7,629 research outputs found
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Integrating Smart Ceiling Fans and Communicating Thermostats to Provide Energy-Efficient Comfort
The project goal was to identify and test the integration of smart ceiling fans and communicating thermostats. These highly efficient ceiling fans use as much power as an LED light bulb and have onboard temperature and occupancy sensors for automatic operationbased on space conditions. The Center for the Environment (CBE) at UC Berkeley led the research team including TRC, Association for Energy Affordability (AEA), and Big Ass Fans (BAF). The research team conducted laboratory tests, installed99 ceiling fans and 12 thermostats in four affordable multifamily housing sites in Californiaâs Central Valley, interviewed stakeholders to develop a case study, developed an online design tool and design guide, outlined codes and standards outreach, and published several papers.The project team raised indoor cooling temperature setpoints and used ceiling fans as the first stage of cooling; this sequencing of ceiling fans and air conditioningreducesenergy consumption, especially during peak periods, while providing thermal comfort.The field demonstration resulted in 39% measured compressor energy savings during the AprilâOctober cooling seasoncompared to baseline conditions, normalized for floor area. Weather-normalized energy use varied from a 36% increase to 71% savings, withmedian savings of 15%.This variability reflects the diversity in buildings, mechanical systems, prior operation settings, space types, andoccupantsâ schedules,preferences, and motivations. All commercial spaces with regular occupancy schedules (and twoof the irregularly-occupied commercial spaces and one of the homes) showed energy savings on an absolute basis before normalizing for warmer intervention temperatures,and 10 of 13 sites showed energy savings on a weather-normalized basis. The ceiling fans provided cooling for one site for months during hot weather when the coolingequipment failed.Occupants reported high satisfaction with the ceiling fans and improved thermal comfort. This technology can apply to new and retrofit residential and commercial buildings
A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings
Buildings currently account for 30â40 percent of total global energy consumption. In particular, commercial buildings are responsible for about 12 percent of global energy use and 21 percent of the United Statesâ energy use, and the energy demand of this sector continues to grow faster than other sectors. This increasing rate therefore raises a critical concern about improving the energy performance of commercial buildings. Recently, researchers have investigated ways in which understanding and improving occupantsâ energy-consuming behaviors could function as a cost-effective approach to decreasing commercial buildingsâ energy demands. The objective of this paper is to present a detailed, up-to-date review of various algorithms, models, and techniques employed in the pursuit of understanding and improving occupantsâ energy-use behaviors in commercial buildings. Previous related studies are introduced and three main approaches are identified: (1) monitoring occupant-specific energy consumption; (2) Simulating occupant energy consumption behavior; and (3) improving occupant energy consumption behavior. The first approach employs intrusive and non-intrusive load-monitoring techniques to estimate the energy use of individual occupants. The second approach models diverse characteristics related to occupantsâ energy-consuming behaviors in order to assess and predict such characteristicsâ impacts on the energy performance of commercial buildings; this approach mostly utilizes agent-based modeling techniques to simulate actions and interactions between occupants and their built environment. The third approach employs occupancy-focused interventions to change occupantsâ energy-use characteristics. Based on the detailed review of each approach, critical issues and current gaps in knowledge in the existing literature are discussed, and directions for future research opportunities in this field are provided
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iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings
Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupantsâ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs
The impact of occupantsâ behaviours on building energy analysis: A research review
Over the past 15 years, the evaluation of energy demand and use in buildings has become increasingly acute due to growing scientific and political pressure around the world in response to climate change. The estimation of the use of energy in buildings is therefore a critical process during the design stage. This paper presents a review of the literature published in leading journals through Science Direct and Scopus databases within this research domain to establish research trends, and importantly, to identify research gaps for future investigation. It has been widely acknowledged in the literature that there is an alarming performance gap between the predicted and actual energy consumption of buildings (sometimes this has been up to 300% difference). Analysis of the impact of occupantsâ behaviour has been largely overlooked in building energy performance analysis. In short, energy simulation tools utilise climatic data and physical/ thermal properties of building elements in their calculations, and the impact of occupants is only considered through means of fixed and scheduled patterns of behaviour. This research review identified a number of areas for future research including: larger scale analysis (e.g. urban analysis); interior design, in terms of space layout, and fixtures and fittings on occupantsâ behaviour; psychological cognitive behavioural methods; and the integration of quantitative and qualitative research findings in energy simulation tools to name but a few
