Dissertations / Theses on the topic 'Energy benchmarks'

This research establishes comprehensive and improved energy consumption benchmarks for Australian tertiary education facilities. It examines the audit of energy end use in various functional areas in a sample of tertiary education institutions to identify, control and reduce electrical energy used in typical existing campus buildings. Many Australian universities have data available for energy consumption of their total campus and selected individual whole buildings. However, as the typical tertiary campus is characterised by a large and diversified portfolio of buildings with differing architecture, facades, occupancy and services, energy comparison between buildings does not provide useful information. This differs from energy use and management in general commercial office buildings. Universities also have different disciplines performing different activities that are not directly comparable. For instance, a campus with a medical school or molecular science building (service equipment intensive type) has a different energy use profile from one that does not. This research develops a common tertiary education functional typology within different campus buildings, grouped according to significant architectural features, energy intensity and use, to establish appropriate energy benchmarks for common functional areas such as offices, lecture rooms and laboratories. Assessment of these common functional areas by energy audit allows quantitative comparison between functional areas, and between diverse whole buildings. It also provides a rational basis for establishing performance targets for buildings at the early design stage by aggregation of functional areas. Benchmarking these areas allows energy managers to manage by exception and the benchmarking process enables managers to practise continuous improvement. The knowledge and data from this study enables researchers to focus on those factors that specifically affect energy use for particular activities. This enables building energy managers to discern and rank those major factors that determine energy consumption, allowing them to concentrate their performance efforts on the most energy efficient measures. The benchmarks derived in this study came from audits of 24 buildings at the University of Sydney campus across a five-year period (2009–2014) comprising over 80 distinct functional areas. Using this data, together with local and overseas sources, the LLO functional area energy benchmark tool was developed. LLO is an acronym derived from the surnames of the researcher and two colleagues who discussed the development of the University of Sydney graduate energy audit program in 2009.

The South African Government has ambitious aspirations relating to energy efficiency in their commercial building stock, but no clear strategy for tackling existing buildings. This research redresses this by examining international approaches to the benchmarking process and applies these in the context of South Africa.

Thesis (M.S.)--Michigan State University. Interdepartmental Physical Sciences, 2008.
Title from PDF t.p. (viewed on July 29, 2009) Includes bibliographical references (p. 378-380). Also issued in print.

To achieve agreed targets for reducing global carbon emissions, industry must become more resource-efficient. To this end, two viable strategies exist: energy efficiency and material efficiency. Despite their inherent interdependence, industry continues to treat these two strategies as isolated pursuits, providing in the process only a partial insight into the potential of resource efficiency. To resolve this disconnect, this thesis attempts to develop and apply tools that help integrate industrial energy and material efficiency analyses. Three areas of research are explored. The first is concerned with a fundamental component of industrial performance: efficiency benchmarks. No agreed-upon metric exists to measure the efficiency with which the sector trans- forms both energy and materials - that is, how resource-efficient they are. This thesis applies exergy - a well-established method to consolidate energy and materials into a single metric - to a case study of the global steel industry in 2010. Results show that this exergy-based metric provides a suitable proxy to capture the interactions between energy and materials. By comparing energy and material efficiency options on an equal footing, this metric encourages the recovery of material by-products - an intervention excluded from traditional energy efficiency metrics. To realise resource efficiency opportunities, individual industry firms must be able to identify them at actionable time-frames and scopes. Doing this hinges on understanding resources flows through entire systems, the most detailed knowledge of which resides in control data. No academic study was found to exploit control data to construct an integrated picture of resources that is representative of real operations. In the second research area, control data is extracted to track the resource flows and efficiency of a basic oxygen steel-making plant from TataSteel. This second case study highlights the plant's material efficiency options during operations. It does so by building close-to-real-time Sankey diagrams of resource flows (measured in units of exergy) for the entire plant and its constituent processes. Without the support of effective policies the new exergy approach is unlikely to be widely adopted in industry. By collating evidence from interviews and policy documents, the third area explores why the European Union's industrial energy and emissions policies do not incentivise material efficiency. Results suggest several contributing factors, including: the inadequacy of monitored indicators; an imposed policy lock-in; and the lack of a designated industry lobby and high-level political buy-in. Policy interventions are then proposed to help integrate material efficiency into energy and climate agendas. The European Union's limited agency stresses the need for Member States and industry to drive the move to a low-carbon industry in the short-term.

