Intelligent housing development building management system (HDBMS) for optimized electricity bills

Li, Weixian, Logenthiran, Thillainathan, Phan, Van-Tung and Woo, Wai Lok (2017) Intelligent housing development building management system (HDBMS) for optimized electricity bills. In: 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE. ISBN 978-1-5386-3918-4

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Abstract

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 established on an IEEE FIPA compliant multi-agent platform named JADE which is also a JAVA extension software. This 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. This simulation studies show the potential of proposed HDBMS strategy to provide the optimal solution for Smart Building energy management.

Item Type:	Book Section
Uncontrolled Keywords:	Power distribution system, Smart Buildings, Multi-agent system, Demand side management, Supply side management, Building energy management system, Housing development building management system, Electricity bills
Subjects:	G900 Others in Mathematical and Computing Sciences H600 Electronic and Electrical Engineering
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	03 Apr 2019 10:34
Last Modified:	10 Oct 2019 20:46
URI:	http://nrl.northumbria.ac.uk/id/eprint/38714

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