An Advanced IoT-based System for Intelligent Energy Management in Buildings

Vangelis Marinakis, Haris Doukas
2018 Sensors  
The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to
more » ... he lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings' energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building's data (e.g., energy management systems), energy production, energy prices, weather data and end-users' behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information. Sensors 2018, 18, 610 2 of 16 energy demand coupled with limited conventional energy reserves are the main factors contributing to the increase in energy problems, which every city will have to resolve. Meanwhile, the ever increasing energy demand, combined with the human tendency towards constant enhancement of the standard of living, have resulted in the automation of a multitude of laborious and tedious tasks [7] . A wide set of measures has been adopted across individual Member States (MS) to actively optimise energy use, especially in buildings that account for 40% of total energy consumption in the EU [8]. The Energy Performance of Buildings Directive (EPBD) is the main policy driver at the EU level to support energy savings at the building sector. EPBD was adopted at the EU level in 2002 (2002/91/EC) and was recast in 2010 (31/2010/EU) with more ambitious provisions (EC, 2002; 2010) . The EPBD introduction has already enabled many EU countries to be more active in the area of buildings' energy performance and many others that had already defined requirements and relative frameworks to better understand and improve the status of their building stock. On 30 November 2016, the Commission proposed an update to the EPBD to help promote the use of smart technology in buildings and to streamline the existing rules. The Commission also published a new buildings database-the EU Building Stock Observatory-to track the energy performance of buildings across Europe [9]. A corollary of all the above was the emergence of the vision of the Smart Building as an environment that combines ambient intelligence and home automation, in order to enable the provision of high-level services to the residents that will ensure increasing comfort and safety within the house, as well as energy efficiency and rational management of resources [10, 11] . At the same time, reliability and flexibility offered by wireless technologies have been the driving force for turning the Smart Building market towards the vision of the Internet of Things (IoT) and have contributed to attracting growing interest in the market. The introduction of IoT in energy and the methods using "intelligent" energy management and Internet technologies constitute an important factor in promoting efficient energy and environmental management of the "smart" building [12] . In particular, the connection of internet technologies in the energy has already created a new emerging market for energy services. It is of common understanding, however, that achieving energy savings in buildings is a difficult and complex process [13, 14] . Integrated, transparent and comprehensive approaches are required to provide cities the tools and methods they need to achieve significant reduction of energy consumption and CO 2 emissions through the contribution of advanced ICT tools [15, 16] . Indeed, although there is plenty of energy related data available in the cities, the need for methodologies and validated tools to collect, integrate and analyse them, supporting energy use management, is highlighted [17, 18] . Nevertheless, the proposed systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications, which is partially due to the lack of semantics. Semantic Web advances give a way to share information about urban areas as physical, social, and specialised frameworks, thus empowering the development of shrewd city employments. The attributes of Smart Cities indicate that they apply the technological data to make effective the usage of infrastructural development that are physical in nature including the environment that is built, roads, and assets [19] . Semantic technologies have been used to create models of urban energy systems able to assess the energy performance of an urban area [20] . Lastly, they enable learning, adaptation and innovation by responding more efficiently and quickly to the varying situations through improvement of the city's intelligence. The Smart Building market is undoubtedly undergoing a fundamental shift towards the exploitation of wireless technologies and is focusing primarily on implementing the vision of IoT. The differentiation and heterogeneity of the offered solutions in levels of both hardware and software diverge from the basic principles of the IoT that require the use of a standard unified model, in order for maximum functionality to be ensured. This paper presents an advanced IoT-based system for intelligent energy management in buildings. More specifically, a semantic framework for the unified and standardized modelling of all entities that constitute the environment of Smart Buildings, as well as their properties and relations, is proposed. This semantic modelling aims to be a realistic and alternative approach that is expected to resolve many
doi:10.3390/s18020610 pmid:29462957 pmcid:PMC5856031 fatcat:np5sruml3jbvhf2mytfi2apvry