Energy and Buildings 94 (2015) 61–70 Contents lists available at ScienceDirect Energy and Buildings j ourna l ho me page: www.elsevier.com/locate/enbuild Optimal scheduling of household appliances with a battery storage system and coordination Ditiro Setlhaolo ∗ , Xiaohua Xia Centre of New Energy Systems, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa a r t i c l e i n f o Article history: Received 5 December 2014 Received in revised form 9 February 2015 Accepted 21 February 2015 Available online 28 February 2015 Keywords: Demand response Appliance scheduling Coordination Battery storage system Mixed integer nonlinear program (MINLP) Solving integer constraint problems (SCIP) a b s t r a c t This paper demonstrates an optimal household appliance scheduling problem with a battery as an energy storage system under time of use electricity tariff. Power consumption measurements of individual appli- ances considered were performed and demand profiles were obtained. In this work, a mixed integer nonlinear programming mathematical model with more practical operation constraints for appliance and battery scheduling is formulated and solved. The simulation results show effectiveness of the algo- rithm in that by optimally scheduling appliances and battery, cost saving, peak shaving and valley filling are achieved through load shifting. The energy cost saving that might be beneficial to consumers; and peak shaving and valley filling, which are of great importance to the utility. It is found that consideration of appliance coordination yields smaller cost saving because of interdependent operation. Without the battery and coordination, a cost saving of 22% and peak reduction from 10.355 kW to 8.405 kW are real- ized. Consideration of appliance coordination gives a further cost saving of 1% and a relatively smaller peak reduction to 8.30 kW. The battery bank system promotes peak shaving and valley filling and a fur- ther cost saving of about 6% and peak reduction to 5.175 kW. Sensitivity analysis, however, reveals that the energy cost saving is sensitive to consumer’s willingness to pay. © 2015 Elsevier B.V. All rights reserved. 1. Introduction Energy consumption in the residential sector accounts for more than 18% of total electricity demand in South Africa 1 [1,2]. Accord- ing to the US Energy Information Administration’s 2013 Annual Energy Outlook report, 2 the residential sector currently makes up 20% of total energy demand and is increasing by 24% worldwide. This shows that residential energy use makes up a sizeable portion of the energy pie. Since demand response (DR) was initially created to manage peak load, it has been found in the USA that the res- idential segment simply cannot be ignored as part of any utility’s energy management strategy. 2 Residential DR (RDR) diverts money that would generally go to a fossil fuel power plant to homeowners instead through peak shifting/shaping and better management of demand. Literature extensively covers the definition and different ∗ Corresponding author. Tel.: +27 12 4206407; fax: +27 12 3625000. E-mail addresses: setlhaolo@tuks.co.za (D. Setlhaolo), xxia@up.ac.za (X. Xia). 1 The Eskomfactor: Power politics and the electricity sector in South Africa, Green- peace report, 2012. http://www.greenpeace.org. 2 Residential demand response infographic. http://www.comverge.com. types of DR programs and the reader is referred to the references 3 [3]. Battery energy storage systems (BESS) are an option to provide peak shaving and valley filling of the residential load profile [4,5]. Electric vehicles and conventional batteries have over the years been used as residential energy storage devices [5–7]. There are two main applications of BESS in the residential sector. First is the off-grid hybrid energy solution, where integrated operation of two or more different types of renewable energy sources and a storage device is employed. This method is mostly applied to rural settle- ments where there is no access to the grid power [8–10]. This has been extensively studied in literature [9,10]. The second applica- tion of BESS is a backup system for a household connected to the grid. 4 This application is motivated by unreliable and intermittent electrical power supply. In this application the BESS is connected to the grid. It can be available as a compact backup electronic power supply system, uninterruptible power supply (UPS). Usually in an African set-up, buying a UPS is not affordable to many because of its high cost due to its technological enhancement features such as 3 FERC, Demand response compensation in organized wholesale energy markets, FERC Docket RM101700, 18 March 2010. http://www.ferc.gov. 4 PowerGen renewable energy http://powergen-renewable-energy.com/. http://dx.doi.org/10.1016/j.enbuild.2015.02.051 0378-7788/© 2015 Elsevier B.V. All rights reserved.