Download or read book Energy Optimization and Prediction in Office Buildings written by Carlos Rubio-Bellido and published by Springer. This book was released on 2018-04-20 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how energy demand and energy consumption in new buildings can be predicted and how these aspects and the resulting CO2 emissions can be reduced. It is based upon the authors’ extensive research into the design and energy optimization of office buildings in Chile. The authors first introduce a calculation procedure that can be used for the optimization of energy parameters in office buildings, and to predict how a changing climate may affect energy demand. The prediction of energy demand, consumption and CO2 emissions is demonstrated by solving simple equations using the example of Chilean buildings, and the findings are subsequently applied to buildings around the globe. An optimization process based on Artificial Neural Networks is discussed in detail, which predicts heating and cooling energy demands, energy consumption and CO2 emissions. Taken together, these processes will show readers how to reduce energy demand, consumption and CO2 emissions associated with office buildings in the future. Readers will gain an advanced understanding of energy use in buildings and how it can be reduced.

Download or read book Proceedings of the 2020 DigitalFUTURES written by Philip F. Yuan and published by Springer Nature. This book was released on 2021-01-28 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is a compilation of selected papers from 2020 DigitalFUTURES—The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020). The book focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers will encounter new ideas about understanding intelligence in architecture.

Download or read book Simulation Based Optimization of Energy Consumption and Occupants Comfort in Open Plan Office Buildings Using Probabilistic Occupancy Prediction Model written by Shide Salimi and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Considering the ever-growing increase in the world energy consumption and the fact that buildings contribute a large portion of the global energy consumption arises a need for detailed investigation towards more effective energy performance of buildings. Thus, monitoring, estimating, and reducing buildings' energy consumption have always been important concerns for researchers and practitioners in the field of energy management. Since more than 80% of energy consumption happens during the operation phase of a building's life cycle, efficient management of building operation is a promising way to reduce energy usage in buildings. Among the parameters influencing the total building energy consumption, building occupants' presence and preferences could have high impacts on the energy usage of a building. To consider the effect of occupancy on building energy performance, different occupancy models, which aim to estimate the space utilization patterns, have been developed by researches. However, providing a comprehensive occupancy model, which could capture all important occupancy features, is still under development. Moreover, researchers investigated the effect of the application of occupancy-centered control strategies on the efficiency of the energy-consuming systems. However, there are still many challenges in this area of research mainly related to collecting, processing, and analyzing the occupancy data and the application of intelligent control strategies. In addition, generally, there is an inverse relationship between the energy consumption of operational systems and the comfort level of occupants using these systems. As a result, finding a balance between these two important concepts is crucial to improve the building operation. The optimal operation of building energy-consuming systems is a complex procedure for decision-makers, especially in terms of minimizing the energy cost and the occupants' discomfort. On this premise, this research aims to develop a new simulation-based multi-objective optimization model of the energy consumption in open-plan offices based on occupancy dynamic profiles and occupants' preferences and has the following objectives: (1) developing a method for extracting detailed occupancy information with varying time-steps from collected Real-Time Locating System (RTLS) occupancy data. This method captures different resolution levels required for the application of intelligent, occupancy-centered local control strategies of different building systems; (2) developing a new time-dependent inhomogeneous Markov chain occupancy prediction model based on the derived occupancy information, which distinguishes the temporal behavior of different occupants within an open-plan office; (3) improving the performance of the developed occupancy prediction model by determining the near-optimum length of the data collection period, selecting the near-optimum training dataset, and finding the most satisfying temporal resolution level for analyzing the occupancy data; (4) developing local control algorithms for building energy-consuming systems; and (5) integrating the energy simulation model of an open-plan office with an optimization algorithm to optimally control the building energy-consuming systems and to analyze the trade-off between building energy consumption and occupants' comfort. It is found that the occupancy perdition model is able to estimate occupancy patterns of the open-plan office with 92% and 86% accuracy at occupant and zone levels, respectively. Also, the proposed integrated model improves the thermal condition by 50% along with 2% savings in energy consumption by developing intelligent, optimal, and occupancy-centered local control strategies.

