Journal
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
Volume 55, Issue 6, Pages 7008-7014Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2019.2938481
Keywords
Battery management system (BMS); demand management; heating ventilation air conditioning (HVAC) modeling; HVAC scheduling; model predictive control (MPC)
Funding
- Con Edison Battery Storage solutions
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This article will discuss and simulate a demand management algorithm in a building with a battery energy storage system (BESS) and heating ventilation air conditioning (HVAC) scheduling using the model predictive control (MPC). Behind-the-meter energy storage system is used for modifying the load shape andminimizing the demand charge of a building. The thermal mass of the building can also be utilized to store the heat/cool energy and HVAC is scheduled to minimize power consumption during peak times. Initially, this article works with optimizing BESS using MPC and compares the results with those of regular optimization. Later HVAC is modeled mathematically to be able to use in optimization. Finally, this article will co-optimize the battery and HVAC schedule minimizing the annual electricity bill without causing thermal discomfort to the residents of the building. The platform has been simulated on a sample building modeled in Energy Plus.
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