Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models

Alessandro Di Giorgio and Francesco Liberati

Applied Energy, 2014, vol. 128, issue C, 119-132

Abstract: This paper presents an event driven model predictive control approach for a local energy management system, enabling residential consumers to the automated participation in demand side management (DSM) programs. We consider a household equipped with smart appliances, a storage unit, electric vehicles and photovoltaic micro-generation. Resources are coordinated according to the needs of maximizing self-consumption and minimizing the cost of energy consumption, in a contractual scenario characterized by designed or market indexed pricing models, with DSM options. The control action (appliances’ start times, the storage charging profile and the IEC 61851 compliant charging profile of the electric vehicles) is updated every time an event triggers the controller, such as a user request, a price/volume signal or the notification of a new forecast of micro-generation from the photovoltaic unit. The control framework is flexible enough to meet the real dynamics of a household and short-term grid requirements, while taking into account user preferences, contractual and technical constraints. A proper set of simulations validates the proposed approach.

Keywords: Automated demand side management; Event driven model predictive control; Smart household appliance; Electric vehicle; IEC 61851; Micro-generation (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (43)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261914003857
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:128:y:2014:i:c:p:119-132

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.2014.04.032

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 ().