Download or read book Predictions of Monthly Energy Consumption and Annual Patterns of Energy Usage for Convenience Stores by Using Multiple and Nonlinear Regression Models written by Krisanee Muendej and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Thirty convenience stores in College Station, Texas, have been selected as the samples for an energy consumption prediction. The predicted models assist facility energy managers for making decisions of energy demand/supply plans. The models are applied to historical data for two years: 2001 and 2002. The approaches are (1) to analyze nonlinear regression models for long term forecasting of annual patterns compared with outdoor temperature, and (2) to analyze multiple regression models for the building type regardless of outdoor temperature. In the first approach, twenty four buildings are categorized as base load group and no base group. Average temperature, cooling efficiencies, and cooling knot temperature are estimated by nonlinear regression models: segment and parabola models. The adjusted r-square results in good performance up to ninety percent accuracy. In the second approach, the other selected six buildings are categorized as no trend group. This group does not respond to outdoor temperature. As the result, multiple a regression model is formed by combination of variables from the nonlinear models and physical building variables of cooling efficiency, cooling temperature, light bulbs, area, outdoor temperature, and orientation of fronts. This model explains up to sixty percent of all convenience stores' data. In conclusion, the accuracy of prediction models is measured by the adjusted r-square results. Among these three models, the multiple regression model shows the highest adjusted r-square (0.597) over the parabola (0.5419) and segment models (0.4806). When the three models come to the application, the multiple regression model is best fit for no trend data type. However, when it is used to predict the energy consumption with the buildings that relate to outdoor temperature, segment and parabola model provide a better prediction result.
Download or read book Master s Theses Directories written by and published by . This book was released on 2005 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Education, arts and social sciences, natural and technical sciences in the United States and Canada".
Download or read book Energy Research Abstracts written by and published by . This book was released on 1987 with total page 1294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Energy and Climate in the Urban Built Environment written by M. Santamouris and published by Routledge. This book was released on 2013-06-17 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both the number and percentage of people living in urban areas is growing rapidly. Up to half of the world's population is expected to be living in a city by the end of the century and there are over 170 cities in the world with populations over a million. Cities have a huge impact on the local climate and require vast quantities of energy to keep them functioning. The urban environment in turn has a big impact on the performance and needs of buildings. The size, scale and mechanism of these interactions is poorly understood and strategies to mitigate them are rarely implemented. This is the first comprehensive book to address these questions. It arises out of a programme of work (POLISTUDIES) carried out for the Save programme of the European Commission. Chapters describe not only the main problems encountered such as the heat island and canyon effects, but also a range of design solutions that can be adopted both to improve the energy performance and indoor air quality of individual buildings and to look at aspects of urban design that can reduce these climatic effects. The book concludes with some examples of innovative urban bioclimatic buildings. The project was co-ordinated by Professor Mat Santamouris from the University of Athens who is also the editor of the book. Other contributions are from the University of Thessaloniki, Greece, ENTPE, Lyons, France and the University of Stuttgart, Germany.
Download or read book Comparison of the Prediction Accuracy of Daily and Monthly Regression Models for Energy Consumption in Commercial Buildings written by Jinrong Wang and published by . This book was released on 1996 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Backpacker written by and published by . This book was released on 2007-09 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Backpacker brings the outdoors straight to the reader's doorstep, inspiring and enabling them to go more places and enjoy nature more often. The authority on active adventure, Backpacker is the world's first GPS-enabled magazine, and the only magazine whose editors personally test the hiking trails, camping gear, and survival tips they publish. Backpacker's Editors' Choice Awards, an industry honor recognizing design, feature and product innovation, has become the gold standard against which all other outdoor-industry awards are measured.
Download or read book Patterns of Energy Consumption in the United States written by Stanford Research Institute and published by . This book was released on 1972 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Climate Impacts on Energy Systems written by Jane O. Ebinger and published by World Bank Publications. This book was released on 2011 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: "While the energy sector is a primary target of efforts to arrest and reverse the growth of greenhouse gas emissions and lower the carbon footprint of development, it is also expected to be increasingly affected by unavoidable climate consequences from the damage already induced in the biosphere. Energy services and resources, as well as seasonal demand, will be increasingly affected by changing trends, increasing variability, greater extremes and large inter-annual variations in climate parameters in some regions. All evidence suggests that adaptation is not an optional add-on but an essential reckoning on par with other business risks. Existing energy infrastructure, new infrastructure and future planning need to consider emerging climate conditions and impacts on design, construction, operation, and maintenance. Integrated risk-based planning processes will be critical to address the climate change impacts and harmonize actions within and across sectors. Also, awareness, knowledge, and capacity impede mainstreaming of climate adaptation into the energy sector. However, the formal knowledge base is still nascent?information needs are complex and to a certain extent regionally and sector specific. This report provides an up-to-date compendium of what is known about weather variability and projected climate trends and their impacts on energy service provision and demand. It discusses emerging practices and tools for managing these impacts and integrating climate considerations into planning processes and operational practices in an environment of uncertainty. It focuses on energy sector adaptation, rather than mitigation which is not discussed in this report. This report draws largely on available scientific and peer-reviewed literature in the public domain and takes the perspective of the developing world to the extent possible."
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Download or read book Energy and Household Expenditure Patterns written by Thomas J. Lareau and published by Routledge. This book was released on 2016-03-17 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1983, Energy and Household Expenditure Patterns claimed that two-thirds of energy consumption in the United States came from households. This study aimed to estimate the expected changes in household activities and how this would affect energy consumption in the country as a whole. Also discussed are implications of direct energy purchases and spending on energy goods in households as well as predicting the growth in energy consumption leading up to the year 2000. This title will be of interest to students of Environmental Studies and Economics.
