Real-time and semantic energy management across buildings in a district configuration

Existing building and district energy management strategies are in urgent need of an overhaul to meet the energy and environmental challenges of the 21st Century. The immense growth in the availability of data through the Internet of Things (IoT), the decentralisation of energy generation, and the increasing power of Artificial Intelligence (AI) presents an opportunity to achieve a paradigm shift in the way energy is controlled and managed. To contribute to this field, this PhD project undertook a thorough literature review combined with a participatory, action research approach to identify and understand the key challenges faced by facility managers and to identify potential areas of improvement. Following this, the PhD thesis aims to tackle three key research areas using simulated case study experiments. These aim to optimise thermal energy management within buildings at a zone-level, control energy generation at a district-level, and combine the learnings from these two experiments with a holistic energy management solution that controls both the energy supply and demand at a building and district-level. At a building-level, a model predictive control approach combining a genetic algorithm and surrogate artificial neural network is used. A predictive and context aware controller is able to produce 24 hour heating set point schedules for each zone within a building. This approach achieved an energy saving of 18% whilst maintaining thermal comfort for users. The methodology also had the capability to adapt to dynamic energy pricing tariffs and capable of optimising for energy cost by shifting load to cheaper periods. At a district-level, a predictive, optimisation-based approach was developed to determine the operation of a multi-vector, district heating, energy centre. When thermal storage and several generation sources are available, alongside variable renewable energy generation and building demand, static, rulebased controllers cannot perform adequately in all conditions. Instead, the optimisation-based approach, developed in this thesis, was able to increase profit to the energy centre by 45% as well as decrease CO2 emissions whist adapting to errors in energy demand and supply forecasting. Finally, the most significant contribution of this thesis was provided by efvii fectively combining the approaches made at a building and district-level. This case study aimed to simultaneously control the energy generation of the district energy centre, alongside the thermal demand of one of the buildings within the district. The additional flexibility provided by partially controlling the building demand led to a further 8% increase in profit to the energy centre, compared to just optimising energy supply. This demonstrates the vital importance of treating the consumer as an integral, active component of the energy system. It is argued that the contributions made throughout this thesis will become more relevant when coupled with additional research fields. This includes the growth in available data from IoT sources, advanced AI including unsupervised learning, and utilising a shared semantic description of smart building, smart energy and smart city concepts. At its core, this thesis aims to demonstrate that ‘thinking’, predictive, control strategies, that are more context-aware, can achieve significant benefits over the traditional reactive, rule-based controllers of the past

An IoT-based solution for monitoring a fleet of educational buildings focusing on energy efficiency

Raising awareness among young people and changing their behaviour and habits concerning energy usage iskey to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examinesways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both theusers (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizenś behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system's high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies andservices in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer newapp-based solutions that can be used either for educational purposes or for managing the energy efficiency ofthebuilding. The system is replicable and adaptable to settings that may be different than the scenarios envisionedhere (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity

Connected systems in smart cities: use-cases of integration of buildings information with smart systems

Realisation of smart cities is highly dependent on innovative connections between the deployed systems in the cities. This implies that successfully deployment of individual smart systems which meet citizens’ needs, is not sufficient to make a city smart. Indeed, the smart cities require to innovate and connect establish infrastructures for the citizens and organisations. To enable connected systems in smart cities, the possibilities to exchange and integration information between different systems is essential. Construction industry is one of the domains which owns huge amount of valuable information asset. Buildings information can be utilised to create initiatives associated with various domains like, urban and infrastructure planning, maintenance/facility management, and energy monitoring. However, there are some barriers to realise these initiatives. This paper introduces and elaborates the details about three use-cases which need to utilise buildings information to present innovative smart services. The three use cases are: 1) Energy Usage Monitoring for positive energy usage district areas in Smart Cities (a use case from River City-anonymous name of the city); 2) Services for Facility Management Industry (a use-case from Estates office in Quay University); 3) Safety & risk management for buildings in 3D Hack event in Dublin. Each use-case considers various stakeholders’ perspectives. Also they include elaborated details related to the barriers and challenges associated with utilisation and integration of buildings information. This paper concludes by the detailed barriers to benefit from valuable buildings information to create innovative smart services. Further, recommendations are provided to overcome the presented challenges

Energy Information Systems: From the Basement to the Boardroom

A significant buildings energy reduction opportunity exists in the office sector, given that this market segment typically is an early adopter of new technology. There is a rising trend towards smart and connected offices through the internet of things (IoT) that provides new opportunities for operational efficiency and environmental sustainability practices. Leading commercial real estate companies have begun to shift from individual building automation systems (BAS) to partially integrated and automated systems such as energy information systems (EIS). In both the United States and India, organizations are seeking operational excellence, enhanced tenant relationships, and topline growth. Hence it is imperative to engage the executives with decision-making power, by tapping into their interest in sustainability, corporate social responsibility, and innovation. This expansion of interest can enable data-driven decisions, strong energy investments, and deeper energy benefits, and would drive innovation in this field. However, none of this would be possible without robust, consistent building energy information to provide visibility across all the levels of decision making, i.e. from the basement where the facilities staff take operational action to the boardroom where the executives make investment decisions. Price, security, and ease of use remain barriers to the adoption and pervasive use of promising EIS technologies in commercial office buildings. We believe that these barriers can be addressed through the development of ready, simplified, consistent, commercially available, low-cost EIS-in-a-box packages, that have a pre-defined set of hardware components and software features and functionality that are pertinent to a particular building sector. These simplified, sector-specific EIS packages can help to obviate the need for customization, and enhance ease of use, thereby enabling scale-up, in order to facilitate building energy savings. The EIS-in-a-box are adaptable in both U.S. and Indian office buildings, and potentially beyond these two countries

