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京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第21883号 / エネ博第384号 / 新制||エネ||75(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 下田 宏, 教授 手塚 哲央, 教授 中村 裕一 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

<p>With increasing concerns about the global warming effects of HFC refrigerants, low-GWP refrigerants and non-vapor compression heat pumps are investigated as potential mid- and long-term replacements for current vapor compression heat pump systems that rely on high-GWP refrigerants. To address the need for more environmentally friendly space cooling and heating, and water heating solutions. the U.S. Department of Energy (DOE) Office of Energy Efficiency & Renewable Energy (EERE) is supporting the development of smarter, more efficient, and affordable heat pumping systems operating with low- or near-zero GWP refrigerants through different programs including the Energy, Emissions, and Equity (E3) Initiative. In addition, the Emerging Technologies (ET) Program within the Building Technologies Office (BTO) emphasized the research and development efforts needed to support new technologies that could reduce energy usage in residential and commercial buildings by 50\% over the next decades. In the literature, limited studies were found that systematically investigated different combinations of conventional and emerging space conditioning and water heating technologies while accounting for real building loads, different climate zones, utility structures, and current state-of-the-art equipment. Existing literature primarily focused on thermodynamic performance evaluations at fixed boundary conditions. In addition, separate sensible latent cooling (SSLC) and other novel cooling and dehumidification systems (e.g., membrane-based systems) can significantly reduce the electricity usage for space conditioning. To compare the performance of conventional and emerging technologies several figures-of-merit such as the second law efficiency, are often used. However, limitations exist in previous studies to define the thermodynamic reversible limits and second law efficiency for cooling and dehumidification systems.</p><p>This study developed a comprehensive modeling framework to evaluate both current state-of-the-art vapor compression systems and emerging HVAC\&R technologies in real-world scenarios. The platform will be used to assess potential energy savings, scalability issues, and the effectiveness of combined technologies for different buildings, climate conditions, and utility structures.</p><p>To compare HVAC technologies, a new physics-based definition for the reversible limit and the second law efficiencies for cooling and dehumidification systems with air recirculation has been developed. The new framework is then extended to define a novel performance metric, the seasonal second law efficiency, to form a universal benchmark for assessing various cooling and dehumidification systems. Five cooling and dehumidification systems including magnetocaloric cooling, solid desiccant dehumidification, and membrane dehumidification are evaluated using this benchmark. Steady-state thermodynamic models are constructed for each system. Second law efficiency for each system under various outdoor temperatures and indoor sensible heat ratios (SHR) are calculated. The annual electricity usage of the five systems is used to justify the seasonal second law efficiency definition. The results show that compared to conventional vapor compression systems with mechanical dehumidification, the membrane-based AMX-R cycle can reduce annual electricity use by 12.2%-22.2% and increase the seasonal second law efficiency by 36%.</p><p>The advancements of nine not-in-kind (defined as non-vapor compression systems, solid-state, and chemical-based systems) technologies, i.e. magnetocaloric, thermoelectric, elastocaloric, electrocaloric, membrane-based, Vuilleumier, sorption, chemical looping, and desiccant, were reviewed in detail and compared with the state-of-the-art vapor compression systems. Suitable figures-of-merit were defined to compare the different technologies from a thermodynamic standpoint as well as technology readiness level. As a result of the thorough literature review, a roadmap was created to track the development of emerging HVAC&R technologies and future developments. More importantly, the roadmap enabled the identification of several case studies to evaluate potential energy savings both for space conditioning and water heating. Techno-economic studies for eight HVAC configurations for space heating, cooling, and water heating were conducted for a realistic building scenario under various climate conditions. Different combinations of advanced equipment such as heat pump water heater (HPWH), ground-source heat pumps (GSHP), cold-climate heat pumps (CCHP), and membrane-heat pumps were compared with traditional vapor compression heat pumps and gas furnaces. A building model was developed in EnergyPlus and validated with historical data from the DC Nanogrid House at the Purdue University campus. A total of eleven climate zones were considered, and both local weather conditions and utility pricing were implemented in the simulations. Moreover, future SEER2/HSPF2 equipment ratings and E3 Initiative targets were also included in the analyses.</p><p>The initial simulation results provided climate-based equipment selection guidelines and quantitative techno-economic assessments. For instance, CCHPs with two-stage compression in heating mode save 10%-20% in annual heating cost compared with single-stage VCHPs in Climate Zone 4A, 4C, 5A, 5B, 6A, and 6B. Membrane evaporative air-conditioners could provide cooling cost savings in places where is a significant cooling load, such as Zone 1A, 2A, 2B, 3A, 3C, 4A, 5A, and 6A. Gas furnaces should only be used in cold places where the electricity price per kWh to gas price ratio is higher than 3. GSHP has the lowest HVAC annual energy cost in six out of eleven climate zones in the U.S. Dual fuel heat pumps are not always the most economical option but yield better average cost savings among the eleven locations. HPWHs should be recommended in areas where the electricity price to gas price ratio is below 3. </p><p>The developed simulation framework will be instrumental to continue in-depth investigations of current and next-generation heat pump technologies. The ultimate goal of this research is to provide future guidelines on the selection of building-specific and climate-specific equipment solutions that will enable energy savings and future decarbonization strategies (e.g., geospatially-resolved simulations).</p>

