Download or read book Improving Energy Efficiency and Reducing Emissions through Intelligent Railway Station Buildings written by Asian Development Bank and published by Asian Development Bank. This book was released on 2015-09-01 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Buildings in the People's Republic of China (PRC) consume 21% of the total energy produced in the country. This study analyzes and proposes feasible energy-saving and emission-reducing solutions for domestic railway stations in the PRC. The use of intelligent building controls support reduction of energy consumption, minimization or elimination of energy wastes, and cost savings. Strong institutional mechanisms and railway building management methods and policies also promote technological innovation. Moreover, these are necessary to balance the interests of multiple parties to be able to achieve energy efficiency in railway station buildings in the PRC.

Download or read book Low Energy Architecture and Low Carbon Cities written by Francesco Pomponi and published by MDPI. This book was released on 2020-12-04 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The built environment is at a turning point. With projected trends in population growth and urbanization, global demand for new floor area is expected to rise sharply. This will put unprecedented pressure on the availability of natural resources and incur greenhouse gas emissions and energy demand. Such environmental stressors risk driving the world away from the UN Sustainable Development Goals, but equally represent an opportunity for just sustainability transitions. The contents of this book aim to address some of these grand challenges from a multi-disciplinary perspective. Low-energy architecture, low-carbon cities and the often-forgotten sustainability of refugee settlements are some of the themes dealt with by the authors.

Download or read book Strategy 2030 Energy Sector Directional Guide written by Asian Development Bank and published by Asian Development Bank. This book was released on 2023-07-01 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This sector directional guide describes the context and rationale that will guide the agenda of the Asian Development Bank (ADB) in supporting developing member countries with financing, knowledge, convening ability, and technical assistance to ensure improved the coherence, relevance, efficiency, and effectiveness of ADB’s energy sector investments. It outlines the priorities and focus for the energy sector in line with Strategy 2023. The guide is designed to be a living document, to be updated as needed to remain relevant to the dynamic development context of Asia and the Pacifi c. A midterm review will be conducted following the expected review of the Energy Policy in 2025.

Download or read book Big Data Science and Analytics for Smart Sustainable Urbanism written by Simon Elias Bibri and published by Springer. This book was released on 2019-05-30 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Download or read book The Report Saudi Arabia 2015 written by Oxford Business Group and published by Oxford Business Group. This book was released on 2015-09-22 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: While Saudi Arabia’s economy remains dominated by its hydrocarbons sector, several other sectors have emerged in recent years as key propellors of economic growth. The Kingdom’s financial services industries have continued to expand steadily despite the liquidity challenges posed by falling oil prices. Trade and investment are being treated as key priorities as the government looks to negotiate this altered economic landscape, aiming to leverage its large population, high per capita income and many sea and air links. The country’s capital markets sector meanwhile is poised for a period of significant growth on the back of the opening of Tadawul to international investors in 2015 and the raft of regulatory upgrades implemented as result. The domestic insurance industry, which remains dominated by the motor and medical segments, has enjoyed double-digit growth over the past five years in both revenue and net profit. Elsewhere the targets outlined in Vision 2030 indicate that a period of greater opportunity and integration is on the horizon for private players operating in core sectors such as health care, utilities, industry and ICT.

Download or read book Big Data for Urban Sustainability written by Stephen Jia Wang and published by Springer. This book was released on 2018-03-22 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a practical framework for the application of big data, cloud, and pervasive and complex systems to sustainable solutions for urban environmental challenges. It covers the technologies, potential, and possible and impact of big data on energy efficiency and the urban environment. The book first introduces key aspects of big data, cloud services, pervasive computing, and mobile technologies from a pragmatic design perspective, including sample open source firmware. Cloud services, mobile and embedded platforms, interfaces, operating system design methods, networking, and middleware are all considered. The authors then explore in detail the framework, design principles, architecture and key components of developing energy systems to support sustainable urban environments. The included case study provides a pathway to improve the eco-efficiency of urban transport, demonstrating how to design an energy efficient next generation urban navigation system by leveraging vast cloud data sets on user-behavior. Ultimately, this resource maps big data’s pivotal intersection with rapid global urbanization along the path to a sustainable future.

