One for all, all for one: A scalable decision-making framework for demand response with a district cooling plant

Srinarayana Nagarathinam, Harihara Subrahmaniam Muralidharan, Arunchandar Vasan, Venkatesh Sarangan, Sermisha Narayana, Anand Sivasubramaniam

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

Abstract

During demand response events, utility customers typically make decisions to reduce their own load independent of other customers. In the presence of district cooling with a centralized cooling plant, the control decisions of buildings and the district cooling plant become coupled, since the setpoints chosen by the cooling plant affect the consumption of the buildings and vice versa. While past works on demand response address control of building-level heating and cooling systems, control of such systems in the presence of district cooling has not received much attention. We consider the problem of minimizing the discomfort of buildings while meeting the target demand reduction. Specifically, we identify the optimal setpoints for the buildings and district cooling plant, even while obeying the non-linear, coupled thermodynamic constraints between the district cooling plant and buildings. We propose a novel solution strategy using domain knowledge that transforms the complex non-linear optimization problem to a series of quadratic programming which can be then solved conventionally. We validate the performance of the proposed strategy by comparing it with a combinatorial brute-force solution on a small data set. We also evaluate the performance of our strategy on a real-world data set of 416 buildings that are served by a district cooling plant. The results indicate that including the district plant in demand response and solving with the coupled constraints, allows the utility to meet higher target reductions for the same comfort levels. Also, the proposed solution strategy is both fast (at least 4x) and scalable (35x) when compared with conventional optimization solvers.

Original languageEnglish (US)
Title of host publicationBuildSys 2019 - Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
PublisherAssociation for Computing Machinery, Inc
Pages277-286
Number of pages10
ISBN (Electronic)9781450370059
DOIs
StatePublished - Nov 13 2019
Event6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2019 - New York, United States
Duration: Nov 13 2019Nov 14 2019

Publication series

NameBuildSys 2019 - Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

Conference

Conference6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2019
CountryUnited States
CityNew York
Period11/13/1911/14/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Renewable Energy, Sustainability and the Environment
  • Building and Construction
  • Architecture
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'One for all, all for one: A scalable decision-making framework for demand response with a district cooling plant'. Together they form a unique fingerprint.

Cite this