Download or read book Optimization of Energy Systems written by Ibrahim Din¿er and published by John Wiley & Sons. This book was released on 2017-05-15 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential resource for optimizing energy systems to enhance design capability, performance and sustainability Optimization of Energy Systems comprehensively describes the thermodynamic modelling, analysis and optimization of numerous types of energy systems in various applications. It provides a new understanding of the system and the process of defining proper objective functions for determination of the most suitable design parameters for achieving enhanced efficiency, cost effectiveness and sustainability. Beginning with a general summary of thermodynamics, optimization techniques and optimization methods for thermal components, the book goes on to describe how to determine the most appropriate design parameters for more complex energy systems using various optimization methods. The results of each chapter provide potential tools for design, analysis, performance improvement, and greenhouse gas emissions reduction. Key features: Comprehensive coverage of the modelling, analysis and optimization of many energy systems for a variety of applications. Examples, practical applications and case studies to put theory into practice. Study problems at the end of each chapter that foster critical thinking and skill development. Written in an easy-to-follow style, starting with simple systems and moving to advanced energy systems and their complexities. A unique resource for understanding cutting-edge research in the thermodynamic analysis and optimization of a wide range of energy systems, Optimization of Energy Systems is suitable for graduate and senior undergraduate students, researchers, engineers, practitioners, and scientists in the area of energy systems.

Download or read book Graph Based Model for Building Energy Prediction written by Atefeh Shamloo and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and timely forecasting of building energy use is critical in mitigating the impacts of climate change. Buildings consume a significant amount of energy worldwide, and the ability to accurately predict their energy usage can inform energy-saving strategies, reduce energy waste, and promote sustainable energy practices. Therefore, timely and precise building energy prediction is essential for achieving global energy conservation goals and mitigating the effects of climate change. Many factors contribute to the energy efficiency of buildings such as space layout design, weather and location of the building. The arrangement of space plays a crucial role in the development of building design and can exert a considerable impact on the energy efficiency of the environment. However, the existing data-driven methods do not effectively take the space relations into account in order to predict the energy consumption of buildings. On the other hand, physic-based models can consider spatial relations by including multiple zones, but it can be computationally intensive and time-consuming. This study aims to investigate the impact of space relationships in a layout on building energy usage and aims to develop a model that can effectively integrate space information and their relations into building prediction methods without significantly increasing computational costs. Thus, the study seeks to address the limitations of existing data-driven building energy prediction models, which often neglect the complex spatial relationships in the building layout or rely on computationally intensive physics-based models. Specifically, this study proposes to use graph neural network for building energy prediction by utilizing the graph structure to abstract building space relations and integrate the space relations in model prediction. The Spatial-temporal Graph Neural Networks, which are an extension of Graph Neural Networks, have been developed to consider the temporal factors for hourly building energy use prediction. This study selects an office building layout as a baseline model to simulate the energy consumption of the building. To investigate the impact of layout variations on energy consumption, we systematically altered the arrangement of spaces within an office building. In this layout we have different functions with different setpoint temperatures. The simulations revealed that altering the spatial arrangement had a significant impact on energy consumption. The maximum annual heating difference observed among different layouts reached around 12%, highlighting the potential for substantial energy savings through strategic spatial planning. Similarly, the cooling energy consumption varied about 8% across the various layouts. Building upon these insights, this research develops a spatial temporal graph neural network model to construct a time-series machine learning model for the building, enabling to forecast the energy consumption. In order to assess the effectiveness of the proposed Spatial-Temporal Graph Neural Network model, a model comparison was conducted, considering alternative data-driven and regression-based approaches commonly employed in building energy prediction. Specifically, the ST-GNN was compared against Extreme Gradient Boosting (XGBoost) and Linear Regression (LR) models, which are widely used for their simplicity and interpretability. These models were chosen to represent the benchmark against which the ST-GNN's performance in capturing spatial and temporal dependencies within the building layout. Since the focus of this study was to develop and implement a new method to assess the impact of spatial relations on energy prediction using ST-GCN model, the other methods (e.g., XGBoost and LR) used in this study serve as baseline models without optimization or enhancements, so the impact of boundary conditions in XGBoost and LR models have not been considered. ST-GCN RMSE and MAPE results showed that the model did a good job predicting the hourly energy consumption, showcasing the importance of including space relationships in predicting the energy consumption. Root Mean Square Error (RMSE) for ST-GNN compared to XGBoost and LR across different seasons improved. The improvement of the ST-GNN occurred across all seasons, with a 33.85% reduction in RMSE during Summer, a 31.60% reduction in Fall, 36.77% reduction in Winter, and a 17.97% reduction in spring. These results emphasize the importance of considering spatial relationships in predicting energy consumption, and the research findings indicate that the ST-GCN model is robust and suitable for similar energy prediction applications. However, further studies are needed to assess the model's performance across a wider range of cases.

