Power capacity profile estimation for building heating and cooling in demand-side management

Juan A. Gomez and Miguel F. Anjos

Applied Energy, 2017, vol. 191, issue C, 492-501

Abstract: This paper presents a new methodology for the estimation of power capacity profiles for smart buildings. The capacity profile can be used within a demand-side management system in order to guide the building temperature operation. It provides a trade-off between the quality of service perceived by the end user and the requirements from the grid in a demand-response context. We use a data-fitting approach and a multiclass classifier to compute the required profile to run a set of electric heating and cooling units via an admission control module. Simulation results validate the performance of the proposed methodology under various conditions, and we compare our approach with neural networks in a real-world-based scenario.

Keywords: Smart buildings; Power demand; Residential load sector; Least squares; Parameter estimation; Classification (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261917300740
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:191:y:2017:i:c:p:492-501

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2017.01.064

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().