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

Drivers and Barriers to the Adoption of Smart Home Energy Management Systems – Users’ Perspective

Smart home energy management system (SHEMS) is a technology, through which households can decrease and manage energy consumption and avoid demand peaks. For a significant sustainable impact, SHEMS should be adopted on a large scale. Based on semi-structured interviews with three user groups (new, prospective and experienced users) from 28 households we identify drivers and barriers to the adoption of SHEMS. The key drivers to adopt SHEMS are saving energy for economic and environmental reasons, increased comfort of living, safety and curiosity. Yet, there is lack of knowledge on SHEMS and how it relates to the larger energy system and use of renewable energy. Price of SHEMS and estimated low ROI, too complicated systems, and retrofitting problems also slow down the adoption. The results inform Information Systems research on sustainable and smart home technologies, including implications on the design of future home energy management technologies and policy planning

Cost effective technology applied to domotics and smart home energy management systems

Premio extraordinario de Trabajo Fin de Máster curso 2019/2020. Máster en Energías Renovables DistribuidasIn this document is presented the state of art for domotics cost effective technologies available on market nowadays, and how to apply them in Smart Home Energy Management Systems (SHEMS) allowing peaks shaving, renewable management and home appliance controls, always in cost effective context in order to be massively applied. Additionally, beyond of SHEMS context, it will be also analysed how to apply this technology in order to increase homes energy efficiency and monitoring of home appliances. Energy management is one of the milestones for distributed renewable energy spread; since renewable energy sources are not time-schedulable, are required control systems capable of the management for exchanging energy between conventional sources (power grid), renewable sources and energy storage sources. With the proposed approach, there is a first block dedicated to show an overview of Smart Home Energy Management Systems (SMHEMS) classical architecture and functional modules of SHEMS; next step is to analyse principles which has allowed some devices to become a cost-effective technology. Once the technology has been analysed, it will be reviewed some specific resources (hardware and software) available on marked for allowing low cost SHEMS. Knowing the “tools” available; it will be shown how to adapt classical SHEMS to cost effective technology. Such way, this document will show some specific applications of SHEMS. Firstly, in a general point of view, comparing the proposed low-cost technology with one of the main existing commercial proposals; and secondly, developing the solution for a specific real case.En este documento se aborda el estado actual de la domótica de bajo coste disponible en el mercado actualmente y cómo aplicarlo en los sistemas inteligentes de gestión energética en la vivienda (SHEMS) permitiendo el recorte de las puntas de demanda, gestión de energías renovables y control de electrodomésticos, siempre en el contexto del bajo coste, con el objetivo de lograr la máxima difusión de los SHEMS. Adicionalmente, más allá del contexto de la tecnología SHEMS, se analizará cómo aplicar esta tecnología para aumentar la eficiencia energética de los hogares y para la supervisión de los electrodomésticos. La gestión energética es uno de los factores principales para lograr la difusión de las energías renovables distribuidas; debido a que las fuentes de energía renovable no pueden ser planificadas, se requieren sistemas de control capaces de gestionar el intercambio de energía entre las fuentes convencionales (red eléctrica de distribución), energías renovables y dispositivos de almacenamiento energético. Bajo esta perspectiva, este documento presenta un primer bloque en el que se exponen las bases de la arquitectura y módulos funcionales de los sistemas inteligentes de gestión energética en la vivienda (SHEMS); el siguiente paso será analizar los principios que han permitido a ciertos dispositivos convertirse en dispositivos de bajo coste. Una vez analizada la tecnología, nos centraremos en los recursos (hardware y software) existentes que permitirán la realización de un SHEMS a bajo coste. Conocidas las “herramientas” a nuestra disposición, se mostrará como adaptar un esquema SHEMS clásico a la tecnología de bajo coste. Primeramente, comparando de modo genérico la tecnología de bajo coste con una de las principales propuestas comerciales de SHEMS, para seguidamente desarrollar la solución de bajo coste a un caso específico real

Simulation of a Smart Home Energy Management System with Dynamic Price Response

With the continuing development of the smart grid combined with the fluctuating nature of the electricity market, the development of demand-side management with controllable loads have been greatly driven. With the amount of household loads in the residential sector, managing their energy usage has received lots of interest. This paper presents a simulation of a previously proposed hardware design of a smart home energy management system (SHEMS), focusing on the data collection and processing functions of the proposed design while implementing them onto standard household loads like an electric water heater and an electric vehicle charging station. It was found that the simulation of the loads save consumers money by a significant amount when an SHEMS is implemented when compared to without implementation of an SHEMS