Download or read book Guidelines for Community Energy Planning written by Hang Yu and published by Springer Nature. This book was released on 2019-09-12 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces readers to the operator method, which can be used in different stages of urban planning. Energy planning should ideally be accompanied by urban planning, ranging from comprehensive planning and detailed planning, to the design of individual construction projects. This book discusses a range of methods and models for defining energy planning objectives; analyzing and predicting energy demand; assessing available energy resources; optimizing integrated energy systems; analyzing the cost-effectiveness of proposals; implementation management; and post-assessment. Part one focuses on energy planning in different urban planning stages, while part two provides detailed discussions of key issues related to energy planning.

Download or read book A Systematic Approach of Integrated Building Control for Optimization of Energy and Cost written by Hatef Aria and published by . This book was released on 2015 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: More efficient building energy management leads to lower energy consumption and cost, higher occupancy comfort and less detrimental effects on the environment. Improving building energy management with advanced integrated building control provides a tool to coordinate and optimize control of multiple indoor parameters by considering their interconnected effects on building energy consumption and comfort. A building integrated optimization requires an approach to calculate building energy consumption, operate in real time, optimize building control parameters, and be able to modify systems operations or schedules in response to environmental or demand response signals inputs. The integrated optimization has significant effects on reductions in energy use and energy costs, reductions in peak load, and improvement of indoor environment quality without replacing the existing equipment. Most of previous research in integrated building control just focused on optimization of specific zone or some of the possible parameters. They also applied their optimization for the current hour without considering its effect on future-hours. The main goal of this research is to develop an advanced building operation optimization tool for integrated control of lighting, shade, ventilation and heating and cooling systems for whole buildings to reduce building energy consumption, operation cost, and peak load while satisfying occupancy comfort. Also, this optimization tool is capable of coordinating integrated control and demand response by real-time modification of time-of-use prices that are received from utilities. In addition, it applies multi-hour optimization by optimizing several hours simultaneously and considering effects of current hour control parameters on future hour energy consumption. As a first step, integrated optimization is investigated based on a developed and validated RC-network model of a typical small office building. Nonlinear optimization is applied to the RC-network model that is created in MATLAB. The optimization results show energy savings up to 35% more than the scheduled control. In addition, multi-hour optimization saved up to 4% of energy cost compare to optimization based on the current hour. For more accurate building energy and cost calculation, using building simulation software is essential. In this research DOE-2 is chosen as an open source building energy use analysis tool and modified based on integrated optimization requirements by adding functions to DOE-2 source code. DOE-2 requires modifications to accept the control parameters’ online and hourly bases. Accomplished modification is validated by simulating nighttime ventilation strategy. Also, the daylighting and window energy calculation algorithm is modified to operate based on shade position instead of just open or closed shade. A building-integrated optimization tool is developed by integrating the genetic algorithm optimization method in MATLAB with building energy and cost calculation software (DOE-2). This integrated optimization tool simulates and optimizes building control parameters such as indoor temperatures, shade position, artificial light power, and outdoor air ventilation rates for an entire building. This optimization tool can be easy applied to any type of building and system when their models are available in DOE-2. Moreover, different strategies are proposed for increasing speed of optimization. First, a rule-based decision-making tool is used before integrated optimization that modifies the control parameters optimization domain. Decision-making rules are developed based on sample integrated optimization results. Second, the neural network is trained for energy consumption prediction of building based on energy consumption results from DOE-2 for random control parameters. This trained neural network is connected to a genetic algorithm and replaces DOE-2 for the energy consumption calculation. Finally, a local optimization method is used after the genetic algorithm to search around genetic algorithm results of control parameters for new control parameters with lower building energy consumption. The integrated MATLAB and DOE-2 optimization tool is initially evaluated by investigating nighttime ventilation and shade position optimization. The results for nighttime ventilation optimization show total energy savings up to 8% and cooling energy consumption reduction up to 23%. Higher savings occurred on days with high diurnal temperature range and average outdoor temperature near 17 ˚C. The results for shade position optimization indicate that in hot days shades stay nearly closed since the effect of solar heat gain, which increases cooling energy consumption in addition to the detrimental effect of conduction heat transfer, is more effective and important than lighting energy reduction from daylighting. Also, in transient seasons when the building is in heating mode, shades mostly stay open since heat gain and illuminance transmission from windows reduce both heating and lighting energy consumption. In addition, using thick shades and a lower illuminance set-point give optimization more flexibility for energy savings. Finally the integrated MATLAB and DOE-2 optimization tool for whole building energy optimization is applied to a typical office building in Montreal. The results show energy savings between 10% and 30%; also higher energy savings potential could be expected during transient seasons compared to very hot or very cold seasons. The results also show peak load savings up to 40%. Keywords: building model, energy consumption, integrated control, optimization, DOE-2.

