The Use of Demand Modelling for Community Energy Analysis

Peter McCallum, Sandhya Patidar, David Jenkins, Andrew Peacock, Valentin Robu, Merlinda Andoni, David Flynn

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)

Abstract

In this paper the challenges of creating accurate, scalable and usable energy demand models are discussed, in the context of existing simulation and data driven energy demand models. Results from high resolution bottom-up data and simulation-based energy demand analysis from a community energy project are provided. A novel Hidden Markov Modelling and Generalised Pareto (HMM-GP) methodology for simulating synthetic electrical demand profiles is validated for residential buildings at a temporal resolution of five minutes. The corresponding dynamic thermal demands for the various building archetypes within the community are also modelled. This is achieved using automated externally driven IES-VE (building simulation) models for arrays of control profiles, and is also compared against in-situ thermal measurements.
Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Subtitle of host publicationProceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages1-5
Number of pages5
ISBN (Electronic)978-1-5386-4881-0
DOIs
Publication statusPublished - 4 May 2018
Externally publishedYes
Event2018 IEEE International Symposium on Circuits and Systems (ISCAS 2018) - Florence Conference Center, Florence, Italy
Duration: 27 May 201830 May 2018
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8334884

Conference

Conference2018 IEEE International Symposium on Circuits and Systems (ISCAS 2018)
Abbreviated titleISCAS 2018
Country/TerritoryItaly
CityFlorence
Period27/05/1830/05/18
Internet address

Keywords

  • aggreation
  • data analysis
  • energy demand
  • thermal modelling

Fingerprint

Dive into the research topics of 'The Use of Demand Modelling for Community Energy Analysis'. Together they form a unique fingerprint.

Cite this