September 2017

https://digitalcommons.usm.maine.edu/jud_tempshalomnl/1060/thumbnail.jp

Gender inclusiveness in the adoption and use of home energy technologies

Home energy technologies, such as smart home energy management systems (SHEMS), are important in reducing energy-related emissions and empowering energy users. However, there are concerns on gender inclusiveness of the adoption and use of SHEMS. So far, information systems research has failed to address this significant challenge. This study examines factors shaping gendered adoption and use of smart home technologies, particularly SHEMS, and the implications this has for sustainability and energy equality. Applying a critical lens, we examine findings from a sensory ethnographic study on the adoption of SHEMS in households. The findings underline the need for more inclusive energy technology design, more understanding of diversity of households and more variety in the approaches for increasing awareness on and facilitating the adoption of energy technologies. We contribute to research on gender and home energy technologies, and to the larger discussion of gender and energy.© 2023 the Authors. This material is brought to you by the ECIS 2023 Proceedings at AIS Electronic Library (AISeL). It has been accepted for inclusion in ECIS 2023 Research Papers by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]=vertaisarvioitu|en=peerReviewed

Design of Smart Home Energy Management System for Saving Energy

The rapid change and development in human life, information technology, and the increase in using home gadgets, modern appliances, and electric cars, leads to more dependency on electrical resources and consecutive increase in CO2 emission from generation plant. The current world issue is on how to save the energy by reducing the consumption and decreasing global warming. In this research, Smart Home Energy Management System (SHEMS) has been developed to operate home appliances in an optimum approach. It is aimed at reducing the consumption energy by detecting the residents’ activity and identifying it among three states: Active, Away, or Sleep. The SHEMS is designed with an algorithm that is based on Hidden Markov Model (HMM) in order to estimate the probability of the home being in each of the above states. The proposed system uses the WiFi technology for data transmission inside home and the GSM technology for external communication. The proposed system and its algorithm was successfully tested and 18% of energy saving were obtained

Understanding User Perception and Intention to Use Smart Homes for Energy Efficiency: A Survey

The positive impact of Smart Homes on energy efficiency is heavily dependent on how consumers use the system after adoption. While the technical aspects of Smart Home systems and their potential to reduce energy usage is a focus of various studies, there is a limited consideration of behavioral psychology while designing systems for energy management. To investigate users' perception and intention to use Smart Homes to support energy efficiency, we design a research model by combining a theory of planned behavior and the norm activation model. We design a questionnaire and conduct a survey targeting current smart home users (over 350 responses). To analyze the survey results, we extend the partial least squares structural equation modeling (PLS-SEM) by a random forest algorithm. The findings suggest that personal norms have the strongest influence on behavioral intention to use Smart Homes for energy efficiency, followed by the ascription of responsibility. Furthermore, the results support the effects of attitudes, subjective norms, awareness of consequences, as well as the moderating effect of past behavior on the relationship between personal norms and behavioral intentions

Home energy monitoring system towards smart control of energy consumption

The need to manage, control and reduce energy consumption has led researchers to propose reliable solutions based on new technologies to achieve this goal. Our contribution in this subject is presented in this paper and consists of the design, implementation and testing of a home energy monitoring system. The presented system is dedicated for residential customers and allows the monitoring and control of the energy consumption, based on distributed and central processing. The system includes distributed monitoring devices, a gateway and a graphical user interface (GUI). To connect the all parts we use a hybrid wireless solution based on the Wi-Fi and Bluetooth Low Energy standards. We present the design and the implementation of the monitoring device hardware as well as the embedded software used to calculate the electrical quantities. We also present the calibration methodology used to eliminate gain and offset errors. In terms of performance test results, we have achieved voltage measurement accuracy below 0.2% and current measurement accuracy below 0.5%. A GUI was also developed for the user to visualize and control remotely the household appliances.This work is supported by FCT with the reference project UID/EEA/04436/2013, COMPETE 2020 with the code POCI-01-0145-FEDER-006941