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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 optimal sizing of energy storage in 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, we assume the heating, ventilation and air-conditioning (HVAC) systems can 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 have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2]
  1. ORNL
  2. University of Tennessee, Knoxville (UTK)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Electricity (OE)
OSTI Identifier:
1376357
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 2017 IEEE Power and Energy Society General Meeting - Chicago, Illinois, United States of America - 7/16/2017 12:00:00 AM-7/20/2017 12:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Liu, Guodong, Li, Zhi, Starke, Michael R., Ollis, Ben, and Tomsovic, Kevin. Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics. United States: N. p., 2017. Web. doi:10.1109/PESGM.2017.8274700.
Liu, Guodong, Li, Zhi, Starke, Michael R., Ollis, Ben, & Tomsovic, Kevin. Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics. United States. https://doi.org/10.1109/PESGM.2017.8274700
Liu, Guodong, Li, Zhi, Starke, Michael R., Ollis, Ben, and Tomsovic, Kevin. 2017. "Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics". United States. https://doi.org/10.1109/PESGM.2017.8274700. https://www.osti.gov/servlets/purl/1376357.
@article{osti_1376357,
title = {Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics},
author = {Liu, Guodong and Li, Zhi and Starke, Michael R. and Ollis, Ben and Tomsovic, Kevin},
abstractNote = {This paper proposes an optimization model for the optimal sizing of energy storage in 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, we assume the heating, ventilation and air-conditioning (HVAC) systems can 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 have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.},
doi = {10.1109/PESGM.2017.8274700},
url = {https://www.osti.gov/biblio/1376357}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {7}
}

Conference:
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