Download or read book Buildings and Climate Change written by United Nations and published by UN. This book was released on 2011 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report, produced by UNEP's Sustainable Buildings and Climate Initiative (SBCI), a think tank and partnership between the United Nations and leading companies and organizations in the building sector, presents results from almost three years of research and collaboration with leading experts around the world. Buildings contribute to well over one third of global energy use and associated greenhouse gas emissions, but also have a huge potential to achieve drastic emission reductions at virtually no cost. The current climate footprint from buildings is equivalent to 8.6 billion tons of CO2 a year and is predicted to almost double to 15.6 billion tons of CO2 by 2030. In addition, the pressure to develop new buildings - as a result of population growth, urbanization and modernization - will lead to an almost doubling of existing building stock in developing countries by 2050. The report highlights the opportunity lying within buildings to deliver cuts in greenhouse gas emissions throug

Download or read book Data Mining and Machine Learning in Building Energy Analysis written by Frédéric Magoules and published by John Wiley & Sons. This book was released on 2016-02-08 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: The energy consumption of a building has, in recent years, become a determining factor during its design and construction. With carbon footprints being a growing issue, it is important that buildings be optimized for energy conservation and CO2 reduction. This book therefore presents AI models and optimization techniques related to this application. The authors start with a review of recent models for the prediction of building energy consumption: engineering methods, statistical methods, artificial intelligence methods, ANNs and SVMs in particular. The book then focuses on SVMs, by first applying them to building energy consumption, then presenting the principles and various extensions, and SVR. The authors then move on to RDP, which they use to determine building energy faults through simulation experiments before presenting SVR model reduction methods and the benefits of parallel computing. The book then closes by presenting some of the current research and advancements in the field.

Download or read book Evaluation of Energy Efficiency and Flexibility in Smart Buildings written by Alessia Arteconi and published by MDPI. This book was released on 2021-01-21 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue “Evaluation of Energy Efficiency and Flexibility in Smart Buildings” addresses the relevant role of buildings as strategic instruments to improve the efficiency and flexibility of the overall energy system. This role of the built environment is not yet fully developed and exploited and the book content contributes to increasing the general awareness of achievable benefits. In particular, different topics are discussed, such as optimal control, innovative efficient technologies, methodological approaches, and country analysis about energy efficiency and energy flexibility potential of the built environment. The Special Issue offers valuable insights into the most recent research developments worldwide.