New intelligent network approach for monitoring physiological parameters : the case of Benin

Benin health system is facing many challenges as: (i) affordable high-quality health care to a growing population providing need, (ii) patients’ hospitalization time reduction, (iii) and presence time of the nursing staff optimization. Such challenges can be solved by remote monitoring of patients. To achieve this, five steps were followed. 1) Identification of the Wireless Body Area Network (WBAN) systems’ characteristics and the patient physiological parameters’ monitoring. 2) The national Integrated Patient Monitoring Network (RIMP) architecture modeling in a cloud of Technocenters. 3) Cross-analysis between the characteristics and the functional requirements identified. 4) Each Technocenter’s functionality simulation through: a) the design approach choice inspired by the life cycle of V systems; b) functional modeling through SysML Language; c) the communication technology and different architectures of sensor networks choice studying. 5) An estimate of the material resources of the national RIMP according to physiological parameters. A National Integrated Network for Patient Monitoring (RNIMP) remotely, ambulatory or not, was designed for Beninese health system. The implementation of the RNIMP will contribute to improve patients’ care in Benin. The proposed network is supported by a repository that can be used for its implementation, monitoring and evaluation. It is a table of 36 characteristic elements each of which must satisfy 5 requirements relating to: medical application, design factors, safety, performance indicators and materiovigilance

IoT software infrastructure for Energy Management and Simulation in Smart Cities

This paper presents an IoT software infrastructure that enables energy management and simulation of new control policies in a city district. The proposed platform enables the interoperability and the correlation of (near-)real-time building energy profiles with environmental data from sensors as well as building and grid models. In a smart city context, this platform fulfills i) the integration of heterogeneous data sources at building and district level, and ii) the simulation of novel energy policies at district level aimed at the optimization of the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real world district and a novel control policy for the heating distribution network has been developed and tested. Results are presented and discussed in the paper

Review of Waste Heat Utilisation from Data Centres

Rapidly increasing global internet traffic, mobile internet users and the number of Internet of Things (IoT) connections are driving exponential growth in demand for data centre and network services, which in turn is driving their electricity demand. Data centres now account for 3% of global electricity consumption and contribute to 4% of the global greenhouse gas emissions. This study discusses the potential of reusing the waste heat from data centres. An overview of imbedding heat recovery systems into data centres is presented. The implications of economic cost and energy efficient heat recovery systems in data centre buildings are also discussed. The main problems with implementing heat recovery systems in existing data centre designs are (i) high capital costs of investment and (ii) low temperatures of the waste heat. This study suggests alternatives that could allow data centre operators to utilise waste heat with more efficiencies. It also discusses how liquid-cooled data centres can be more efficient in utilising their waste heat than the air-cooled ones. One possible solution suggested here is that data centre operators can decrease their environmental impact by exporting waste heat to the external heat networks. The barriers in connecting datacentres to heat networks are discussed and suggestions to overcome those barriers have been provided

Blockchain Solutions for Multi-Agent Robotic Systems: Related Work and Open Questions

The possibilities of decentralization and immutability make blockchain probably one of the most breakthrough and promising technological innovations in recent years. This paper presents an overview, analysis, and classification of possible blockchain solutions for practical tasks facing multi-agent robotic systems. The paper discusses blockchain-based applications that demonstrate how distributed ledger can be used to extend the existing number of research platforms and libraries for multi-agent robotic systems.Comment: 5 pages, FRUCT-2019 conference pape

Building energy modelling and monitoring by integration of IoT devices and Building Information Models

In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side, advances in physical and environmental information sensing, communication and processing, enabled the monitoring of energy behaviour of buildings in real-time. The access to this information has been made easy and ubiquitous thank to Internet-of-Things (IoT) devices and protocols. From the other side, the creation of digital repositories of buildings and districts (i.e. Building Information Models - BIM) enabled the development of complex and rich energy models that can be used for simulation and prediction purposes. As such, an opportunity is emerging of mixing these two information categories to either create better models and to detect unwanted or inefficient energy behaviours. In this paper, we present a software architecture for management and simulation of energy behaviours in buildings that integrates heterogeneous data such as BIM, IoT, GIS (Geographical Information System) and meteorological services. This integration allows: i) (near-) real-time visualisation of energy consumption information in the building context and ii) building performance evaluation through energy modelling and simulation exploiting data from the field and real weather conditions. Finally, we discuss the experimental results obtained in a real-world case-study