Download or read book Advances in the Leading Paradigms of Urbanism and their Amalgamation written by Simon Elias Bibri and published by Springer Nature. This book was released on 2020-06-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the recent advances in the leading paradigms of urbanism, namely compact cities, eco-cities, and data–driven smart cities, and the evolving approach to their amalgamation under the umbrella term of smart sustainable cities. It addresses these advances by investigating how and to what extent the strategies of compact cities and eco-cities and their merger have been enhanced and strengthened through new planning and development practices, and are being supported and leveraged by the applied solutions pertaining to data-driven smart cities. The ultimate goal is to advance sustainability and harness its synergistic effects on multiple scales. This entails developing and implementing more effective approaches to the balanced integration of the three dimensions of sustainability, as well as to producing combined effects of the strategies and solutions of the prevailing approaches to urbanism that are greater than the sum of their separate effects in terms of the tripartite value of sustainability. Sustainable urban development is today seen as one of the keys towards unlocking the quest for a sustainable world. And the big data revolution is set to erupt in cities throughout the world, heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities and the spaces we live in thanks to the IoT. Big data and the IoT technologies are seen as powerful forces that have tremendous potential for advancing urban sustainability. Indeed, they are instigating a massive change in the way sustainable cities can tackle the kind of special conundrums, wicked problems, and significant challenges they inherently embody as complex systems. They offer a multitudinous array of innovative solutions and sophisticated approaches informed by groundbreaking research and data–driven science. As such, they are becoming essential to the functioning of sustainable cities. Besides, yet knowing to what extent we are making progress towards sustainable cities is problematic, adding to the fragmented, conflicting picture that arises of change on the ground in the face of the escalating rate and scale of urbanization and in the light of emerging ICT and its novel applications. In a nutshell, new circumstances require new responses. This timely and multifaceted book is intended for a wide readership. As such, it will appeal to researchers, academics, urban scientists, urbanists, planners, designers, policy-makers, and futurists, as well as all readers interested in sustainable cities and their ongoing and future data-driven transformation.

Download or read book Workshop Introduction Building Energy Performance Improvement Through Advanced Technologies Smart Organization and Financing written by and published by . This book was released on 2004 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy savings performance contracts (ESPCs) are a relatively recent contracting development. ESPCs are used to obtain a variety of energy services ranging from commodity provision on a regional basis; to assumption of operation of utility plants and distribution system; to identification, implementation, and maintenance of energy and water efficiency capital improvements. ESPCs provide a means of obtaining needed resources such as manpower and technical expertise by paying for those resources through savings from reductions in facility energy use. Additional benefits may include reductions in greenhouse gas emissions and oil consumption, increases in energy efficiency, expansion of the use of renewable energy sources, and identification and implementation of energy and water saving measures. Depending on the nature of the agreement, ESPCs allow the private sector and Federal agencies to reduce energy consumption and improve efficiency in facilities, with potentially no capital investment from the end-user. However, it seems that ESPC contractors have exhausted the "low hanging fruit" opportunities for energy savings. Future projects will likely be increasingly complex and require technical and methodological support that will allow for more detailed energy systems assessment, better understanding of the available technologies and their level of their maturity, accurate replacement technology benchmarking and economic guidance.