The world is currently submerged in two big problems: supply energy crisis and climate change. It is clear that society has to do its best to overcome these challenges, and one effective way to mitigate their effects is by conducting an energy audit, which helps to identify the weaknesses and strengths of the buildings, enabling improvements in their thermal efficiency.  The main goal of this study was to carry out an energy audit on a century-old single- family house located in a city in the middle of Sweden. To achieve this, relevant data of the building was gathered such as the bills and some temperature and dimension measurements. Subsequently, the calculations of the energy losses and gains were done manually. From this step it was observed that almost 70 % of the thermal losses occurred due to transmission through the walls, windows and roof. To reduce these losses, potential energy-saving measures were studied, such as replacing the 2-panel windows with 3-panel windows and adding 200 mm of mineral wool to the roof. Both improvements reduced transmission losses around 700 kWh/year and diminished CO2 emissions around 20 kg/year, which implied a decrease of 1262 and 1277 SEK per year for each measure respectively. However, the profitability of these measures was difficult to attain because the required initial capitals are probably higher than the investments allowed, which are around 17371 and 17579 SEK for each measure respectively.  Moreover, a study about installing photovoltaic solar cells was conducted and it resulted in a significant positive impact in the energy usage of the house. In particular, this improvement lead to a reduction of 2471 kWh per year, which equaled to an annual decrease of 6036 SEK. These annual savings implied an investment allowed of 58620 SEK. Furthermore, a decrease of 99 kg of CO2 emissions per year was obtained. In conclusion, this measure yielded substantial profitability, making it the most recommended option for future energy-saving improvements.  Finally, changing in the occupant’s behavior by reducing the indoor temperature had a positive impact on the house without the need for an initial investment. Specifically, it decreased around 105 kWh per year.

