Demand response through smart home energy management using thermal inertia

Haiming Wang; Ke Meng; Fengji Luo; Zhao Yang Dong; Gregor Verbič; Zhao Xu; K. P. Wong

Demand response through smart home energy management using thermal inertia

Haiming Wang
, Ke Meng
, Fengji Luo
, Zhao Yang Dong
, Gregor Verbič
, Zhao Xu
, K. P. Wong

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

66 Citations (Scopus)

Abstract

In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid.

Original language	English
Title of host publication	2013 Australasian Universities Power Engineering Conference, AUPEC 2013
Publication status	Published - 1 Dec 2013
Event	2013 Australasian Universities Power Engineering Conference, AUPEC 2013 - Hobart, TAS, Australia Duration: 29 Sept 2013 → 3 Oct 2013

Conference

Conference	2013 Australasian Universities Power Engineering Conference, AUPEC 2013
Country/Territory	Australia
City	Hobart, TAS
Period	29/09/13 → 3/10/13

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Demand Response
Mixed Integer Linear Programming
Smart Home Energy Management System
Thermal Inertia

ASJC Scopus subject areas

Energy Engineering and Power Technology
Fuel Technology

Cite this

@inproceedings{077585bc2ab248f7a81521e9c68cc715,

title = "Demand response through smart home energy management using thermal inertia",

abstract = "In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid.",

keywords = "Demand Response, Mixed Integer Linear Programming, Smart Home Energy Management System, Thermal Inertia",

author = "Haiming Wang and Ke Meng and Fengji Luo and Dong, \{Zhao Yang\} and Gregor Verbi{\v c} and Zhao Xu and Wong, \{K. P.\}",

year = "2013",

month = dec,

day = "1",

language = "English",

isbn = "9781862959132",

booktitle = "2013 Australasian Universities Power Engineering Conference, AUPEC 2013",

note = "2013 Australasian Universities Power Engineering Conference, AUPEC 2013 ; Conference date: 29-09-2013 Through 03-10-2013",

}

TY - GEN

T1 - Demand response through smart home energy management using thermal inertia

AU - Wang, Haiming

AU - Meng, Ke

AU - Luo, Fengji

AU - Dong, Zhao Yang

AU - Verbič, Gregor

AU - Xu, Zhao

AU - Wong, K. P.

PY - 2013/12/1

Y1 - 2013/12/1

N2 - In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid.

AB - In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid.

KW - Demand Response

KW - Mixed Integer Linear Programming

KW - Smart Home Energy Management System

KW - Thermal Inertia

UR - https://www.scopus.com/pages/publications/84894427543

M3 - Conference article published in proceeding or book

SN - 9781862959132

BT - 2013 Australasian Universities Power Engineering Conference, AUPEC 2013

T2 - 2013 Australasian Universities Power Engineering Conference, AUPEC 2013

Y2 - 29 September 2013 through 3 October 2013

ER -

Demand response through smart home energy management using thermal inertia

Abstract

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

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Cite this