Download or read book Automated Residential Energy Audits and Savings Measurements Using a Smart Wifi Thermostat Enabled Data Mining Approach written by Abdulrahman Mubarak Q. Alanezi and published by . This book was released on 2021 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: The building sector has been identified as one of the biggest contributions to electricity and natural gas consumption in the U.S. These findings have necessitated the need for the development of energy saving initiatives in the sector, which will aid in reducing greenhouse gas emission needed to reduce the risk of climate change. However, despite several efforts by state agencies, such as the implementation of Property Assessed Clean Energy (PACE) and On-Bill Repayment or On-Bill Financing of energy efficiency investments, there are significant challenges to achieving energy efficiency in the building sector. Fundamentally the question is "How do we find the most cost effective energy efficiency measures present in the world?" Conventional energy audits, the typical way to discern, struggle from high cost, inconsistency in audit recommendations, and a lack of people trained to deliver. Thus, the approach just is not capable of "at-scale" identification of the measures to address first, then second, and so on. Additionally, it is essential that the savings from any investment and/or even behavioral changes be capable of being measured with accuracy in order to improve the ability to find the most effective energy reduction measures existing in the broader building sector and in order to communicate the relative economic benefits from upgrades to building owners. At this time, unless there are short-interval energy meters in buildings, the ability to measure savings with accuracy is just not there. As a solution, this dissertation investigates utilizing smart Wi-Fi thermostats data to conduct visual energy audits and predict energy savings with improved accuracy from any energy systems upgrade and any behavioral modification. The study leverages data from 101 residences owned by the University of Dayton. In 2015 prior University of Dayton researchers completed energy audits of these; documenting the geometric and energy characteristics and occupancy, as well as documenting any unique energy consuming device such as washers/dyers/dishwashers in the residence. These houses provided a diversity of size, age, insulation, and energy effectiveness. Additionally, historical energy consumption data, as well as smart WiFi thermostat data with corresponding weather data, were collected for these houses. The archived thermostat measured temperature data was used to develop unique power spectrums for the measured interior temperature for each residence. The binned power spectral density is shown to be an effective signature of the energy effectiveness of the various energy characteristics associated with a residence. Moreover, the outdoor temperature for each meter period was binned into histogram groupings.This research utilizes an AutoML H2O package to determine the best machine learning algorithm for predicting both the energy characteristics and energy consumption, as well as complete the tuning needed to determine the best model hyperparameters. Machine learning models were trained to predict attic and wall R-Values, furnace efficiency, and air conditioning seasonal energy efficiency ratio (SEER) using smart WiFi thermostat measured temperature data in the form of a power spectrum, corresponding historical weather and energy consumption data, building geometry characteristics, and occupancy data. The models validation coefficient of performance (R2 values) were respectively 0.9408, 0.9421, 0.9536, and 0.9053 for predicting attic and wall R-Values, furnace efficiency, and AC SEER. This research helped lift up the possibility of conducting low-cost, large-scale, data-based energy auditing of residences that rely only on data that could easily be collected for any residence.Similarly, a power spectrum derived from the measured thermostat indoor temperature is combined with outdoor temperature data and known residential geometrical and energy characteristics in order to train a singular machine learning model capable of predicting energy consumption in any residence. The best model obtained had a percentage mean absolute error (MAE) of 8.6% for predicting monthly gas consumption. This result indicates that the best model is effective to estimate energy savings from upgrades in residential buildings. Specifically, when it is applied to real residences in which attic insulation upgraded, the energy savings estimation uncertainty was less than 7%. This is a significant improvement over the ASHRAE recommended guidelines for estimating building energy consumptions and savings, which has been termed capable, at best, of resolving savings only greater than 10% of total consumption, and, in many cases, unable to resolve any savings at all.

Download or read book Water Infrastructure written by Cecilia Tortajada and published by Routledge. This book was released on 2017-10-02 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water infrastructure is an essential element in water management. Together with institutions, policies and regulation, it provides basic services to growing populations, especially in developing countries, where much of the growth is taking place. In the Asia-Pacific region, for instance, populations are growing not only in size but also in affluence, straining further the existing infrastructure and demanding urgently the development of a new one. While 79% of total water use in Asia occurs in agriculture, the fastest increases in demand are emanating from industry and from urban areas. This trend is a natural consequence of the fastest industrialization and urbanization process in history. By 2030, more than 55% of Asia’s population will live in urban areas, an increase of 1.1 billion people. Nevertheless, water infrastructure is of concern not only in the global South but also in the North, where much of the drinking-water infrastructure needs upgrading or replacement, a significant undertaking as infrastructure is more than a hundred years old in many cases. The American Water Works Association estimates that changing all of the water pipes in the United States would cost more than USD 1 trillion. In this book, in-depth case studies on water infrastructure challenges and policy solutions are presented from different parts of the world. This book was published as a special issue of the International Journal of Water Resources Development.

