Optimal sizing of energy storage for community microgrids considering building thermal dynamics

Guodong Liu; Zhi Li; Michael Starke; Thomas B. Ollis; Kevin Tomsovic

doi:10.1109/PESGM.2017.8274700

Optimal sizing of energy storage for community microgrids considering building thermal dynamics

Guodong Liu, Zhi Li, Michael Starke, Thomas B. Ollis, Kevin Tomsovic

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

3 Scopus citations

Abstract

This paper proposes an optimization model for the sizing of energy storage for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost, and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, heating, ventilation and air-conditioning (HVaC) systems are assumed to be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings has been integrated into the optimization model. Numerical simulations show significant cost reduction with the proposed model. The impacts of various costs on the optimal solution are investigated through sensitivity analysis.

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.2017.8274700
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.

Keywords

Community microgrid
Customer comfort
Energy storage sizing
HVaC
Thermal dynamic model

Access to Document

10.1109/PESGM.2017.8274700

Cite this

Liu, G., Li, Z., Starke, M., Ollis, T. B., & Tomsovic, K. (2018). Optimal sizing of energy storage for community microgrids considering building thermal dynamics. In 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 (pp. 1-5). (IEEE Power and Energy Society General Meeting; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/PESGM.2017.8274700

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title = "Optimal sizing of energy storage for community microgrids considering building thermal dynamics",

abstract = "This paper proposes an optimization model for the sizing of energy storage for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost, and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, heating, ventilation and air-conditioning (HVaC) systems are assumed to be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings has been integrated into the optimization model. Numerical simulations show significant cost reduction with the proposed model. The impacts of various costs on the optimal solution are investigated through sensitivity analysis.",

keywords = "Community microgrid, Customer comfort, Energy storage sizing, HVaC, Thermal dynamic model",

author = "Guodong Liu and Zhi Li and Michael Starke and Ollis, {Thomas B.} 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",

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day = "29",

doi = "10.1109/PESGM.2017.8274700",

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Liu, G, Li, Z, Starke, M , Ollis, TB & Tomsovic, K 2018, Optimal sizing of energy storage for community microgrids 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.2017.8274700

Optimal sizing of energy storage for community microgrids considering building thermal dynamics. / Liu, Guodong; Li, Zhi; Starke, Michael 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

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AU - Tomsovic, Kevin

PY - 2018/1/29

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N2 - This paper proposes an optimization model for the sizing of energy storage for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost, and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, heating, ventilation and air-conditioning (HVaC) systems are assumed to be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings has been integrated into the optimization model. Numerical simulations show significant cost reduction with the proposed model. The impacts of various costs on the optimal solution are investigated through sensitivity analysis.

AB - This paper proposes an optimization model for the sizing of energy storage for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost, and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, heating, ventilation and air-conditioning (HVaC) systems are assumed to be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings has been integrated into the optimization model. Numerical simulations show significant cost reduction with the proposed model. The impacts of various costs on the optimal solution are investigated through sensitivity analysis.

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KW - Customer comfort

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Optimal sizing of energy storage for community microgrids considering building thermal dynamics

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