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Housing development building management system (HDBMS) for optimized electricity bills

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
International Conference on Environment and Electrical Engineering (17 ; 06-09.06.2017 ; Milan, Italy)
Języki publikacji
EN
Abstrakty
EN
Smart Buildings is a modern building that allows residents to have sustainable comfort with high efficiency of electricity usage. These objectives could be achieved by applying appropriate, capable optimization algorithms and techniques. This paper presents a Housing Development Building Management System (HDBMS) strategy inspired by Building Energy Management System (BEMS) concept that will integrate with smart buildings using Supply Side Management (SSM) and Demand Side Management (DSM) System. HDBMS is a Multi-Agent System (MAS) based decentralized decision making system proposed by various authors. MAS based HDBMS was created using JAVA on a IEEE FIPA compliant multi-agent platform named JADE. It allows agents to communicate, interact and negotiate with energy supply and demand of the smart buildings to provide the optimal energy usage and minimal electricity costs. This results in reducing the load of the power distribution system in smart buildings which simulation studies has shown the potential of proposed HDBMS strategy to provide the optimal solution for smart building energy management.
Rocznik
Strony
64--71
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
  • School of Electrical and Electronic Engineering, Newcastle University, Singapore Campus, Singapore
  • School of Electrical and Electronic Engineering, Newcastle University, Singapore Campus, Singapore
autor
  • School of Electrical and Electronic Engineering, Newcastle University, Singapore Campus, Singapore
autor
  • School of Electrical and Electronic Engineering, Newcastle University, Singapore Campus, Singapore
Bibliografia
  • [1] B. Asare-Bediako, P.F. Ribeiro, and W.L. Kling, “Integrated energy optimization with smart home energy management systems,” in Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on. IEEE, 2012, pp. 1-8.
  • [2] J. Byun, I. Hong, B. Kang, and S. Park, “A smart energy distribution and management system for renewable energy distribution and context-aware services based on user patterns and load forecasting,” IEEE Transactions on Consumer Electronics, vol. 57, no. 2, 2011.
  • [3] H.-L. Chao, C.-C. Tsai, P.-A. Hsiung, I. Chou et al., “Smart grid as a service: a discussion on design issues,” The Scientific World Journal, vol. 2014, 2014.
  • [4] D.D. Gross, “Spotlight on singapore: Smart grid city,” 2010. [Online]. Available: http://www.cleantechinvestor.com/portal/smart-grid/5860-spotlight-on-singapore-smart-grid-city.html.
  • [5] L. Hurtado, P. Nguyen, and W. Kling, “Agent-based control for building energy management in the smart grid framework,” pp. 1-6, 2014.
  • [6] A. Mishra, D. Irwin, P. Shenoy, J. Kurose, and T. Zhu, “Greencharge: Managing renewableenergy in smart buildings,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 7, pp. 1281-1293, 2013.
  • [7] F. Corno and F. Razzak, “Intelligent energy optimization for user intelligible goals in smart home environments,” IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 2128-2135, 2012.
  • [8] C. Wang, Y. Zhou, B. Jiao, Y. Wang, W. Liu, and D. Wang, “Robust optimization for load scheduling of a smart home with photovoltaic system,” Energy Conversion and Management, vol. 102, pp. 247-257 , 2015.
  • [9] C. Chen, K. Nagananda, G. Xiong, S. Kishore, and L.V. Snyder, “A communication-based appliance scheduling scheme for consumerpremise energy management systems,” IEEE Transactions on smart Grid, vol. 4, no. 1, pp. 56-65, 2013.
  • [10] E. Mocanu, K.O. Aduda, P.H. Nguyen, G. Boxem, W. Zeiler, M. Gibescu, and W.L. Kling, “Optimizing the energy exchange between the smart grid and building systems,” pp. 1-6, 2014.
  • [11] P. Zhao, S. Suryanarayanan, and M.G. Simões, “An energy management system for building structures using a multi-agent decision-making control methodology,” IEEE Transactions on Industry Applications, vol. 49, no. 1, pp. 322-330, 2013.
  • [12] S.D. McArthur, E.M. Davidson, V.M. Catterson, A.L. Dimeas, N.D. Hatziargyriou, F. Ponci, and T. Funabashi, “Multi-agent systems for power engineering applicationspart i: Concepts, approaches, and technical challenges,” pp. 1743-1752, 2007.
  • [13] S.D. McArthur, E.M. Davidson, V.M. Catterson, A.L. Dimeas, N.D. Hatziargyriou, F. Ponci, and T. Funabashi, “Multi-agent systems for power engineering applicationspart ii: Technologies, standards, and tools for building multi-agent systems,” pp. 1753-1759, 2007.
  • [14] W. Li, T. Logenthiran, V.-T. Phan, and W.L. Woo, “Intelligent multiagent system for power grid communication,” in Region 10 Conference (TENCON), 2016 IEEE. IEEE, 2016, pp. 3386-3389.
  • [15] W. Li, T. Logenthiran, W. Woo, V. Phan, and D. Srinivasan, “Implementation of demand side management of a smart home using multi-agent system,” in IEEE World Congress on Computational Intelligence. IEEE, 2016, pp. 1-8.
  • [16] W. Li, T. Logenthiran, and W. Woo, “Intelligent multi-agent system for smart home energy management,” in Smart Grid Technologies-Asia (ISGT ASIA), 2015, IEEE Innovative. IEEE, 2015, pp. 1-6.
  • [17] W. Li, T. Logenthiran, V.-T. Phan, and W.L. Woo, “Intelligent housing development building management system (hdbms) for optimized electricity bills,” in Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), 2017 IEEE International Conference on. IEEE, 2017, pp. 1-6.
  • [18] B. Nee, “Singapore energy statistics 2015,” 2015. [Online]. Available: https://www.ema.gov.sg/cmsmedia/Publications and Statistics/Publications/SES2015 Final website 2 mb.pdf.
  • [19] E.M. Authority, “Energy consumption,” 2015. [Online]. Available: https://www.ema.gov.sg/cmsmedia/Publications and Statistics/Publications/ses/2015/energy.
  • [20] P.E. Centre, “Energy audit of selected hdb,” 2004. [Online]. Available: http://www.siongboon.com/projects/2010-08-22%20 electronic%20ballast/Energy%20Audit%20of%20selected%20HDB%20residential%20blocks%20in%20Singapore%20Aug%202004.pdf.
  • [21] teoalida, 2015. [Online]. Available: http://www.teoalida.com/singapore/hdbstatistics/.
  • [22] Mypower, “Overview of the singapore electricity market,” 2014. [Online]. Available: https://www.mypower.com.sg/About/about.html.
  • [23] E.M. Company, “Price information,” 2015. [Online]. Available:https://www.emcsg.com/marketdata/priceinformation#priceDataView.
  • [24] S.P.Ltd,“Tariffs,”2014. [Online].Available: http://www.singaporepower.com.sg/irj/servlet/prt/portal/prtroot.
  • [25] E.A.J. LUTHER, “Solar energy technology primer: A summary,” 2011.
  • [26] L.T. Authority, “Factsheet on electric vehicles,” 2010. [Online]. Available: http://www.lta.gov.sg/data/apps/news/press/2010/EV%20Factsheet%20.pdf.
  • [27] K. Mahbubani, “Big idea no. 1: A ’less-car’ singapore,”2014. [Online]. Available: http://www.straitstimes.com/opinion/big-idea-no-1-a-less-car-singapore.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-27f33152-80b1-47fd-ac71-e87e776bc88f
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