Download or read book Optimization Techniques for Hybrid Power Systems Renewable Energy Electric Vehicles and Smart Grid written by Hazra, Sunanda and published by IGI Global. This book was released on 2024-07-17 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.

Download or read book Using Dashboards to Improve Energy and Comfort in Federal Buildings written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Federal agencies are taking many steps to improve the sustainability of their operations, including improving the energy efficiency of their buildings, promoting recycling and reuse of materials, encouraging carpooling and alternative transit schemes, and installing low flow water fixture units are just a few of the common examples. However, an often overlooked means of energy savings is to provide feedback to building users about their energy use through information dashboards connected to a building?s energy information system. An Energy Information System (EIS), broadly defined, is a package of performance monitoring software, data acquisition hardware, and communication systems that is used to collect, store, analyze, and display energy information. At a minimum, the EIS provides the whole-building energy-use information (Granderson 2009a). We define a?dashboard? as a display and visualization tool that utilizes the EIS data and technology to provide critical information to users. This information can lead to actions resulting in energy savings, comfort improvements, efficient operations, and more. The tools to report analyzed information have existed in the information technology as business intelligence (Few 2006). The dashboard is distinguished from the EIS as a whole, which includes additional hardware and software components to collect and storage data, and analysis for resources and energy management (Granderson 2009b). EIS can be used for a variety of uses, including benchmarking, base-lining, anomaly detection, off-hours energy use evaluation, load shape optimization, energy rate analysis, retrofit and retro-commissioning savings (Granderson 2009a). The use of these EIS features depends on the specific users. For example, federal and other building managers may use anomaly detection to identify energy waste in a specific building, or to benchmark energy use in similar buildings to identify energy saving potential and reduce operational cost. There are several vendors of EIS technology that provide information on energy and other environmental variables in buildings.

Download or read book Financial and Technological Innovation for Sustainability written by Artie Ng and published by Taylor & Francis. This book was released on 2023-11-03 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: The COVID-19 crisis has proven that sustainability of an institution or organization requires a constant review of one’s strategic positioning and the execution of pertinent plans in response to evolving externalities. Resilient organizations continue to revive themselves through effective R&D and the renewal of their range of products and services. Financial and Technological Innovation for Sustainability: Environmental, Social and Governance Performance examines approaches to sustainability under the ongoing development of energy sustainability and the green finance initiatives. It unveils global heterogeneous efforts in achieving Environmental Social Governance (ESG) performance in light of climate change, global sustainability and concerns over corporate “greenwashing”. The book assembles a wealth of case studies from a variety of contemporary organizations that actively pursue sustainable development while seeking their next economic growth. These global cases demonstrate the salience of governance that institutes continuous advancements to enable the timely revitalization of corporate strategies, technological innovation and deployment of financial resources for sustainability transformation regardless of their stages of lifecycle. They reveal distinct approaches to financial and technological innovation in Africa, Asia, Europe and North America in pursuing the shared UN Sustainable Development Goals. The intertwined public-private partnership and implications of geopolitics under an evolving global financial system for sustainability transformation are articulated. This book will appeal to academics as well as business and finance professionals, who are keen to understand the interrelationship between financial and technological innovation, and to those who want to comprehend the underlying global challenges and opportunities of adopting emerging technologies to reinvent a business model that forges measurable and impactful ESG performances.

