Optimal behavior of responsive residential demand considering hybrid phase change materials

• Published in: Applied energy Vol. 163; pp. 81 - 92
• Main Authors: Shafie-khah, M., Kheradmand, M., Javadi, S., Azenha, M., de Aguiar, J.L.B., Castro-Gomes, J., Siano, P., Catalão, J.P.S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2016
• Subjects: Buildings; Demand response programs; Household energy management; Phase change material; Thermal energy storage; Thermal energy storage; Household energy management; Phase change material; Demand response programs; Buildings
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2015.11.013

•An operational model of HEM system incorporating with a hybrid PCM is proposed in this paper.•Incorporation of hybrid PCM mortar had a complementary effect on the proposed HEM system.•The proposed model ensures the technical and economic limits of batteries and electrical appliances.•The customer’s electricity cost can be reduced up to 48% by utilizing the proposed model. Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customer’s cost in different DRPs but also to guaranty the habitants’ satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customer’s electricity cost can be reduced up to 48% by utilizing the proposed model.