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Establishing Inverse Modeling Analysis Tools to Enable Continuous Efficiency Improvement Loop Implementation written by Zahra Hatami and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: To reduce the risk of global warming it is necessary to reduce greenhouse gas emissions associated with energy usage in buildings, particularly central grid supplied electric energy. According to U.S. GREEN BUILDING COUNCIL, buildings sector accounts for 39% of carbon dioxide (CO2) emissions in the United States per year, more than any other sector and the most significant factor contributing to CO2 emissions from buildings is their use of electricity; it is more than 70% of electricity use in the U.S. It appears that convenience stores have significant opportunities for reductions in electric energy use. The Commercial Buildings Energy Consumption Survey (CBECS) reported energy use intensity (kBtu/ft2) of convenience stores is 2.9 times more than commercial office buildings. Understanding convenience store's energy use and consumption patterns will provide useful information, which will help to inform owners and operators as to what operational changes can be made to reduce energy consumption. Continually monitoring the energy consumption of convenience stores in order to identify typical energy use patterns is necessary. Monitoring includes sufficient sub-metering of specific subsystem (lighting, HVAC, refrigeration, and food preparation) energy use in specific weather and customer interactions. The monitoring data is used within a with a set of monitoring and targeting (M&T) analysis tools that establishes expected energy use relative to a data-based baseline. Actual convenience store operational data is used to demonstrate the usefulness of the M&T practice. In order to determine the electricity consumption pattern of main meter and sub-meters in each store, the inverse modeling method is applied to the convenience energy utilization data and the associated accumulated sum of differences between expected and observed energy use (CUSUM) M&T for the whole building and specific subsystem energy uses allows facility managers to immediately determine the end-use cause of energy use deviations observed in the energy use CUSUM reporting. The results indicate that the similarly designed stores exhibit very similar qualitative energy use dependencies with changes in ambient weather conditions with respect to whole building energy use and subsystem energy uses. However, the quantitative levels of energy use as well as the changes in energy use with change in ambient temperatures are specific, even for stores in close physical proximity. The energy use patterns are quite reproducible for a given location and deviations are observed to occur only when significant changes in site equipment performance or building envelope changes occur. It's believed, with some modification, this technique could be used in continues energy monitoring of an entire fleet of similar, high energy utilization commercial building types, allowing for automated notification of unexpected deviations from expected energy use at a site and probable subsystem root causes of such deviations. The automated, coupled measuring and monitoring system would form the core of a Continuous Efficiency Improvement Loop (CEIL).
Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Download or read book Simulation of Household In home and Transportation Energy Use written by Feifei Yu (S.M.) and published by . This book was released on 2013 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident in increased ownership of appliances and motor vehicles - will have a large impact on residential energy use in the future. The pattern of growth of Chinese cities may also play an intertwined role in influencing and being influenced by consumption patterns and, thus energy use. Nonetheless, models for evaluating energy demand often neglect the evolution of appliance & vehicle ownership and directly correlate consumption with static characteristics without explicit behavioral links. In this thesis I aim to provide a comprehensive method for understanding household energy behavior over time. Using household survey data and neighborhood form characteristics from Jinan, a mid-sized Chinese city, I explore the relationship between neighborhood design and household-level behaviors and their impact on final energy consumption. My ultimate goal is to provide the modeling engine for the "Energy Proforma©" a tool intended to help developers, designers, and policy-makers implement more energy-efficient neighborhoods. To predict in-home and transportation energy use, and their trade-offs, I develop an integrated household-level micro-simulation framework. The simulation tool is based on a total of eight inter-related behavioral models which estimate out-of-home energy use by predicting trip generation, mode choice and trip length for each household and in-home energy use according to different energy sources. In the various sub-models, relevant dimensions of neighborhood form and design are included as explanatory variables. These models are then combined with modules that update household demographics, appliance & vehicle ownership information, and activity trade-off patterns. These inter-linked models can then be used to estimate the long-term effects of neighborhood design on household energy consumption and greenhouse gas emissions. Unlike separate in-home or out-of-home energy demand models, I develop an integrated simulation framework for forecasting. It captures estimated trade-off effects between in-home and transportation energy-consuming behaviors. The approach produces indicators of detailed behavioral outcomes such as trip mode and trip length choice, making it easier to relate policies, such as mode-oriented strategies, to ultimate outcomes of interest. I ultimately aim to provide urban designers, developers, and policy makers a decision support tool to explore and compare long-term energy performance across proposed neighborhood development projects.
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
Download or read book Unsupervised Learning for Residential Energy Consumption Analytics written by Thanchanok Teeraratkul and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing strategies to encourage reduction in households energy consumption requires utilities to categorize, predict and modify consumers electricity usage. Unfortunately, a typical consumer exhibits wide variation in daily 24-hour electricity usage patterns. Traditional clustering methods have resulted in many hundreds of clusters, with a given consumer often associated with several clusters, making it difficult to classify consumers into stable representative groups and to predict individual electricity usage patterns. This dissertation presents two methods that better cluster consumer electricity usage pattern. The first method uses Dynamic time warping (DTW), which seeks an optimal alignment between electricity usage patterns. The second method assumes that electricity usage composes of a sequence of blocks generated from electrical devices. The clustering uses a novel block factorization model that embeds consumer usage pattern into a low dimensional space that flexibly captures time shifts of usage. Compared to commonly used clustering algorithm, both methods result in a more distinct set of clusters, and on average, a given consumer associates with a fewer clusters. The ideas and results from clustering is then used for individual electricity usage prediction. Prediction is done at two levels. The first level is day-to-day prediction where the shape of next day electricity usage pattern is predicted by cluster representatives from DTW. The second level is finer grain prediction based on block idea where load curve is predicted through block sequences. Predictions at both levels result in lower prediction error compared to some popular load forecasting techniques.
