Community microgrid scheduling considering building thermal dynamics

Guodong Liu; Michael Starke; Bailu Xiao; Xiaohu Zhang; Kevin Tomsovic

doi:10.1109/PESGM.2017.8274336

Community microgrid scheduling considering building thermal dynamics

Guodong Liu, Michael Starke, Bailu Xiao, Xiaohu Zhang, Kevin Tomsovic

Grid Systems Architecture

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

This paper proposes a scheduling model for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed optimization framework minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point. The heating, ventilation and air-conditioning (HVAC) systems are scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show significant saving in electricity cost by the proposed model.

Original language	English
Title of host publication	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Publisher	IEEE Computer Society
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538622124
DOIs	https://doi.org/10.1109/PESGM.2017.8274336
State	Published - Jan 29 2018
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: Jul 16 2017 → Jul 20 2017

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-January
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Country/Territory	United States
City	Chicago
Period	07/16/17 → 07/20/17

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan(http://energy.gov/downloads/doe-public-access-plan). This work also made use of Engineering Research Center Shared Facilities supported by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program.

Funders	Funder number
CURENT
LLC
National Science Foundation and the Department of Energy
UT-Battelle
National Science Foundation	EEC-1041877

Keywords

Community microgrids
Customer comfort
HVAC
Scheduling
Thermal dynamic model

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10.1109/PESGM.2017.8274336

Cite this

@inproceedings{07d63f5bea7441a69a5eae22b63ee30b,

title = "Community microgrid scheduling considering building thermal dynamics",

abstract = "This paper proposes a scheduling model for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed optimization framework minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point. The heating, ventilation and air-conditioning (HVAC) systems are scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show significant saving in electricity cost by the proposed model.",

keywords = "Community microgrids, Customer comfort, HVAC, Scheduling, Thermal dynamic model",

author = "Guodong Liu and Michael Starke and Bailu Xiao and Xiaohu Zhang and Kevin Tomsovic",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 ; Conference date: 16-07-2017 Through 20-07-2017",

year = "2018",

month = jan,

day = "29",

doi = "10.1109/PESGM.2017.8274336",

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Liu, G , Starke, M, Xiao, B, Zhang, X & Tomsovic, K 2018, Community microgrid scheduling considering building thermal dynamics. in 2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Power and Energy Society General Meeting, vol. 2018-January, IEEE Computer Society, pp. 1-5, 2017 IEEE Power and Energy Society General Meeting, PESGM 2017, Chicago, United States, 07/16/17. https://doi.org/10.1109/PESGM.2017.8274336

Community microgrid scheduling considering building thermal dynamics. / Liu, Guodong ; Starke, Michael; Xiao, Bailu et al.
2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Computer Society, 2018. p. 1-5 (IEEE Power and Energy Society General Meeting; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Community microgrid scheduling considering building thermal dynamics

AU - Liu, Guodong

AU - Starke, Michael

AU - Xiao, Bailu

AU - Zhang, Xiaohu

AU - Tomsovic, Kevin

PY - 2018/1/29

Y1 - 2018/1/29

N2 - This paper proposes a scheduling model for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed optimization framework minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point. The heating, ventilation and air-conditioning (HVAC) systems are scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show significant saving in electricity cost by the proposed model.

AB - This paper proposes a scheduling model for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed optimization framework minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point. The heating, ventilation and air-conditioning (HVAC) systems are scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show significant saving in electricity cost by the proposed model.

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KW - Customer comfort

KW - HVAC

KW - Scheduling

KW - Thermal dynamic model

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M3 - Conference contribution

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BT - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017

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Y2 - 16 July 2017 through 20 July 2017

ER -

Community microgrid scheduling considering building thermal dynamics

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