Download or read book Study on Improving Rail Energy Efficiency E2 written by Aviva Brecher and published by . This book was released on 2015 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: A recent Volpe Center report [1] for the Federal Railroad Administration's (FRA) Rail Energy, Environment, and Engine (E3) Technology research and development program reviewed rail industry best practices (BPs) and strategies for improving energy efficiency (E2) and environmental sustainability. The review included examples of and opportunities for adoption of international transferrable BPs, and US technologies for equipment, operations and logistics software tools that have measurably improved E2 performance for passenger and freight railroads. Drivers providing renewed impetus for rail industry E2 advances include environmental compliance requirements with US Environmental Protection Agency (EPA) locomotive emission standards, US Department of Transportation Congestion Mitigation and Air Quality improvement program grants, state, regional and urban clean diesel campaigns, as well as the FRA National Rail Plan, and High-Speed Intercity Passenger Rail (HSIPR) initiatives. The report presented comparative rail system energy efficiency data and trends relative to competing modes, illustrated the benefits of energy- efficient technologies, and of alternative fuels use. Based on a comprehensive literature review and on experts' inputs, the report highlighted models of corporate rail sustainability plans and system-wide BPs and success stories. Available rail equipment and operational practices proven to improve E2 with environmental and economic benefits for all rail industry segments were illustrated. Findings and recommendations for further improving rail E2 and sustainability were tailored to the specific needs and goals of intercity and commuter passenger rail, and freight railroads (Class I-III). Key opportunities highlighted included: public-private partnerships (P3) with Federal agencies (FRA, EPA/SmartWay) for joint research, development test and evaluation (RDT&E)on advanced equipment (electric and hybrid, or dual fuel locomotives), or alternative fuels (biodiesel, CNG/LNG, Fuel cells/Hydrogen); participation in international rail organizations (UIC) and trade associations (AAR, AREMA, APTA, AASHTO), and partnering with regional and State environmental protection agencies for cross-enterprise E2 and sustainability improvements.

Download or read book Proactive Energy Management for Smart Building and Compute Server Architectures written by Abhinandan Majumdar and published by . This book was released on 2017 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing demand for improved operational performance, coupled with the increasing scarcity of energy resources, calls for new approaches to improving the energy efficiency of smart buildings and computer systems. Traditional energy management techniques have been either reactive or locally predictive at best. These schemes often underperform, by either failing to meet the desired performance target or consuming excess energy. Moreover, different applications and environments create a diverse set of challenges. Therefore, there is a dire need to develop new techniques that approach energy-performance optimality under stringent and diverse application and environmental conditions. In this dissertation, we propose proactive management techniques for Heating, Ventilation, and Air-Conditioning (HVAC) in smart buildings, and for dynamic power management of heterogeneous processors. We show how the lack of future visibility and adaptivity of traditional energy management techniques proposed in these two domains degrades energy and performance. We develop proactive techniques to improve energy efficiency in buildings and processors. We first focus on building energy management. We propose to automatically assign meetings to rooms to reduce overall energy consumption. We derive an HVAC energy model for meeting assignment by characterizing building energy behavior. Using this energy model, we propose several assignment algorithms, and analyze their optimality and scalability. We also characterize how different factors impact energy savings, when it is worthwhile to use complex assignment algorithms, and when simpler methods suffice. We further extend this model to include weather factors, and develop a methodology for assigning meetings to the most appropriate room given the expected weather. We then propose to apply Model Predictive Control (MPC) to dynamically balance HVAC energy consumption and occupant comfort. Traditional energy management techniques ignore past discomfort behavior and therefore poorly trade off energy for comfort. Our MPC framework uses a probabilistic model to predict the upcoming occupancy and discomfort history, in order to adaptively balance energy consumption and occupant comfort. Our approach achieves high energy efficiency while operating within a specified discomfort target. For heterogeneous processors, we propose MPC-based dynamic General Purpose Graphics Processing Unit (GPGPU) power management. Traditional schemes ignore future kernel behavior, and may degrade performance and energy efficiency due to their inability to plan for the performance and energy characteristics of future phases. Our approach proactively configures hardware states based on recent execution history, the pattern of upcoming kernels, and the predicted behavior of those kernels, and adaptively varies its future visibility in order to achieve high energy savings with negligible performance impact and overhead. We extend this framework for workloads that use the CPU and the GPU concurrently. Our MPC approach simultaneously optimizes the CPU and GPU across adaptively-managed time windows consisting of multiple phases of CPU and GPU applications.