La consommation énergétique augmente dans les technologies informatiques, notamment à cause de l'augmentation de l'utilisation des services web et distribuée, l'informatique dans les nuages, ou les appareils mobiles. Par conséquent, des approches de gestion de l'énergie ont été développées, de l'optimisation du code des logiciels, à des stratégies d'adaptation basées sur l'utilisation des ressources matérielles. Afin de répondre à ces lacunes, nous présentons dans cette thèse, des modèles énergétiques, approches et outils pour estimer fidèlement la consommation énergétique des logiciels, au niveau de l'application, et au niveau du code, et pour inférer le modèle d'évolution énergétique des méthodes basé sur leurs paramètres d'entrées. Nous proposons aussi Jalen et Jalen Unit, des frameworks énergétiques pour estimer la consommation énergétique de chaque portion de code de l'application, et pour inférer le modèle d'évolution énergétique des méthodes en se basant sur des études et expériences empiriques. En utilisant des modèles énergétiques et d’outils d'estimations logicielles, nous pouvons proposer des informations énergétiques précises sans avoir besoin de wattmètres ou d'investissement de matériels de mesures énergétiques. Les informations énergétiques que nous proposons, offrent aussi aux approches de gestion énergétique des mesures directes et précises pour leurs approches d'adaptations et d'optimisations énergétiques. Ces informations énergétiques établissent aussi un modèle d'évolution énergétique des logiciels en se basant sur leurs paramètres d'entrées. Cela offre aux développeurs une connaissance plus profonde sur l'efficacité énergétique dans les logiciels
With the rise of the usage of computers and mobile devices, and the higher price of electricity, energy management of software has become a necessity for sustainable software, devices and IT services. Energy consumption in IT is rising through the rise of web and distributed services, cloud computing, or mobile devices. However, these approaches do not use proper energy information for their adaptations rendering themselves limited and not energy-aware. They do not provide an energy feedback of software, and limited information is available on how and where energy is spend in software code. To address these shortcomings, we present, in this thesis, energy models, approaches and tools in order to accurately estimate the energy consumption of software at the application level, at the code level, and for inferring energy evolution models based on the method's own input parameters. We also propose Jalen and Jalen Unit, energy frameworks for estimating how much energy each portion of code consumes, and for inferring energy evolution models based on empirical benchmarking of software methods. By using software estimations and energy models, we are able to provide accurate energy information without the need of power meters or hardware energy investment. The energy information we provide also gives energy management approaches direct and accurate energy measurements for their adaptations and optimizations. Provided energy information also draws a model of energy consumption evolution of software based on the values of their input parameters. This gives developers knowledge on energy efficiency in software leading to choose some code over others based on their energy performance

