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 contribution

3 Citations (Scopus)
104 Downloads (Pure)

Abstract

In this paper the challenges of creating accurate, scalable and usable energy demand models are discussed, along with a review of simulation and data driven energy demand models. Seminal 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 (HMM) and Generalised Pareto (HMM-GP) methodology for simulating synthetic electrical demand profiles is validated for residential buildings at five minute resolution. Utilising building simulation software, IES-VE, dynamic thermal demand modelling for varying archetypes using hourly data is also evaluated against in-situ thermal measurements.
Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems (ISCAS)
PublisherIEEE
ISBN (Electronic)9781538648810
DOIs
Publication statusPublished - 4 May 2018
Event2018 IEEE International Symposium on Circuits and Systems - Florence Congress Centre, Florence, Italy
Duration: 27 May 201830 May 2018
http://www.iscas2018.org/

Publication series

NameIEEE International Symposium on Circuits and Systems (ISCAS)
PublisherIEEE
ISSN (Electronic)2379-447X

Conference

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

Keywords

  • ENERGY DEMAND
  • Data analysis
  • energy system

Fingerprint

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

Cite this