TY - GEN
T1 - Nationwide evaluation of potential energy savings and payback of integrated building and battery energy storage system through model predictive controls
AU - Fontenot, Hannah
AU - Dong, Bing
AU - Aradillaz, Karen
AU - Pineda, Gabriela
AU - Li, Zhaoxuan
AU - Jiang, Tianhui
N1 - Publisher Copyright:
© 2019 Building Simulation Conference Proceedings. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Building-integrated microgrids (BIMGs) are rising in popularity due to their flexibility in incorporating multiple distributed energy resources including renewable energy sources and battery energy storage systems (BESS) and their natural suitability for demand response. To date, there have been almost no studies about the effect of various climate, building type, and electricity prices on BESS's potential for peak load reduction and energy cost savings. In this study, all sixteen U.S. Department of Energy (DOE) commercial reference building types are simulated with weather data from eighty U.S. cities across all eight ASHRAE climate zones using model predictive control (MPC) algorithm and incorporating BESS and varying electricity price schemes for Intelligent Building to Battery (B2B) control. Results show that cities in colder climate zones can expect up to 3% greater cost and demand savings than in hotter climate zones; additionally, cities with time-of-use price scheme can expect up to 60% shorter payback period than those with tiered prices.
AB - Building-integrated microgrids (BIMGs) are rising in popularity due to their flexibility in incorporating multiple distributed energy resources including renewable energy sources and battery energy storage systems (BESS) and their natural suitability for demand response. To date, there have been almost no studies about the effect of various climate, building type, and electricity prices on BESS's potential for peak load reduction and energy cost savings. In this study, all sixteen U.S. Department of Energy (DOE) commercial reference building types are simulated with weather data from eighty U.S. cities across all eight ASHRAE climate zones using model predictive control (MPC) algorithm and incorporating BESS and varying electricity price schemes for Intelligent Building to Battery (B2B) control. Results show that cities in colder climate zones can expect up to 3% greater cost and demand savings than in hotter climate zones; additionally, cities with time-of-use price scheme can expect up to 60% shorter payback period than those with tiered prices.
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M3 - Conference contribution
AN - SCOPUS:85104372096
T3 - Building Simulation Conference Proceedings
SP - 1659
EP - 1666
BT - 16th International Conference of the International Building Performance Simulation Association, Building Simulation 2019
A2 - Corrado, Vincenzo
A2 - Fabrizio, Enrico
A2 - Gasparella, Andrea
A2 - Patuzzi, Francesco
PB - International Building Performance Simulation Association
T2 - 16th International Conference of the International Building Performance Simulation Association, Building Simulation 2019
Y2 - 2 September 2019 through 4 September 2019
ER -