There is evidence that hotels are the highest energy use buildings of the tertiary sector in Europe and internationally because of their operational characteristics and the large number of users. Therefore, there is potential for significant energy savings. This study investigated the energy performance of the hotel sector in Greece and proposes a methodology for their energy classification and climate change mitigation strategies for an optimum building envelope design for a typical hotel building operated all year or seasonally. This was achieved by collecting operational energy data for 90 Greek hotels and analyzing them using the k-means algorithm. Then a typical hotel building was modelled using TRNSYS and climate change weather files to assess the impact on its energy demand and to propose climate change mitigation strategies. The assessment was performed via hourly simulations with real climatic data for the past and generated future data for the years 2020, 2050 and 2080. The analysis of the energy data (based on utilities supply) of 90 hotels shows average consumption approx 290 kWh/m2/year for hotels with annual operation and 200 kWh/m2/year for hotels with seasonal operation. Furthermore, the hotels were classified in well separated clusters in terms of their electricity and oil consumption. The classification showed that each cluster has high average energy consumption compared to other buildings in Greece. Cooling energy demand of the typical building increased by 33% and heating energy demand decreased by 22% in 2010 compared to 1970. Cooling load is expected to rise by 15% in year 2020, 34% in year 2050 and 63% in year 2080 compared to year 1970. Heating load is expected to decrease by 14% in year 2020, 29% in year 2050 and 46% in year 2080. It was found that different strategies can be applied to all year and seasonally operated buildings for the most energy efficient performance. These include: a. For all year operated buildings: insulation, double low e glazing, intelligently controlled night and day ventilation, ceiling fans and shading. The building of year 2050 would need more shading and the building of year 2080 would need additional shading and cool materials. b. For seasonally operated buildings: Intelligently controlled night and day ventilation, cool materials, ceiling fans, shading and double low e glazing. Only the building of year 2080 would need insulation. This study makes a contribution to understanding the impact of the climate change on the energy demand of hotel buildings and proposes mitigation strategies that focus on the building envelope in different periods and climatic zones of Greece.

This document gives an overview of the proposed MSc study. The main goal of the study is to model the cases listed in the code benchmark study of the International Atomic Energy Agency CRP–6 fuel performance study (Verfondern & Lee, 2005). The platform that will be employed is the GETTER code (Keshaw & van der Merwe, 2006). GETTER was used at PBMR for the release calculations of metallic and some non–metallic long–lived fission products. GETTER calculates the transport of fission products from their point of fission to release from the fuel surface taking into account gas precursors and activation products. Results show that for certain experiments the codes correspond very well with the experimental data whilst in others there are orders of magnitude differences. It can be seen that very similar behaviour is observed in all codes. Improvements are needed in updating the strontium diffusion coefficient and in understanding, on a deeper level, the transport of silver in TRISO particles and how it deviates from simple diffusion models.
Thesis (M.Sc. Engineering Sciences (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2012.

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This paper investigates a new scheme for fault detection and isolation based on time series and data analysis. This scheme is applied in a wind turbine model and illustrates the power of the proposed approach in the context of renewable energy. The proposed scheme is performed in two steps and it is based on process data without using any kind of mathematical modeling. The first step, the fault detection, is based on an alternative method based on the Gibbs sampling algorithm in which the occurrence of a sensor fault is modeled as a change point detection in a time series. The second step, the fault isolation, is handled via a Fuzzy/Bayesian network scheme classifying the kind of fault. This approach presented a good performance for detection and diagnostics of sensor faults in a standard wind turbine benchmark. In addition, this work presents proposals for research extension with enhancements of the fault detection and isolation system and formulation of fault tolerant control system.
Esse trabalho apresenta um novo esquema para detecção e isolamento de falhas baseado na análise de séries temporais e dados do processo. A metodologia é aplicada a um modelo de turbina eólica, e ilustra o potencial da abordagem proposta no contexto de energia renovável. A estratégia proposta é realizada em duas etapas e se baseia apenas em dados do processo sem o uso de qualquer tipo de modelo matemático do sistema. O primeiro passo, a detecção de falha, é realizado com base em amostragem de Gibbs, no qual a ocorrêcia de uma falha, seja ela num sensor, num atuador ou na planta, é modelada como uma detecção de novidades em séries temporais. O segundo passo, é o isolamento de falhas, realizado por meio de redes fuzzy/Bayesianas capazes de classificar cada tipo de falha de forma isolada ou simultânea. A abordagem proposta apresentou bons resultados para detecção e diagnóstico de falhas em sensores num benchmark padrão de turbina eólica. O trabalho ainda apresenta propostas de extensão da pesquisa com melhorias no sistema de detecção e isolamento de falhas e formulação de sistemas de controle tolerante a falhas também baseados em dados.