Download or read book Optimal Energy efficiency Retrofit and Maintenance Planning for Existing Buildings Considering Green Building Policy Compliance written by Yuling Fan and published by . This book was released on 2017 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reducing global energy consumption is a common challenge faced by the human race due to the energy shortage and growing energy demands. The building sector bears a large responsibility for the total energy consumption throughout the world. In particular, it was concluded that existing buildings, which are usually old and energy-inefficient, are the main reason for the high energy consumption of the building sector, in view of the low replacement rate (about 1%-3% per year) of existing buildings by new energy-efficient buildings. Therefore, improving the energy efficiency of existing buildings is a feasible and effective way to reduce energy consumption and mitigate the environmental impact of the building sector. The high energy intensity and requirements of a green building policy are the main motivation of this study, which focuses on finding cost-effective solutions to green building retrofit and maintenance planning to reduce energy consumption and ensure policy compliance. As about 50% of the total energy usage of a general building is caused by its envelope system, this study first proposes a multi-objective optimization approach for building envelope retrofit planning in Chapter 2. The purpose is to maximize the energy savings and economic benefits of an investment by improving the energy efficiency of existing buildings with the optimal retrofit plans obtained from the proposed approach. In the model formulation, important indicators for decision makers to evaluate an investment, including energy savings, net present value and the payback period, are taken into consideration. In addition, a photovoltaic (PV) power supply system is considered to reduce the energy demand of buildings because of the adequate solar resource in South Africa. The performance degradation of the PV system and corresponding maintenance cost are built into the optimization process for an accurate estimation of the energy savings and payback period of the investment so that decision makers are able to make informed decisions. The proposed model also gives decision makers a convenient way to interact with the optimization process to obtain a desired optimal retrofit plan according to their preferences over different objectives. In addition to the envelope system, the indoor systems of a general building also account for a large proportion of the total energy demand of a building. In the literature, research related to building retrofit planning methods aiming at saving energy examines either the indoor appliances or the envelope components. No study on systematic retrofit plan for the whole building, including both the envelope system and the indoor systems, has been reported so far. In addition, a systematic whole-building retrofit plan taking into account the green building policy, which in South Africa is the energy performance certificate (EPC) rating system, is urgently needed to help decision makers to ensure that the retrofit is financially beneficial and the resulting building complies with the green building policy requirements. This has not been investigated in the literature. Therefore, Chapter 4 of this thesis fills the above-mentioned gaps and presents a model that can determine an optimal retrofit plan for the whole building, considering both the envelope system and indoor systems, aiming at maximizing energy savings in the most cost-effective way and achieving a good rating from the EPC rating system to comply with the green building policy in South Africa. As reaching the best energy level from the EPC rating system for a building usually requires a high amount of investment, resulting in a long payback period, which is not attractive for decision makers in view of the vulnerable economic situation of South Africa, the proposed model treats the retrofit plan as a multi-year project, improving efficiency targets in consecutive years. That is to say, the model breaks down the once-off long-term project into smaller projects over multiple financial years with shorter payback periods. In that way, the financial concerns of the investors are alleviated. In addition, a tax incentive program to encourage energy saving investments in South Africa is considered in the optimization problem to explore the economic benefits of the retrofit projects fully. Considering both the envelope system and indoor systems, many systems and items that can be retrofitted and massive retrofit options available for them result in a large number of discrete decision variables for the optimization problem. The inherent non-linearity and multi-objective nature of the optimization problem and other factors such as the requirements of the EPC system make it difficult to solve the building retrofit problem. The complexity of the problem is further increased when the target buildings have many floors. In addition, there is a large number of parameters that need to be obtained in the building retrofit optimization problem. This requires a detailed energy audit of the buildings to be retrofitted, which is an expensive bottom-up modeling exercise. To address these challenges, two simplified methods to reduce the complexity of finding the optimal whole-building retrofit plans are proposed in Chapter 4. Lastly, an optimal maintenance planning strategy is presented in Chapter 5 to ensure the sustainability of the retrofit. It is natural that the performance of all the retrofitted items will degrade over time and consequently the energy savings achieved by the retrofit will diminish. The maintenance plan is therefore studied to restore the energy performance of the buildings after retrofit in a cost-effective way. Maintenance planning for the indoor systems is not considered in this study because it has been thoroughly investigated in the literature. In addition, a maintenance plan for the PV system involved in the retrofit of this study is investigated in Chapter 2.

