Download or read book Determination of a Reduced Dataset to Guide Forecasting of Energy Use in Commercial Buildings written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Energy Abstracts for Policy Analysis written by and published by . This book was released on 1989 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Development of a Commercial Sector Data Base and Forecasting Model for Electricity Usage and Demand written by Hittman Associates and published by . This book was released on 1980 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Whose Fault is it Anyway written by Danielle S. Dahan and published by . This book was released on 2017 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to the International Energy Agency, energy efficiency programs make up 72% of global greenhouse gas abatement strategies. However, there is extensive literature that shows compelling evidence for an "energy efficiency gap" in which expected energy savings from energy efficiency programs are not realized. Due to the importance of energy efficiency in global climate mitigation, as well as the significant federal, state, and local budgets for energy efficiency, there is a clear need for further research in this domain to evaluate the energy efficiency gap and prioritize methods for reducing the gap. Further, there is significantly less research on the gap as it applies to commercial buildings; the majority of research does not take advantage of advancements in available statistical modeling techniques; and there is very limited research evaluating the gap as it applies to the new field of fault detection and diagnostics (FDD). With FDD, building owners are able to closely monitor on an ongoing basis any faults that begin to occur in a commercial building that can waste energy and lead to the gap in energy efficiency. However, there has been very little research evaluating these systems in real buildings and calculating the energy efficiency impact. This thesis proposes and tests a modeling approach using novel machine learning algorithms to estimate counterfactual energy usage in real buildings and calculate the energy efficiency savings associated with an existing FDD system. In this thesis, I propose a modeling technique using novel machine learning algorithms to estimate counterfactual energy usage of commercial buildings. I take advantage of high-frequency 15- minute interval electricity, chilled water, and steam energy usage data over several years in four campus buildings. I then compare the accuracy of these models applied to brand-new data using three different machine learning modeling techniques, the Lasso Model, Ridge Regression, and an Elastic Net Model. Finally, I applied these models to 8 time periods in which the existing FDD system identified a fault, thus isolating the energy impact of the fault. With this approach, I found that each of the three modeling techniques outperformed the other two techniques in at least one of the models, indicating that there is likely a benefit from using three approaches in building energy modeling. Further, I found that the models are likely able to isolate the energy increase associated with these faults, with some models yielding a higher confidence level than others. In addition to the overall average increase in energy, the faults showed consistent results in the daily load profile shifts after the fault occurred. Overall, the faults yielded monthly energy cost increases of $800-$1600 each. This methodology could therefore be used in more buildings and with different types of fault detection diagnostics systems to better evaluate the benefits of FDD software across applications. By using this method more extensively, we can better inform policy that can in turn aim reduce the energy efficiency gap in commercial buildings.
Download or read book Energy Research Abstracts written by and published by . This book was released on 1992 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Management written by and published by . This book was released on 1975 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fossil Energy Update written by and published by . This book was released on 1983 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1985 with total page 1346 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book NASA SP 7500 written by United States. National Aeronautics and Space Administration and published by . This book was released on 1978 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Research and Development Report written by United States. Bonneville Power Administration and published by . This book was released on 1993 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Energy a Continuing Bibliography with Indexes written by and published by . This book was released on 1976 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Guide to Reducing Energy Use Budget Costs written by National Association of Counties and published by . This book was released on 1976 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied Data Analysis and Modeling for Energy Engineers and Scientists written by T. Agami Reddy and published by Springer Nature. This book was released on 2023-10-18 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and illustrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability, statistics, experimental design, regression, optimization, parameter estimation, inverse modeling, risk analysis, decision-making, and sustainability assessment methods to energy processes and systems. It provides a formal structure that offers a broad and integrative perspective to enhance knowledge, skills, and confidence to work in applied data analysis and modeling problems. This new edition also reflects recent trends and advances in statistical modeling as applied to energy and building processes and systems. It includes numerous examples from recently published technical papers to nurture and stimulate a more research-focused mindset. How the traditional stochastic data modeling approaches are complemented by data analytic algorithmic models such as machine learning and data mining are also discussed. The important societal issues related to the sustainability of energy systems are presented, and a formal structure is proposed meant to classify the various assessment methods found in the literature. Applied Data Analysis and Modeling for Energy Engineers and Scientists is designed for senior-level undergraduate and graduate instruction in energy engineering and mathematical modeling, for continuing education professional courses, and as a self-study reference book for working professionals. In order for readers to have exposure and proficiency with performing hands-on analysis, the open-source Python and R programming languages have been adopted in the form of Jupyter notebooks and R markdown files, and numerous data sets and sample computer code reflective of real-world problems are available online.
Download or read book ERDA Energy Research Abstracts written by United States. Energy Research and Development Administration and published by . This book was released on 1977 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book ERDA Energy Research Abstracts written by United States. Energy Research and Development Administration. Technical Information Center and published by . This book was released on 1977 with total page 982 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book EIA Publications Directory written by and published by . This book was released on 1980 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Driven Models Applied in Building Load Forecasting for Residential and Commercial Buildings written by SM Mahbobur Rahman and published by . This book was released on 2015 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significant portion of the operating costs of utilities comes from energy production. Machine learning methods are widely used for short-term load forecasts for commercial buildings and also the utility grid. These forecasts are used to minimize unit power production costs for the energy managers for better planning of power units and load management. In this work, three different state-of-art machine learning methods i.e. Artificial Neural Network, Support Vector Regression and Gaussian Process Regression are applied in hour ahead and 24 –hour ahead building energy forecasting. The work uses four residential buildings and one commercial building located in Downtown, San Antonio as test-bed using energy consumption data from those buildings monitored in real-time. Uncertainty quantification analysis is conducted to understand the confidence in each forecast using Bayesian Network. Using a combination of weather variables and historical load, forecasting is done in a supervised way based on a moving window training algorithm. A range of comparisons between different forecasting models in terms of relative accuracy are then presented.
