A1 Journal article (refereed), original research

Self-scheduling model for home energy management systems considering the end-users discomfort index within price-based demand response programs

Open Access publication

Publication Details
Authors: Javadi Mohammad Sadegh, Esmaeelnezhad Ali, Nardelli Pedro H.J., Gough Matthew, Lotfi Mohamed, Santos Sérgio, Catalão João P.S.
Publisher: Elsevier
Publication year: 2021
Language: English
Related Journal or Series Information: Sustainable Cities and Society
Volume number: 68
ISSN: 2210-6707
JUFO-Level of this publication: 1
Open Access: Open Access publication
Location of the parallel saved publication: http://urn.fi/URN:NBN:fi-fe202103228003


This paper presents a self-scheduling model for home energy management systems (HEMS) in which a novel formulation of a linear discomfort index (DI) is proposed, incorporating the preferences of end-users in the daily operation of home appliances. The HEMS self-scheduling problem is modelled as a mixed-integer linear programming (MILP) multi-objective problem, aimed at minimizing the energy bill and DI. In this framework, the proposed DI determines the optimal time slots for the operation of home appliances while minimizing end-users’ bills. The resulting multi-objective optimization problem has then been solved by using the epsilon-constraint technique and the VIKOR decision maker has been employed to select the most desired Pareto solution. The proposed model is tested considering tariffs in the presence of various price-based demand response programs (DRP), namely time-of-use (TOU) and real-time pricing (RTP). In addition, different scenarios considering the presence of electrical energy storage (EES) are investigated to study their impact on the optimal operation of HEMS. The simulation results show that the self-scheduling approach proposed in this paper yields significant reductions in the electricity bills for different electricity tariffs.

Last updated on 2021-25-03 at 11:30