Residential load control: Distributed scheduling and convergence with lost AMI messages

Nikolaos Gatsis; Georgios B. Giannakis

doi:10.1109/TSG.2011.2176518

Residential load control: Distributed scheduling and convergence with lost AMI messages

Nikolaos Gatsis, Georgios B. Giannakis

Electrical and Computer Engineering

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

167 Scopus citations

Abstract

This paper deals with load control in a multiple-residence setup. The utility company adopts a cost function representing the cost of providing energy to end-users. Each residential end-user has a base load, two types of adjustable loads, and possibly a storage device. The first load type must consume a specified amount of energy over the scheduling horizon, but the consumption can be adjusted across different slots. The second type does not entail a total energy requirement, but operation away from a user-specified level results in user dissatisfaction. The research issue amounts to minimizing the electricity provider cost plus the total user dissatisfaction, subject to the individual constraints of the loads. The problem can be solved by a distributed subgradient method. The utility company and the end-users exchange information through the Advanced Metering Infrastructure (AMI)-a two-way communication network-in order to converge to the optimal amount of electricity production and the optimal power consumption schedule. The algorithm finds near-optimal schedules even when AMI messages are lost, which can happen in the presence of malfunctions or noise in the communications network. The algorithm amounts to a subgradient iteration with outdated Lagrange multipliers, for which convergence results of wide scope are established.

Original language	English (US)
Article number	6168820
Pages (from-to)	770-786
Number of pages	17
Journal	IEEE Transactions on Smart Grid
Volume	3
Issue number	2
DOIs	https://doi.org/10.1109/TSG.2011.2176518
State	Published - 2012

Bibliographical note

Funding Information:
Manuscript received May 22, 2011; revised September 11, 2011; accepted October 17, 2011. Date of publication March 13, 2012; date of current version May 21, 2012. This work was supported by NSF grants CCF-1016605 and ECCS-1002180; and grant NPRP 09-341-2-128. The material in this paper was presented in part at the 45th Annual Conference on Information Sciences and Systems, Baltimore, MD, March 2011. Paper no. TSG-00186-2011.

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

Keywords

Advanced metering infrastructure
demand-side management
distributed algorithms
energy consumption scheduling
smart grid

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

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10.1109/TSG.2011.2176518

Cite this

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title = "Residential load control: Distributed scheduling and convergence with lost AMI messages",

abstract = "This paper deals with load control in a multiple-residence setup. The utility company adopts a cost function representing the cost of providing energy to end-users. Each residential end-user has a base load, two types of adjustable loads, and possibly a storage device. The first load type must consume a specified amount of energy over the scheduling horizon, but the consumption can be adjusted across different slots. The second type does not entail a total energy requirement, but operation away from a user-specified level results in user dissatisfaction. The research issue amounts to minimizing the electricity provider cost plus the total user dissatisfaction, subject to the individual constraints of the loads. The problem can be solved by a distributed subgradient method. The utility company and the end-users exchange information through the Advanced Metering Infrastructure (AMI)-a two-way communication network-in order to converge to the optimal amount of electricity production and the optimal power consumption schedule. The algorithm finds near-optimal schedules even when AMI messages are lost, which can happen in the presence of malfunctions or noise in the communications network. The algorithm amounts to a subgradient iteration with outdated Lagrange multipliers, for which convergence results of wide scope are established.",

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note = "Funding Information: Manuscript received May 22, 2011; revised September 11, 2011; accepted October 17, 2011. Date of publication March 13, 2012; date of current version May 21, 2012. This work was supported by NSF grants CCF-1016605 and ECCS-1002180; and grant NPRP 09-341-2-128. The material in this paper was presented in part at the 45th Annual Conference on Information Sciences and Systems, Baltimore, MD, March 2011. Paper no. TSG-00186-2011. Copyright: Copyright 2012 Elsevier B.V., All rights reserved.",

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AB - This paper deals with load control in a multiple-residence setup. The utility company adopts a cost function representing the cost of providing energy to end-users. Each residential end-user has a base load, two types of adjustable loads, and possibly a storage device. The first load type must consume a specified amount of energy over the scheduling horizon, but the consumption can be adjusted across different slots. The second type does not entail a total energy requirement, but operation away from a user-specified level results in user dissatisfaction. The research issue amounts to minimizing the electricity provider cost plus the total user dissatisfaction, subject to the individual constraints of the loads. The problem can be solved by a distributed subgradient method. The utility company and the end-users exchange information through the Advanced Metering Infrastructure (AMI)-a two-way communication network-in order to converge to the optimal amount of electricity production and the optimal power consumption schedule. The algorithm finds near-optimal schedules even when AMI messages are lost, which can happen in the presence of malfunctions or noise in the communications network. The algorithm amounts to a subgradient iteration with outdated Lagrange multipliers, for which convergence results of wide scope are established.

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Residential load control: Distributed scheduling and convergence with lost AMI messages

Abstract

Bibliographical note

Keywords

UN SDGs

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