Since COVID-19 was declared a pandemic by the World Health Organization(WHO) in March 2020, teleworking, or working from home, has been used to an increasing extent by companies and organisations all over the world. Evidence suggests that teleworking will become part of “the new normal”, why teleworking-related research will be of value in a long-term perspective. To estimate the potential for energy saving in relation to teleworking, and to identify possible measures to achieve such savings, a literature study and a retrospective case study of an office building in Gävle, Sweden, was conducted. The occupant presence during 2020 was mapped through conversations with representatives of the organisation using the offices. Data logs of energy usage in 2020, in the form of district heating and electricity, were provided by the energy supplier. The results showed that the number of permanent office workers had dropped by just over 40% around the middle of March 2020, and that the occupancy from November 2020 onwards was just over 20 % of that by the beginning of the year. The demand for heating, cooling, and ventilation in an office is the same regardless of the number of people present, which was believed to be the explanation of the lack of covariation between occupancy and district heating supply, as well as between occupancy and HVAC electrical loads. Earlier research has found that a common reason behind lack of impact from occupancy on plug loads and lighting is that equipment and lighting is turned on in office spaces with no one present. This was not the case in the present study. The study failed to identify the reason behind plug loads and lighting having poor correlation with occupancy. Further research of the matter is encouraged. Methods for improving energy efficiency in office buildings in relation to teleworking includes presence-based control strategies for HVAC systems and lighting, energy efficient behaviour, consolidating office space, and hotdesking. Due to the lack of reliable occupancy data, the study failed in quantifying the potential for energy saving in the building, regarding both district heating and electricity. The results give clear evidence of there being an energy saving potential, but not the extent of it. / Sedan covid-19 deklarerades som en pandemi av Världshälsoorganisationen WHO i mars 2020 har distansarbete tillämpats i allt högre grad av verksamheter världen över. Mycket tyder på att distansarbete kommer att bli en del av ”det nya normala”, varför studier på områden relaterade till distansarbete kommer att vara värdefulla ur energieffektiviseringsperspektiv på lång sikt. I syfte att ta reda på hur stor energibesparingspotential distansarbete kan medföra, och att identifiera åtgärdsförslag för att uppnå sådana besparingar, genomfördes en litteraturstudie samt en retrospektiv fallstudie av en kontorsbyggnad i Gävle. Personnärvaron under 2020 kartlades i samtal med representanter för den verksamhet som har kontor i byggnaden, medan uppgifter om energitillförseln, fördelad på fjärrvärme, fastighetsel och verksamhetsel, tillhandahölls av energileverantören. Det framkom att den fasta personnärvaron sjunkit med drygt 40 % i mitten av mars 2020, och att den från och med november 2020 utgjorde drygt 20 % av närvaron vid årets början. Inga samvariationer mellan energianvändning och personnärvaro observerades, och tillförseln av såväl fjärrvärme som fastighetsel och verksamhetsel var densamma vid årets slut som vid dess början. Behovet av uppvärmning, kylning och ventilation i ett kontor är detsamma oavsett hur många personer som befinner sig i det, vilket bedömdes vara orsaken till bristen på samvariationer mellan personnärvaro och fjärrvärme respektive fastighetsel. Tidigare studier har visat att en vanlig orsak till att personnärvaro har liten påverkan på verksamhetselkonsumtion är att utrustning och belysning är påslagna även i utrymmen där ingen uppehåller sig. Så var inte fallet i föreliggande studie. Studien kunde inte identifiera orsaken till att användning av verksamhetsel inte följde variationerna i personnärvaro, varför ytterligare forskning är nödvändig. Metoder för energieffektivisering i kontorsbyggnader vid distansarbete inkluderar närvarostyrd teknologi, energimedvetet beteende, minskning av totalt utnyttjat kontorsutrymme samt hotdesking. Då personnärvaron inte kunde kartläggas med tillfredsställande precision i föreliggande studie var det inte möjligt att kvantifiera byggnadens energieffektiviseringspotential, varken för fjärrvärme eller elektricitet. Studiens resultat visar tydligt att energibesparingspotential föreligger, men inte i vilket omfång.

Building energy usage can be derived and controlled by performing building energy modeling. BEM can be performed using numerous software tools such as DesignBuilder, OpenStudio, EnergyPlus etc. These modeling tools can be sorted into three different modeling categories: Black-box, Gray-box and White-box. It is important for a modeler to be able to quickly select the proper tool from the proper category to meet the need of the project. To validate the method of categorizing tools, the three models generated using tools from each category and the modeling outputs required were compared. Each model was designed to estimate the amount of heat transfer through building envelope elements. All the modeling tools were able to generate the required output, therefore, the method for selecting the most effective tool will be based on the output requirements and the time it takes to build the model, time it takes to generate the output and interpret the output.

<p dir="ltr">Personalized thermal controls are beneficial for occupant comfort and productivity in office buildings. Recent research efforts on learning personal thermal comfort support the integration of personalized preferences in optimal building control and further implementation in real buildings. This Thesis presents the development and field implementation of personal preference-based thermal control in real offices, emphasizing the role of model predictive control (MPC) and low-cost local sensing. Probabilistic thermal preference profiles, a low-cost thermal sensing network and a MPC framework were integrated into a centralized building management and control system. The customized, preference-based HVAC control implemented in the offices indicated the comfort benefits of monitoring local thermal conditions (vs wall thermostats) for different preference profiles and showed 28-35% energy savings with personalized MPC (vs personalized static setpoint control).</p><p dir="ltr">Regarding the practical limitations in collecting sufficient data from occupants to train their thermal comfort model, we present a Bayesian meta-learning approach for developing reliable, data-driven personalized thermal comfort models using limited data from individuals. A high-dimensional neural network was developed, considering general thermal comfort impact factors (environmental variables, clothing level and metabolic rate) as well as personal thermal characteristics (expressed as a vector of continuous latent variables) as model inputs. The model parameters in the neural network were trained with subsets of ASHRAE RP-884 database. The trained neural network is transferrable, so that the thermal preferences of new individuals can be predicted by inferring their personal thermal characteristics using limited data. The results show that the developed Bayesian meta-learning approach to infer personal thermal comfort performs better than existing methods, especially when using limited data.</p><p dir="ltr">Moreover, this Thesis also discusses the potential of balancing thermal comfort and energy cost by setting dynamic temperature constraints in personalized MPC. A co-simulation framework of EnergyPlus and MPC is constructed using EnergyPlus Python API. Dynamic temperature constraints are selected based on personal thermal profile, weather conditions and utility rate variations. The performance of the personalized MPC with dynamic constraints demonstrates a balance between thermal comfort and energy cost in cooling season.</p>

