A novel multi-market optimization problem for commercial heating, ventilation, and air-conditioning systems providing ancillary services using multi-zone inverse comprehensive room transfer functions. (17th August 2016)

• Record Type: Journal Article
• Authors: Blum, David H.; Xu, Nora; Norford, Leslie K.
• Is Part Of: Science and technology for the built environment. Volume 22:Number 6(2016)
• Page Start: 783
• Page End: 797
• Publication Date: 2016-08-17
• Subjects: Heating -- Periodicals; Ventilation -- Periodicals; Air conditioning -- Periodicals; Refrigeration and refrigerating machinery -- Periodicals; Indoor air quality -- Periodicals; Indoor air quality; Air conditioning; Heating; Refrigeration and refrigerating machinery; Ventilation; Periodicals; 697
• DOI: 10.1080/23744731.2016.1197718
• Languages: English
• ISSNs: 2374-474X

Abstract

Abstract : Electricity grids increasingly include demand response in not only the energy market, but also grid-stabilizing ancillary services markets. Commercial buildings can provide demand response through use of their heating, ventilating, and air-conditioning systems to access the buildings' thermal storage capacity. Within a model predictive control framework, commercial buildings can optimize demand response while respecting thermal comfort and system limits. In this article, a novel multi-market optimization problem that minimizes total operating costs, including energy costs, and separate revenues from regulation and reserve markets, is proposed. The 24-hour multi-zone and multi-market optimization problem is solved using a multi-zone inverse comprehensive room transfer function model of an 18-zone office building and accompanying variable air volume heating, ventilating, and air-conditioning system model. Optimal energy use, ancillary service provision, energy cost, and ancillary service revenues are reported for eight scenarios, which highlight the impact of ancillary service provision on optimal energy use and the effect of thermal mass on demand response provision. This work improves the operating capabilities of an individual building using model predictive control and can also be used to better understand demand-side resource potential for energy and ancillary services from a grid-planning perspective.