Download or read book Intelligent Control System Design for Energy Conservation in Commercial Buildings written by Hao Huang and published by . This book was released on 2016 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the development of model predictive control (MPC) strategies for reducing energy consumption in air-conditioned buildings. It is well known that the building sector is responsible for 40 per cent of the world's energy usage and 33 per cent of all greenhouse emissions. As a result of global environmental issues and decreasing energy resources, there is strong motivation to develop more efficient control strategies for Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings. The existing HVAC control strategies are not energy or cost efficient, which results in energy waste, high on-peak electricity demand and poor thermal comfort in buildings. Previous works have shown that MPC can be utilised as a supervisory controller to achieve energy saving while maintaining the indoor thermal comfort in buildings. However, most of the past studies were focused on small residential buildings or mid-size commercial buildings. It is highly desired to improve the existing MPC strategies to make them more reliable and applicable for large commercial buildings. This thesis extends the previous works by addressing the following challenges when dealing with the large buildings. Firstly, HVAC plants and the thermal dynamics of buildings are inherently nonlinear. Accurate modelling of these components is difficult due to the limited number of sensors that are usually installed and the paucity of prior knowledge of the system. There is a need to develop models that are capable of effectively handling the nonlinearity to achieve better modelling accuracy. Secondly, in large commercial buildings with adjacent large open spaces, the effects of thermal coupling between differently controlled spaces play a crucial role. This significance of the interaction between zones has seldom been discussed before and requires more thorough investigation. Thirdly, although load shifting function of MPC have been proven to be effective in achieving cost savings in buildings with a considerable thermal mass, it is demanding to investigate the application value of these strategies in lightweight commercial buildings. Finally, given the presence of uncertainties, these models may not be able to predict the indoor temperature accurately, which may lead to poor control performance and even instability in operation of the MPC strategy. The existing robust control approaches are generally too conservative, and may not be suitable for use in real-world buildings. In this study, the advantages of neural networks (NNs) will be exploited to address the challenges outlined above. NNs are known as universal approximators, meaning that they can model any continuous functions with any desired degree of accuracy. In particular, the NNs will be used to conduct modelling work, generate control rule, and improve the performance of classical MPC. The major contributions of this thesis are presented in four chapters, with each based on an individual scientific paper. Paper-1 presents a systematic modelling method for air handling units (AHUs) and thermal zone using a recursive NN (RNN). As the major novelty, a cascade NN structure is developed, which enables the thermal dynamics modelling of both interior zones and perimeter zones within investigated building. This approach allows accurate prediction of both supply air temperature and zone temperature prediction, making it suitable for predictive control design. Continuing with the first paper, Paper-2 introduces a multi-input, multi-output (MIMO) model, which effectively models the convective heat exchange between open spaces within multi-zone commercial buildings. The proposed model allows closed-loop prediction for several adjacent zones simultaneously by considering their thermal interaction. A NN-based optimal start-stop control method is also developed in this paper to demonstrate the energy saving potential enabled by using the proposed predictive model. The NN models provide accurate prediction results, but they are in general difficult to optimise under an MPC framework. Paper-3 presents a hybrid MPC (HMPC), which combines the classic MPC with an inverse NN model. With the HMPC, the classical MPC based on linearised building model optimises the supplied cooling energy. The inverse NN model compensates the nonlinearity associated with the AHU process and generates more accurate control inputs. Simulations and experiments demonstrate the feasibility of the proposed method in achieving energy and cost reductions while maintaining good indoor thermal comfort in the investigated large commercial building. The MPC formulation in Paper-3 does not take the system uncertainty into account. In reality, however, the modelled building energy systems are always affected by uncertainties, so that the modelling errors become inevitable which cause control performance degradation to the MPC. Paper-4 considers the application of a robust MPC (RMPC) to handle the system uncertainty within buildings. In particular, an uncertainty estimator is developed based on the previously presented RNN model to provide uncertainty bound to the conventional closed-loop min-max RMPC. The newly developed bound estimator reduces the conservatism of the RMPC and achieves improved control performance. In conclusion, the research work presented in this thesis has made important contributions to the research of intelligent model predictive control for air-conditioning systems in commercial buildings. The methodologies developed in this thesis can be utilised for other buildings or for the control of other dynamic systems.