Download or read book Deep Energy Retrofit Guide for Public Buildings written by Rüdiger Lohse and published by Springer. This book was released on 2019-04-10 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides detailed information on how to set up Deep Energy Retrofits (DERs) in public buildings, and shares in-depth insights into the current status of the major technologies, strategies and practical best practice examples of how to cost-effectively combine them. Case studies from Europe are analyzed with respect to energy use before and after renovation, reasons for undertaking the renovation, co-benefits achieved, resulting cost-effectiveness, and the business models employed. The building sector holds the potential for tremendous improvements in terms of energy efficiency and reducing carbon emissions, and energy retrofits to the existing building stock represent a significant opportunity in the transition to a low-carbon future. Moreover, investing in highly efficient building materials and systems can replace long-term energy imports, contribute to cost cutting, and create a wealth of new jobs. Yet, while the technologies needed in order to improve energy efficiency are readily available, significant progress has not yet been made, and “best practices” for implementing building technologies and renewable energy sources are still relegated to small “niche” applications. Offering essential information on Deep Energy Retrofits, the book offers a valuable asset for architects, public authorities, project developers, and engineers alike.

Download or read book Energy Optimization in Commercial Buildings by Energy Management Systems written by Harjit S. Kapur and published by . This book was released on 1981 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evaluating Energy Performance and Improvement Potential of China Office Buildings in the Hot Humid Climate Against U S Reference Buildings written by and published by . This book was released on 2010 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study compares the building code standards for office buildings in hot humid climates of China and the USA. A benchmark office building model is developed for Guangzhou, China that meets China's minimum national and regional building codes with incorporation of common design and construction practices for the area. The Guangzhou office benchmark model is compared to the ASHRAE standard based US model for Houston, Texas which has similar climate conditions. The research further uses a building energy optimization tool to optimize the Chinese benchmark with existing US products to identify the primary areas for potential energy savings. The most significant energy-saving options are then presented as recommendations for potential improvements to current China building codes.

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 Building Performance Simulation for Design and Operation written by Jan L.M. Hensen and published by Routledge. This book was released on 2019-04-24 with total page 958 pages. Available in PDF, EPUB and Kindle. Book excerpt: When used appropriately, building performance simulation has the potential to reduce the environmental impact of the built environment, to improve indoor quality and productivity, as well as to facilitate future innovation and technological progress in construction. Since publication of the first edition of Building Performance Simulation for Design and Operation, the discussion has shifted from a focus on software features to a new agenda, which centres on the effectiveness of building performance simulation in building life cycle processes. This new edition provides a unique and comprehensive overview of building performance simulation for the complete building life cycle from conception to demolition, and from a single building to district level. It contains new chapters on building information modelling, occupant behaviour modelling, urban physics modelling, urban building energy modelling and renewable energy systems modelling. This new edition keeps the same chapter structure throughout including learning objectives, chapter summaries and assignments. Moreover, the book: • Provides unique insights into the techniques of building performance modelling and simulation and their application to performance-based design and operation of buildings and the systems which service them. • Provides readers with the essential concepts of computational support of performance-based design and operation. • Provides examples of how to use building simulation techniques for practical design, management and operation, their limitations and future direction. It is primarily intended for building and systems designers and operators, and postgraduate architectural, environmental or mechanical engineering students.

Download or read book Building Energy Audits Diagnosis and Retrofitting written by Constantinos A. Balaras and published by MDPI. This book was released on 2021-01-12 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book “Building Energy Audits-Diagnosis and Retrofitting” is a collection of twelve papers that focus on the built environment in order to systematically collect and analyze relevant data for the energy use profile of buildings and extended for the sustainability assessment of the built environment. The contributions address historic buildings, baselines for non-residential buildings from energy performance audits, and from in-situ measurements, monitoring, and analysis of data, and verification of energy saving and model calibration for various building types. The works report on how to diagnose existing problems and identify priorities, assess, and quantify the opportunities and measures that improve the overall building performance and the environmental quality and well-being of occupants in non-residential buildings and houses. Several case studies and lessons learned from the field are presented to help the readers identify, quantify, and prioritize effective energy conservation and efficiency measures. Finally, a new urban sustainability audit and rating method of the built environment addresses the complexities of the various issues involved, providing practical tools that can be adapted to match local priorities in order to diagnose and evaluate the current state and future scenarios towards meeting specific sustainable development goals and local priorities.

Download or read book Data driven Analytics for Sustainable Buildings and Cities written by Xingxing Zhang and published by Springer Nature. This book was released on 2021-09-11 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.