Changing Energy Consumption Patterns Based on Multi-agent Human Behavior Modeling for Analyzing the Effects of Feedback Techniques PDF Download
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Author: Mesfer Alrizq
Publisher:
ISBN:
Category : Consumer behavior
Languages : en
Pages : 113
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Book Description
With the deployment of smart grid technologies and Advanced Metering Infrastructure, demand side management via feedback is a subject of interest to utility companies and researchers for modeling consumer behavior. Home area devices, such as in-home displays and smart appliances, are being developed and implemented to achieve real-time feedback. Near real-time feedback provided via Advanced Metering Infrastructure is used to change the consumers’ electricity consumption behavior and to conserve scarce resources. Analyses on the effects of real-time feedback show improvements in energy conservation, but the improvements are not as expected. This is due to the fact that altering human behavior is not an easy task, and not all react in the same way to a similar feedback. Modeling consumer behavior helps to understand their reactions toward different types of feedback, and hence allows for the categorization of the feedback and its relevance to a specific consumer category. This research focuses on two main tasks: (1) modeling human behavior for residential electricity consumption, and (2) identifying different consumer behavioral categories and feedback sets for each consumer behavioral category. The first task addresses load profile (electricity consumption) data needed by electric utility companies for expansion planning, in view of the evolution of smart grid and distributed energy resource concepts. Conventional methods of collecting the load profile data, such as surveys and metering, are tedious and time-consuming activities. Consumer demand, as well as continuous technological evolution, contributes to rendering data obsolete in a short period of time. For these reasons, the conventional methods pose barriers for electric utility companies. In response, this research presents an innovative behavior model for generating electricity consumption load profiles. The model will be narrowed to focus on consumption-based decision-making that is related to human comfort and to the consumer’s state of mind. Based on fuzzy logic and activity graphs, the method requires minimum consumer data and can be easily updated to adapt to changes in technology. We demonstrate the accuracy of our model against real world data. The goal of the second task is to analyze behavior change by using a multi-agent-based system, in order to eventually improve energy consumption. Analyses of behavior change have been based on surveys or face-to-face interviews. These methods are inefficient and time consuming and do not always measure the impact on energy consumption, besides suffering from difficulties related to the sample size. Therefore, we propose a multi-agent-based system to study the effects of feedback on different types of consumers. An evaluation is performed on the factors that influence the changes in consumer behavior positively and negatively. Consumer categories are generated based on their behavioral responses to given feedback. The feedback methods that are most effective for each category are evaluated and identified.
Author: Mesfer Alrizq
Publisher:
ISBN:
Category : Consumer behavior
Languages : en
Pages : 113
Get Book Here
Book Description
With the deployment of smart grid technologies and Advanced Metering Infrastructure, demand side management via feedback is a subject of interest to utility companies and researchers for modeling consumer behavior. Home area devices, such as in-home displays and smart appliances, are being developed and implemented to achieve real-time feedback. Near real-time feedback provided via Advanced Metering Infrastructure is used to change the consumers’ electricity consumption behavior and to conserve scarce resources. Analyses on the effects of real-time feedback show improvements in energy conservation, but the improvements are not as expected. This is due to the fact that altering human behavior is not an easy task, and not all react in the same way to a similar feedback. Modeling consumer behavior helps to understand their reactions toward different types of feedback, and hence allows for the categorization of the feedback and its relevance to a specific consumer category. This research focuses on two main tasks: (1) modeling human behavior for residential electricity consumption, and (2) identifying different consumer behavioral categories and feedback sets for each consumer behavioral category. The first task addresses load profile (electricity consumption) data needed by electric utility companies for expansion planning, in view of the evolution of smart grid and distributed energy resource concepts. Conventional methods of collecting the load profile data, such as surveys and metering, are tedious and time-consuming activities. Consumer demand, as well as continuous technological evolution, contributes to rendering data obsolete in a short period of time. For these reasons, the conventional methods pose barriers for electric utility companies. In response, this research presents an innovative behavior model for generating electricity consumption load profiles. The model will be narrowed to focus on consumption-based decision-making that is related to human comfort and to the consumer’s state of mind. Based on fuzzy logic and activity graphs, the method requires minimum consumer data and can be easily updated to adapt to changes in technology. We demonstrate the accuracy of our model against real world data. The goal of the second task is to analyze behavior change by using a multi-agent-based system, in order to eventually improve energy consumption. Analyses of behavior change have been based on surveys or face-to-face interviews. These methods are inefficient and time consuming and do not always measure the impact on energy consumption, besides suffering from difficulties related to the sample size. Therefore, we propose a multi-agent-based system to study the effects of feedback on different types of consumers. An evaluation is performed on the factors that influence the changes in consumer behavior positively and negatively. Consumer categories are generated based on their behavioral responses to given feedback. The feedback methods that are most effective for each category are evaluated and identified.