EnCOMPASS - An integrative approach to behavioural change for energy saving
This paper presents the research objectives of the enCOMPASS project, which aims at implementing and validating an integrated socio-technical approach to behavioural change for energy saving. To this end, innovative user-friendly digital tools will be developed to 1) make energy data consumption available and understandable for different types of users and stakeholders (household residents, office employees, school pupils, building managers, utilities, ICT providers) and to 2) empower them to collaborate in order to achieve energy savings and manage their energy needs in efficient, cost-effective and comfort-preserving ways. The project will demonstrate how this can be achieved with a novel approach that integrates user-centered visualisation of energy data from smart sensors and user-generated information with context-aware collaborative recommendations for energy saving, intelligent control and adaptive gamified incentives enabling effective and sustained behavioural change
Scenarios for Educational and Game Activities using Internet of Things Data
Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. The goal to address the global climate problem requires informing the population on their roles in mitigation actions and adaptation of sustainable behaviors. Addressing climate change and achieve ambitious energy and climate targets requires a change in citizen behavior and consumption practices. IoT sensing and related scenario and practices, which address school children via discovery, gamification, and educational activities, are examined in this paper. Use of seawater sensors in STEM education, that has not previously been addressed, is included in these educational scenaria
Benefits and challenges of using smart meters for advancing residential water demand modeling and management: a review
Over the last two decades, water smart metering programs have been launched in a number of medium to large cities worldwide to nearly continuously monitor water consumption at the single household level. The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies. Research to date has been focusing on one or more of these aspects but with limited integration between the specialized methodologies developed so far. This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain. The paper contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments. In particular, the future challenges posed by growing population demands, constrained sources of water supply and climate change impacts are expected to require more and more integrated procedures for effectively supporting residential water demand modeling and management in several countries across the world
What are people's responses to thermal discomfort? Sensing clothing and activity levels using senseCam
Recent international agreements on reducing energy consumption have led to a series of interventions in residential buildings, from modifying the building fabric to upgrading operating systems. To date, these attempts have met with limited success. One reason for this has been identified as the ârebound effectâ, where the occupantsâ respond to their home thermal environment change in unexpected ways after interventions. Often people decide to turn up the heating, to leave it on for longer, or to increase the average spatial temperature by heating more rooms. Although much of the research on heating patterns in dwellings has focused on identifying methods to predict and to assess thermal sensation, less is understood about the way occupants form their responses. Research presented in this paper focuses on mapping householders thermal discomfort responses. Empirical methods, drawn from the social and cognitive sciences, were used in a several studies, which monitored a small sample of UK households during winter of 2010. One of the tools used, the SenseCam, facilitates an automatic electronic diary collection by logging occupantsâ responses in a systematic approach.SenseCam results enabled the mapping of participantsâ activities in their home, in particular the estimation of clothing and activity level throughout the record period. The preliminary monitoring results show that different householders are interacting with their home thermal comfort systems in very different ways, and that their responses diverge from the current predictive models. Further analysisexamines the factors influencing responses to thermal discomfort and thereby energy consumption of individual in dwellings
FSEA 2014 â Proceedings of the AVI 2014 Workshop on Fostering Smart Energy Applications through Advanced Visual Interfaces
It is with great pleasure that we welcome you to FSEA 2014, the AVI 2014 workshop on Fostering Smart Energy Applications through Advanced Visual Interfaces.
This workshop focuses on advanced interaction, interface, and visualization techniques for energy-related applications, tools, and services. It brings together researchers and practitioners from a diverse range of background, including interaction design, human-computer interaction, visualization, computer games, and other fields concerned with the development of advanced visual interfaces for smart energy applications.
FSEA 2014 is the result of the efforts of many people involved in its organization, including our programme committee, and others who have assisted us in putting this workshop together
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