Change search
ReferencesLink to record
Permanent link

Direct link
Robust Scheduling of Smart Appliances in Active Apartments With User Behavior Uncertainty
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-4210-8672
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-1835-2963
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2015 (English)In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 13, no 1, 247-259 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a robust approach for scheduling of smart appliances and electrical energy storages (EESs) in active apartments with the aim of reducing both the electricity bill and the CO2 emissions. The proposed robust formulation takes the user behavior uncertainty into account so that the optimal appliances schedule is less sensitive to unpredictable changes in user preferences. The user behavior uncertainty is modeled as uncertainty in the cost function coefficients. In order to reduce the level of conservativeness of the robust solution, we introduce a parameter allowing to achieve a trade-off between the price of robustness and the protection against uncertainty. Mathematically, the robust scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which is solved by using standard algorithms. The numerical results show effectiveness of the proposed approach to increase both the electricity bill and CO2 emissions savings, in the presence of user behavior uncertainties. Mathematical insights into the robust formulation are illustrated and the sensitivity of the optimum cost in the presence of uncertainties is investigated. Although home appliances and EESs are considered in this work, we point out that the proposed scheduling framework is generally applicable to many use cases, e.g., charging and discharging of electrical vehicles in an effective way. In addition, it is applicable to various scenarios considering different uncertainty sources, different storage technologies and generic programmable electrical loads, as well as different optimization criteria.

Place, publisher, year, edition, pages
IEEE Press, 2015. Vol. 13, no 1, 247-259 p.
Keyword [en]
Demand response, mixed-integer linear programming, multi-objective robust optimization, robust scheduling of smart appliances, user behavior uncertainty
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-182340DOI: 10.1109/TASE.2015.2497300ScopusID: 2-s2.0-84949883456OAI: oai:DiVA.org:kth-182340DiVA: diva2:904282
Funder
Swedish Energy AgencyKnut and Alice Wallenberg FoundationVINNOVA
Note

QC 20160226

Available from: 2016-02-18 Created: 2016-02-18 Last updated: 2016-06-03Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Paridari, KavehSandberg, HenrikJohansson, Karl Henrik
By organisation
Automatic ControlACCESS Linnaeus Centre
In the same journal
IEEE Transactions on Automation Science and Engineering
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 619 hits
ReferencesLink to record
Permanent link

Direct link