Author: Abusaada, Hisham
Publisher: IGI Global
ISBN: 1522592407
Category : Architecture
Languages : en
Pages : 445
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Book Description
The efficient usage, investigation, and promotion of new methods, tools, and technologies within the field of architecture, particularly in urban planning and design, is becoming more critical as innovation holds the key to cities becoming smarter and ultimately more sustainable. In response to this need, strategies that can potentially yield more realistic results are continually being sought. The Handbook of Research on Digital Research Methods and Architectural Tools in Urban Planning and Design is a critical reference source that comprehensively covers the concepts and processes of more than 20 new methods in both planning and design in the field of architecture and aims to explain the ways for researchers to apply these methods in their works. Pairing innovative approaches alongside traditional research methods, the physical dimensions of traditional and new cities are addressed in addition to the non-physical aspects and applied models that are currently under development in new settlements such as sustainable cities, smart cities, creative cities, and intercultural cities. Featuring a wide range of topics such as built environment, urban morphology, and city information modeling, this book is essential for researchers, academicians, professionals, technology developers, architects, engineers, and policymakers.
Author: Jingzheng Ren
Publisher: Springer Nature
ISBN: 3030673766
Category : Technology & Engineering
Languages : en
Pages : 283
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Book Description
This book presents various multi-criteria analysis methods for sustainability-oriented analysis and decision-making for energy systems, under various different conditions and scenarios. It presents methodologies to answer the questions relating to which of the options are the most sustainable among the alternatives, and how multi-criteria decision analysis methods can be used to select the most sustainable energy systems. A systematic innovative methodological framework is presented, which enables the most appropriate energy system to be selected under different conditions including: Scientific decision support tools for sustainable energy system selection; Fuzzy, grey, and rough sets based multi-criteria decision analysis; Decision-making models under uncertainties; and The combination of life cycle thinking and multi-criteria decision analysis This book is of interest to researchers, engineers, decision makers, and postgraduate students within the field of energy systems, sustainability, and multi-criteria decision analysis.
Author: Feifei Yu (S.M.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 113
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Book Description
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.
Author: Peter Saundry
Publisher: Springer Nature
ISBN: 3030299147
Category : Technology & Engineering
Languages : en
Pages : 686
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Book Description
This will be the first textbook on the integration of food, energy and water systems (FEWS). In recent years, the world has seen a dramatic rise in interdisciplinary energy and environmental courses and degrees at the undergraduate and graduate levels. In the US for instance, the number and variety of such programs has increased significantly over the past decade, Simultaneously, national and international initiatives that integrate food, energy and water systems have been launched. This textbook provides a substantive introduction to the food-energy-water nexus suitable for use in higher level undergraduate and graduate level courses and for scholars moving into the field of nexus studies without a strong background in all three areas and the many aspects of nexus studies.
