/j.apenergy.2023.122188
Bovornkeeratiroj PBashir NDeulkar VBalaji BShenoy PIrwin DHajiesmaili M(2023)Quantifying the Decarbonization Potential of Flexible LoadProceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3600100.3626346(429-433)Online publication date: 15-Nov-2023
https://dl.acm.org/doi/10.1145/3600100.3626346
Show More Cited By

Index Terms

VPeak: exploiting volunteer energy resources for flexible peak shaving
1. Applied computing
  1. Operations research
    1. Forecasting
2. Hardware
  1. Power and energy
    1. Energy distribution
      1. Smart grid

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Published In

cover image ACM Conferences

BuildSys '21: Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

November 2021

388 pages

ISBN:9781450391146

DOI:10.1145/3486611

General Chair:
Xiaofan (Fred) Jiang
Columbia University
,
Program Chairs:
Omprakash Gnawali
University of Houston
,
Zoltan Nagy
The University of Texas Austin

Copyright © 2021 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 the author(s) 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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SIGEnergy: ACM Special Interest Group on Energy Systems and Informatics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 November 2021

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National Science Foundation

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BuildSys '21

Sponsor:

SIGEnergy

BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

November 17 - 18, 2021

Coimbra, Portugal

Acceptance Rates

BuildSys '21 Paper Acceptance Rate 28 of 107 submissions, 26%;

Overall Acceptance Rate 148 of 500 submissions, 30%

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Cited By

Wamburu JLee SIyengar SIrwin DShenoy P(2024)Analyzing the Energy Usage of a Community and the Benefits of Energy StorageACM Journal on Computing and Sustainable Societies10.1145/36372092:2(1-23)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3637209
Deng XZhang YJiang YZhang YQi H(2024)A novel operation method for renewable building by combining distributed DC energy system and deep reinforcement learningApplied Energy10.1016/j.apenergy.2023.122188353(122188)Online publication date: Jan-2024
https://doi.org/10.1016/j.apenergy.2023.122188
Bovornkeeratiroj PBashir NDeulkar VBalaji BShenoy PIrwin DHajiesmaili M(2023)Quantifying the Decarbonization Potential of Flexible LoadProceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3600100.3626346(429-433)Online publication date: 15-Nov-2023
https://dl.acm.org/doi/10.1145/3600100.3626346
Zakaria CYilmaz GMammen PChee MShenoy PBalan R(2023)SleepMoreProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35694896:4(1-32)Online publication date: 11-Jan-2023
https://dl.acm.org/doi/10.1145/3569489

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