Optimal co-scheduling of HVAC control and battery management for energy-efficient buildings considering state-of-health degradation

Tiansong Cui, Shuang Chen, Yanzhi Wang, Qi Zhu, Shahin Nazarian, Massoud Pedram

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

The heating, ventilation and air conditioning (HVAC) system accounts for half of the energy consumption of a typical building. Additionally, the need for HVAC changes over hours and days as does the electric energy price. Level of comfort of the building occupants is, however, a primary concern, which tends to overwrite pricing. Dynamic HVAC control under a dynamic energy pricing model while meeting an acceptable level of occupants' comfort is thus critical to achieving energy efficiency in buildings in a sustainable manner. Finally, there is the possibility that the building is equipped with some renewable source of power such as solar panels mounted on the rooftop. The presence of a battery energy storage system in a target building would enable peak power shaving by adopting a suitable charge and discharge schedule for the battery, while simultaneously meeting building energy efficiency and user satisfaction. Achieving this goal requires detailed information (or predictions) about the amount of local power generation from the renewable source plus the power consumption load of the building. This paper addresses the coscheduling problem of HVAC control and battery management to achieve energy-efficient buildings, while also accounting for the degradation of the battery state-of-health during charging and discharging operations (which in turn determines the amortized cost of owning and utilizing a battery storage system)aaȩcč A time-of-use dynamic pricing scenario is assumed and various energy loss components are considered including power dissipation in the power conversion circuitry as well as the rate capacity effect in the battery. A global optimization framework targeting the entire billing cycle is presented and an adaptive co-scheduling algorithm is provided to dynamically update the optimal HVAC air flow control and the battery charging/discharging decision in each time slot during the billing cycle to mitigate the prediction error of unknown parameters. Experimental results show that the proposed algorithm achieves up to 15% in the total electric utility cost reduction compared with some baseline methods.

Original languageEnglish (US)
Title of host publication2016 21st Asia and South Pacific Design Automation Conference, ASP-DAC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages775-780
Number of pages6
ISBN (Electronic)9781467395694
DOIs
StatePublished - Mar 7 2016
Event21st Asia and South Pacific Design Automation Conference, ASP-DAC 2016 - Macao, Macao
Duration: Jan 25 2016Jan 28 2016

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
Volume25-28-January-2016

Other

Other21st Asia and South Pacific Design Automation Conference, ASP-DAC 2016
CountryMacao
CityMacao
Period1/25/161/28/16

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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    Cui, T., Chen, S., Wang, Y., Zhu, Q., Nazarian, S., & Pedram, M. (2016). Optimal co-scheduling of HVAC control and battery management for energy-efficient buildings considering state-of-health degradation. In 2016 21st Asia and South Pacific Design Automation Conference, ASP-DAC 2016 (pp. 775-780). [7428105] (Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC; Vol. 25-28-January-2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASPDAC.2016.7428105