Author: Chi-Chun Lee
Publisher: CRC Press
ISBN: 1000794180
Category : Science
Languages : en
Pages : 130
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Book Description
The main purpose of the work is to showcase the interdisciplinary engineering approaches in modeling and understanding human behaviors during interpersonal interactions those that could be typical, distressed, or atypical. The ability to measure human behaviors quantitatively has been a core component and a major research direction in both fields of engineering and psychology – though often with distinct approaches designed for different targeted applications. Engineering methods often strive to achieve high predictive accuracies using behavioral informatics techniques; these techniques employ a combination of behavior measures derived using automated signal based descriptors, and of statistical frameworks modeled using machine learning techniques. These approaches are often distinct from the observational approaches the gold standard for the past three decades in the study of psychology, even in clinical settings. The observational approaches are largely based on human subjective judgments.
Author: Su Jin Lee
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Jan Kloppenborg Møller
Publisher: CRC Press
ISBN: 1003834957
Category : Mathematics
Languages : en
Pages : 383
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Book Description
Do you have data on occupant behaviour, indoor environment or energy use in buildings? Are you interested in statistical analysis and modelling? Do you have a specific (research) question and dataset and would like to know how to answer the question with the data available? Statistical Modelling of Occupant Behaviour covers a range of statistical methods and models used for modelling energy- and comfort-related occupant behaviour in buildings. It is a classical textbook on statistics, including many practical examples related to occupant behaviour that are either taken from real research problems or adapted from such. The main focus is traditional statistical techniques based on the likelihood principle that can be applied to occupant behaviour modelling, including: General, generalised linear and survival models Mixed effect and hierarchical models Linear time series and Markov models Linear state space and hidden Markov models Illustration of all methods using occupant behaviour examples implemented in R The built environment affects occupants who live and work in it, and occupants affect the built environment by adapting it to their needs – for example, by adapting their indoor environments by interacting with building components and systems. These adaptive behaviours account for great uncertainty in the prediction of building energy use and indoor environmental conditions. Occupant behaviour is complex and multi-disciplinary but can be successfully modelled using statistical approaches. Statistical Modelling of Occupant Behaviour is written for researchers and advanced practitioners who work with real-world applications and modelling of occupant data. It describes the kinds of statistical models that may be used in various occupant behaviour modelling research. It gives a theoretical overview of these methods and then applies them to the study of occupant behaviour using readily replaceable examples in the R environment that are based on actual and experimental data.
Author: Kevin A. Gluck
Publisher: Psychology Press
ISBN: 9780805850482
Category : Psychology
Languages : en
Pages : 440
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Book Description
Accompanying CD-ROM contains ... "loadable/runnable versions of the D-OMAR ATC simulations and the human data that have been collected." -- p. 11.
Author: JAN KLOPPENBORG;SCHWEIKER MLLER (MARCEL;ANDERSEN)
Publisher:
ISBN: 9781003340812
Category : SCIENCE
Languages : en
Pages : 0
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Book Description
Do you have data on occupant behaviour, indoor environment or energy use in buildings? Are you interested in statistical analysis and modelling? Do you have a specific (research) question and dataset and would like to know how to answer the question with the data available? Statistical Modelling of Occupant Behaviour covers a range of statistical methods and models used for modelling energy- and comfort-related occupant behaviour in buildings. It is a classical textbook on statistics, including many practical examples related to occupant behaviour that are either taken from real research problems or adapted from such. The main focus is traditional statistical techniques based on the likelihood principle that can be applied to occupant behaviour modelling, including: General, generalised linear and survival models Mixed effect and hierarchical models Linear time series and Markov models Linear state space and hidden Markov models Illustration of all methods using occupant behaviour examples implemented in R The built environment affects occupants who live and work in it, and occupants affect the built environment by adapting it to their needs - for example, by adapting their indoor environments by interacting with building components and systems. These adaptive behaviours account for great uncertainty in the prediction of building energy use and indoor environmental conditions. Occupant behaviour is complex and multi-disciplinary but can be successfully modelled using statistical approaches. Statistical Modelling of Occupant Behaviour is written for researchers and advanced practitioners who work with real-world applications and modelling of occupant data. It describes the kinds of statistical models that may be used in various occupant behaviour modelling research. It gives a theoretical overview of these methods and then applies them to the study of occupant behaviour using readily replaceable examples in the R environment that are based on actual and experimental data.
