A user-centric system architecture for residential energy consumption reduction

Long-term energy consumption reduction can be achieved more readily through sensible cooperation between end users and technological advancements. The DANCER project presented here proposes a user-centric residential energy management system, with the intention to achieve long-term energy related behavioural changes, thus improving the energy efficiency of modern homes. Although, it follows the same basic principles as other contemporary approaches, it focuses on minimizing the interaction of the user with the system. This is achieved through an improved feedback mechanism and a generic, policy based service that takes advantage of the modularity and generality of the software architecture. The proposed system is designed to support a variety of technologies (WiFi, Zigbee, X10), in order to ameliorate the input and output of the decision making operation. In this paper, the general outline of the DANCER system architecture and its most important components are discussed and the prototype test-bed is presented. Special consideration is given to the implementation, operation and response behaviour of the prototype

Of impacts, agents, and functions: An interdisciplinary meta-review of smart home energy management systems research

Smart home energy management technologies (SHEMS) have long been viewed as a promising opportunity to manage the way households use energy. Research on this topic has emerged across a variety of disciplines, focusing on different pieces of the SHEMS puzzle without offering a holistic vision of how these technologies and their users will influence home energy use moving forward. This paper presents the results of a systematic, interdisciplinary meta-review of SHEMS literature, assessing the extent to which it discusses the role of various SHEMS components in driving energy benefits. Results reveal a bias towards technical perspectives and controls approaches that seek to drive energy impacts such as load management and energy savings through SHEMS without user or third-party participation. Not only are techno-centric approaches more common, there is also a lack of integration of these approaches with user-centric, information-based solutions for driving energy impacts. These results suggest future work should investigate more holistic solutions for optimal impacts on household energy use. We hope these results will provoke a broader discussion about how to advance research on SHEMS to capitalize on their potential contributions to demand-side management initiatives moving forward

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

Introducing smart grids in residential contexts : consumers' perception of smart household appliances

A more energy efficient supply and demand in household settings is high on the agenda. Smart grids, smart meters, demand side management and smart appliances play a crucial role in this context. Many stakeholders are involved, but the exact role of the customer is often neglected. More specifically, his opinion, attitude, drivers or barriers towards new ways of energy consumption and energy management. This paper employs a user-centric perspective. It aims at mapping consumers perception of the possibilities of demand side management through smart household appliances. A quantitative survey was conducted among 500 households spread over Flanders, Belgium. In this paper, the results of this survey with regard to the respondents perception of smart appliances are presented. The Technology Acceptance Model was used as the theoretical framework to measure these perceptions

Integration of Real-Intelligence in Energy Management Systems to Enable Holistic Demand Response Optimization in Buildings and Districts

Although multiple trials have been conducted demonstrating that demand side flexibility works and even though technology roll-out progresses significantly fast, the business application of residential and small tertiary demand response has been slow to develop. This paper introduces a holistic demand response optimization framework that enables significant energy costs reduction at the consumer side, while introducing buildings as a major contributor to energy networks' stability in response to network constraints and conditions. The backbone of the solution consists in a modular interoperability and data management framework that enables open standards-based communication along the demand response value chain. The solution is validated in four large-scale pilot sites, incorporating diverse building types, heterogeneous home, building and district energy systems and devices, a variety of energy carriers and spanning diverse climatic conditions, demographic and cultural characteristics.European Commission's H2020, 76861

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

Privacy Enforcement in a Cost-Effective Smart Grid

In this technical report we present the current state of the research conducted during the first part of the PhD period. The PhD thesis “Privacy Enforcement in a Cost-Effective Smart Grid” focuses on ensuring privacy when generating market for energy service providers that develop web services for the residential domain in the envisaged smart grid. The PhD project is funded and associated to the EU project “Energy Demand Aware Open Services for Smart Grid Intelligent Automation” (SmartHG) and therefore introduces the project on a system-level. Based on this, we present some of the integration, security and privacy challenges that emerge when designing a system architecture and infrastructure. The resulting architecture is a consumer-centric and agent-based design and uses open Internet-based communication protocols for enabling interoperability while being cost-effective. Finally, the PhD report presentthe envisaged future work and publications that will lead to completion of the PhD study

Contributions to Decision Support Systems, Energy Economics, and Shared Micromobility Research

This thesis includes research articles on Decision Support Systems, Energy Informatics, and Economics, Shared Micromobility, and Digital Study Assistance. For many years, established Information Systems (IS) scholars have called for solutionoriented research to address the most pressing problems of climate change. In this context, this thesis summarizes three consecutive research articles that present the multi-year development of a Decision Support System (DSS) for the energy transformation of the building sector. The DSS Nano Energy System Simulator (NESSI) was developed using Design Science Research guidelines and was further field tested and evaluated with stakeholders. In the discipline of Energy Informatics, a research article is presented that provides a morphological box for the classification of real microgrids. Next, a research article is presented that used regression analysis to investigate the influences of factors on residential photovoltaic system prices and revealed spatial price heterogeneity in Germany. Three research articles are outlined in the Shared Micromobility field. The first article uses a multi-year dataset of location data to examine the spatial and temporal use of e-scooters in Berlin. The second article builds on this and quantifies the influences of various factors such as weather, Covid-19 lockdowns, and other socio-economic parameters on the use of three micromobility concepts. The third article uses a web content mining process to collect a large dataset of police reports on e-scooter accidents. It analyzes risk factors as well as accident implications for riders. A research article on the requirements analysis and development of a digital study assistant concludes this thesis. Here, quantitative surveys and qualitative expert interviews are used to collect requirements from higher education institution stakeholders for a digital study assistant. In addition, developing a study assistance prototype is demonstrated and tested in the field