Цель работы – создание математической модели технологического процесса энергопотребления здания, создание набора данных, создание нейросети для прогнозирования энергопотребления здания, выявление закономерностей и аномалий. Объект исследования – энергопотребление здания. Рассматриваются различные факторы, такие как работа системы кондиционирования, системы подачи воды, бытовые приборы, освещение помещения. Детально рассмотрена система кондиционирования. Построена математическая модель в итераторе OpenModelica, учитывающая факторы внешней и внутренней среды здания. Собран набор данных в формате .csv. Проведён анализ результатов, выявлены взаимодействия признаков системы, аномалии влияющие на энергопотребление здания. Написана нейросеть прогнозирующая энергопотребление здания, создан pipeline для выявления и визуализации аномалий. Результаты представлены на графиках, сделаны выводы. В ходе полученных результатов были предложены методы оптимизации работы системы, которые привели к экономическому и экологическому эффекту. / The purpose of the work is to create a mathematical model of the technological process of energy consumption of a building, create a data set, create a neural network to predict the energy consumption of a building, identify patterns and anomalies. The object of study is the energy consumption of the building. Various factors are considered, such as the operation of the air conditioning system, water supply system, household appliances, and room lighting. The air conditioning system is examined in detail. A mathematical model was built in the OpenModelica iterator, considering the factors of the external and internal environment of the building. Collected data set in .csv format. An analysis of the results was carried out, interactions of system characteristics and anomalies affecting the energy consumption of the building were identified. A neural network was written to predict the energy consumption of a building, and a pipeline was created to identify and visualize anomalies. The results are presented in graphs and conclusions are drawn. As a result of the results obtained, methods were proposed to optimize the operation of the system, which led to economic and environmental benefits.

This paper presents an analysis of data supplied by the US Green Buildings Council on the credits achieved by 117 LEED-certified commercial and institutional buildings. The paper quantifies several relationships, among others it explores the correlation between building energy performance, water consumption and the overall amount of points the projects has achieved. The paper also attempts to identify which credits are not usually selected by type of project, ownership, certification level and climate zone.

According to the U.S. energy consumption survey in 2012, about 25% of the commercial and 42% of the residential building energy were used for heating. Despite the development of new and more efficient Heating, Ventilation, and Air Conditioning (HVAC) systems over the years, the high energy consumption in heating is still one of the major energy efficiency issues. Studies showed that decreasing HVAC operating temperature set points by 4°F will result in energy savings of 15% or more. Thus, the smart localized heating control (SLHC) system was designed and prototyped to provide localized heat directly to a person so that HVAC can run at a lower temperature set point. SLHC detects human movement and delivers the heat based on the result of the target location estimation and temperature measurement feedback. To detect the human movement, image processing techniques were used; image segmentation, mass center detection, background subtraction using the Mixture of Gaussian model, and human feature detection. In SLHC, a near-infrared heater and a tracking function were used to provide an instant and a direct heat to the person in order to minimize wasting energy. The SLHC system is divided into the sensing and processing (SP) and the heating and regulating (HR) subsystem. The SP’s primary function is to process captured video images and measured temperature data. SP also generates and sends the heater operating signal to HR. HR purposes to control the heater’s direction and power based on the signal. The communication between SP and HR was established through Wi-Fi enabled development platform. The SLHC prototype successfully processed the sensing data and transmitted the control signal. The result shows that it detected human movement and estimated the person’s location in 3D space within 10% margin of error. Also, it delivered the focused heat to the surface of the human body and increased the temperature by 10.0°F in 3 minutes at the distance of 1.5m away from the heater. This cost-effective, wireless, and localized heating system demonstrates the potential to improve energy efficiency in buildings. / Electrical and Computer Engineering