31,093 research outputs found
Building Information Modeling (BIM) Based Solutions for Rapid Energy Modeling (REM) and High Performance Buildings [video]
NPS Defense Energy SeminarFederal, state and local governments are setting ambitious targets to reduce energy use of existing buildings through retrofits. It has been challenging for owners of large building portfolios (i.e. Cities, campuses and DoD installations) to identify and prioritize buildings and retrofit measures with the highest potential, due to the time, cost and expertise required for detailed energy audits. This presentation introduces new Rapid Energy Modeling (REM) capabilities for energy analysis of entire building portfolios with minimal data input. The energy modeling approach allows prioritization of buildings, evaluation of retrofit measures, and agile exploration of scenarios to achieve energy goals at a city-scale. Results are presented dynamically in the context of a digital 3D City Model and customizable dashboards. Additionally, the individual building information models (BIM) can be used for more detailed analysis of prioritized buildings. This approach can contribute to portfolio benchmarking/audit initiatives and can help guide data-driven planning and decisions for large building portfolios. This presentation will highlight a case study based on a project recently completed at the Tinker Air Force Base (Okla.) and workflow for high performance building design
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State-of-the-art on research and applications of machine learning in the building life cycle
Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science
Energy Transparency in the Multifamily Housing Sector
Mirroring recent trends in other real estate sectors, the multifamily housing sector is subject to an increasing number of rules and regulations related to energy-performance benchmarking and performance disclosure. State and local governments are moving rapidly to institutionalize benchmarking and make energy performance information available in the real estate marketplace, while major lending institutions are taking initial steps to factor building energy performance into financial products. The goal of these new rules is to enable transparent building energy-performance information to drive energy efficiency improvements in multifamily housing that lower energy bills for residents; contribute to greater local housing affordability; and new jobs and services related to energy efficiency. Many multifamily owners and operators have never benchmarked the energy performance of their buildings, while other parties -- including state, local, and federal policymakers, tenants, utilities, and lenders -- have little or no access to building energy-performance information that can help shape real estate decisions or inform the development of policies, incentives, and financial vehicles to advance energy efficiency. This critical shortage of information about building energy performance has prevented property markets from valuing energy efficiency and severely undermined both public and private efforts to increase the energy efficiency of multifamily housing.While energy benchmarking and disclosure policies are an innovative approach to overcome energy-performance information gaps in the multifamily sector, several challenges must be addressed. The multifamily sector is fragmented and resists a one-size-fits-all approach, ranging from low-income public housing to luxury properties, all with varied sources of public and private financing. Policies must reflect and accommodate the diversity of both the building stock and its stakeholders. In many cases, underlying barriers continue to limit the ability of many multifamily owners to conduct benchmarking and other energy-performance assessment measures. This report is intended to serve as a guide for policymakers and multifamily stakeholders on benchmarking and disclosure rules and regulations. It provides an introduction to the multifamily housing sector, followed by a thorough review of existing benchmarking and disclosure policies and an assessment of continuing policy challenges and opportunities
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Towards evaluation design for smart city development
Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments
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Communication on Smart City Evaluation and Reporting In UK cities: Pilots, Demos and Experiments Case
Global trends towards urbanisation are associated with wide-ranging challenges and opportunities for cities. Smart technologies create new opportunities for a range of smart city development and regeneration programmes designed to address the environmental, economic and social challenges concentrated in cities. Whilst smart city programmes have received much publicity, there has been much less discussion about the evaluation and measurement of smart city programme outcomes. Existing evaluation approaches have been criticised as non-standard and inadequate, focusing more on implementation processes and investment metrics than on city outcomes and the impacts of smart city programmes. Addressing this, the SmartDframe project aimed to examine city approaches to the evaluation of smart city projects and programmes and reporting of their impacts on city outcomes. A number of ‘smarter’ UK cities were invited to participate, with agreement by city authorities from Birmingham, Bristol, Manchester, Milton Keynes and Peterborough to be interviewed about their smart city work. The findings provide a series of smart city case studies that exemplify contemporary city practices, offering a timely, insightful contribution to city discourse about existing and best practice approaches to evaluation and reporting of complex smart city projects and programmes
An empirical study of electricity and gas demand drivers in large food retail buildings of a national organisation
AbstractFood retail buildings account for a measurable proportion of a country's energy consumption and resultant carbon emissions so energy-operating costs are key business considerations. Increased understanding of end-use energy demands in this sector can enable development of effective benchmarking systems to underpin energy management tools. This could aid identification and evaluation of interventions to reduce operational energy demand. Whilst there are a number of theoretical and semi-empirical benchmarking and thermal modelling tools that can be used for food retail building stocks, these do not readily account for the variance of technical and non-technical factors that can influence end-use demands.This paper discusses the various drivers of energy end-uses of typical UK food retail stores. It reports on an empirical study of one organisation's hypermarket stock to evaluate the influence of various factors on annual store electricity and gas demands. Multiple regression models are discussed in the context of the development and application of a methodology for estimating annual energy end-use demand in food retail buildings. The established models account for 75% of the variation in electricity demand, 50% of the variation in gas demand in stores without CHP and 77% of the variation in gas demand in stores with CHP
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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
Giving In Numbers: 2014 Edition
Developed by CECP, in association with The Conference Board, 'Giving in Numbers: 2014 Edition' is based on data from 261 companies, including 62 of the largest 100 companies in the Fortune 500. The sum of contributions across all respondents of the recent survey on 2013 contributions totaled more than $25 billion in cash and in-kind giving. This report not only presents a profile of corporate philanthropy and employee engagement in 2013, but also pinpoints how corporate community engagement is evolving and becoming more focused following the end of the Great Recession. This is the tenth annual report on trends in corporate giving
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