Multi-modal Building Energy Management System for Residential Demand Response

Demand response is proposed as a solution to handle the fluctuations in the power supply in a scenario with higher penetration of renewable energy sources. While demand response already offers a positive business case in certain domains it still lacks matureness in other areas, especially in the residential domain. This paper aims at providing a feasibility study of residential demand response by designing and validating a novel multi-modal Building Energy Management System (BEMS) that enables demand response provision and energy efficient control from residential buildings. The proposed consumer-centric BEMS monitors the building performance and its surroundings, interacts with the residents, optimally controls local Distributed Energy Resources (DERs) and provides demand response to an aggregator. The design decisions and the consequent architecture are detailed. A prototype of the envisioned BEMS has been developed and deployed in a testbed - a 12-storey residential building located in Denmark. The prototype performance, the data monitoring capabilities, interaction with the residents and controllability of local DER of the BEMS are demonstrated.

[1]  W.-H. Edwin Liu,et al.  Consumer-centric smart grid , 2011, ISGT 2011.

[2]  Rune Hylsberg Jacobsen,et al.  Demand response potential of ventilation systems in residential buildings , 2016 .

[3]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[4]  Saifur Rahman,et al.  Demand response implementation in a home area network: A conceptual hardware architecture , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[5]  Sunil Kumar,et al.  An Intelligent Home Energy Management System to Improve Demand Response , 2013, IEEE Transactions on Smart Grid.

[6]  Enrico Tronci,et al.  A Glimpse of SmartHG Project Test-bed and Communication Infrastructure , 2015, 2015 Euromicro Conference on Digital System Design.

[7]  H. Madsen,et al.  Benefits and challenges of electrical demand response: A critical review , 2014 .

[8]  Yogesh L. Simmhan,et al.  Prediction models for dynamic demand response: Requirements, challenges, and insights , 2015, 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[9]  Ahmad Faruqui,et al.  The impact of informational feedback on energy consumption d A survey of the experimental evidence , 2010 .

[10]  Michael Sankur,et al.  An architecture for integrated commercial building demand response , 2013, 2013 IEEE Power & Energy Society General Meeting.

[11]  Gregor P. Henze,et al.  Evaluation of commercial building demand response potential using optimal short-term curtailment of heating, ventilation, and air-conditioning loads , 2014 .

[12]  C. Goldman Coordination of Energy Efficiency and Demand Response , 2010 .

[13]  Giuseppe Tommaso Costanzo,et al.  An overview of demand side management control schemes for buildings in smart grids , 2013, 2013 IEEE International Conference on Smart Energy Grid Engineering (SEGE).

[14]  Henrik W. Bindner,et al.  An aggregation model for households connected in the low-voltage grid using a VPP interface , 2013, IEEE PES ISGT Europe 2013.

[15]  Giuseppe Tommaso Costanzo,et al.  A System Architecture for Autonomous Demand Side Load Management in Smart Buildings , 2012, IEEE Transactions on Smart Grid.

[16]  Carl A. Gunter,et al.  An Integrated Architecture for Demand Response Communications and Control , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[17]  Dae-Man Han,et al.  Smart home energy management system using IEEE 802.15.4 and zigbee , 2010, IEEE Transactions on Consumer Electronics.

[18]  J. Torriti,et al.  Demand response experience in Europe: Policies, programmes and implementation , 2010 .

[19]  Tao Wang,et al.  Design and implementation of a Web-based Energy Management Application for smart buildings , 2013, 2013 IEEE Electrical Power & Energy Conference.

[20]  Hans Christian Gils,et al.  Assessment of the theoretical demand response potential in Europe , 2014 .