Residential demand response scheduling with multiclass appliances in the smart grid

Hee Tae Roh, Jang Won Lee

Research output: Contribution to journalArticle

60 Citations (Scopus)

Abstract

In this paper, we study an electricity load scheduling problem in a residence. Compared with previous works in which only limited sets of appliances are considered, we classify various appliances into five sets considering their different energy consumption and operation characteristics, and provide mathematical models for them. With these appliance models, we propose an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit. The optimization problem is formulated as a mixed integer nonlinear programming (MINLP) problem, which is in general, difficult to solve. In order to solve the problem, we use the generalized Benders decomposition approach with which we can solve the MINLP problem easily with low computational complexity. By solving the problem, we provide an algorithm to obtain the optimal electricity load scheduling of various appliances with different energy consumption and operation characteristics in a unified way.

Original languageEnglish
Article number7152979
Pages (from-to)94-104
Number of pages11
JournalIEEE Transactions on Smart Grid
Volume7
Issue number1
DOIs
Publication statusPublished - 2016 Jan 1

Fingerprint

Energy utilization
Electricity
Scheduling
Nonlinear programming
Scheduling algorithms
Computational complexity
Mathematical models
Decomposition
Costs

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

@article{0c5f331e0047412a9483369caebf845a,
title = "Residential demand response scheduling with multiclass appliances in the smart grid",
abstract = "In this paper, we study an electricity load scheduling problem in a residence. Compared with previous works in which only limited sets of appliances are considered, we classify various appliances into five sets considering their different energy consumption and operation characteristics, and provide mathematical models for them. With these appliance models, we propose an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit. The optimization problem is formulated as a mixed integer nonlinear programming (MINLP) problem, which is in general, difficult to solve. In order to solve the problem, we use the generalized Benders decomposition approach with which we can solve the MINLP problem easily with low computational complexity. By solving the problem, we provide an algorithm to obtain the optimal electricity load scheduling of various appliances with different energy consumption and operation characteristics in a unified way.",
author = "Roh, {Hee Tae} and Lee, {Jang Won}",
year = "2016",
month = "1",
day = "1",
doi = "10.1109/TSG.2015.2445491",
language = "English",
volume = "7",
pages = "94--104",
journal = "IEEE Transactions on Smart Grid",
issn = "1949-3053",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

Residential demand response scheduling with multiclass appliances in the smart grid. / Roh, Hee Tae; Lee, Jang Won.

In: IEEE Transactions on Smart Grid, Vol. 7, No. 1, 7152979, 01.01.2016, p. 94-104.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Residential demand response scheduling with multiclass appliances in the smart grid

AU - Roh, Hee Tae

AU - Lee, Jang Won

PY - 2016/1/1

Y1 - 2016/1/1

N2 - In this paper, we study an electricity load scheduling problem in a residence. Compared with previous works in which only limited sets of appliances are considered, we classify various appliances into five sets considering their different energy consumption and operation characteristics, and provide mathematical models for them. With these appliance models, we propose an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit. The optimization problem is formulated as a mixed integer nonlinear programming (MINLP) problem, which is in general, difficult to solve. In order to solve the problem, we use the generalized Benders decomposition approach with which we can solve the MINLP problem easily with low computational complexity. By solving the problem, we provide an algorithm to obtain the optimal electricity load scheduling of various appliances with different energy consumption and operation characteristics in a unified way.

AB - In this paper, we study an electricity load scheduling problem in a residence. Compared with previous works in which only limited sets of appliances are considered, we classify various appliances into five sets considering their different energy consumption and operation characteristics, and provide mathematical models for them. With these appliance models, we propose an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit. The optimization problem is formulated as a mixed integer nonlinear programming (MINLP) problem, which is in general, difficult to solve. In order to solve the problem, we use the generalized Benders decomposition approach with which we can solve the MINLP problem easily with low computational complexity. By solving the problem, we provide an algorithm to obtain the optimal electricity load scheduling of various appliances with different energy consumption and operation characteristics in a unified way.

UR - http://www.scopus.com/inward/record.url?scp=84960328388&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960328388&partnerID=8YFLogxK

U2 - 10.1109/TSG.2015.2445491

DO - 10.1109/TSG.2015.2445491

M3 - Article

VL - 7

SP - 94

EP - 104

JO - IEEE Transactions on Smart Grid

JF - IEEE Transactions on Smart Grid

SN - 1949-3053

IS - 1

M1 - 7152979

ER -