Thesis (MBA)--Stellenbosch University, 2011.
The world as we know it is in a warming cycle. The rate of warming is being exacerbated by human activity; more specifically, the burning of fossil fuels to power expanding economies. Awareness that something must be done before a catastrophic point of no return is reached, has become more urgent. Before any strategies can be developed to reduce greenhouse gas emissions, the levels must be accurately measured to provide a benchmark and to determine reduction targets. The determination of an organisation’s carbon footprint is thus the starting point of the whole process. When the carbon footprint is known, various strategies can be implemented to reduce the carbon footprint. South Africa is classified as a developing country and is not required to comply with greenhouse gas reduction targets under the Kyoto Protocol. This may change at any time in the future and it is therefore necessary to be ready when targets become compulsory. The general public is not knowledgeable about global warming. All of these factors need to change to provide impetus to reduction strategies. The South African Police Service (SAPS) is one of the largest government departments and is situated in nearly every town in South Africa. The SAPS is thus in a position to provide leadership in government and in communities on issues like global warming. The carbon footprint of the SAPS has been calculated as prescribed by the Greenhouse Gas Protocol (2011). As a service organisation, the SAPS does not have industrial processes that may be the source of large quantities of greenhouse gases. In this research study, Scope 1 and scope 2 emissions were calculated and possible mitigation options are proposed. A survey conducted among a specific target group has indicated a general understanding of the concept of climate change. The respondents have difficulty in establishing a connection between climate change and increased crime levels. Behavioural change and education are necessary to promote a culture of energy efficiency and a reduction of greenhouse gases. Leadership is seen as an inhibiting factor, as top management does not consider global warming to be an influencing factor on crime levels. Government must provide strong leadership and formulate climate change strategies. Funding can be generated with carbon tax and emissions trading. On departmental level the energy efficiency of buildings can be improved and alternative fuels for vehicles be used.

Tsunami are a fascinating but potentially devastating natural phenomena that have occurred regularly throughout history along New Zealand's shorelines, and around the world. With increasing population and the construction of infrastructure in coastal zones, the effect of these large waves has become a major concern. Many natural phenomena are capable of creating tsunami. Of particular concern is the underwater landslide-induced tsunami, due to the potentially short warning before waves reach the shore. The aims of this research are to generate a quality benchmark dataset suitable for comprehensive comparisons with numerical model results and to increase our understanding of the physical processes involved in tsunami generation. The two-dimensional experimental configuration is based on a benchmark configuration described in the scientific literature, consisting of a semi-elliptical prism sliding down a submerged 15° slope. A unique feature of these experiments is the method developed to measure water surface variation continuously in both space and time. Water levels are obtained using an optical technique based on laser induced fluorescence, which is shown to be comparable in accuracy and resolution to traditional electrical point wave gauges. In the experiments, the landslide density and initial submergence are varied and detailed measurements of wave heights, lengths, propagation speeds, and shore run-up are made. Particle tracking velocimetry is used to record the landslide kinematics and sub-surface water velocities. Particular attention is paid to maintaining a high level of test repeatability throughout the experimental process. The experimental results show that a region of high pressure ahead of the landslide forces up the water over the front half of the landslide to form the leading wave crest, which propagates ahead of the landslide. The accelerating fluid above, and the turbulent wake behind, the moving landslide create a region of low pressure, which draws down the water surface above the rear half of the landslide to form the leading trough. Differences in the phase and group velocities of the components in the wave packet cause waves to be continually generated on the trailing end of the wave train. The downstream position that these waves form continually moves downstream with time and the wave packet is found to be highly dispersive. The interaction of the landslide pressure field with the free surface wave pressure field is important, as the location of the low pressure around the landslide relative to the wave field acts to reinforce or suppress the waves above. This has a substantial effect on the increase or decrease in wave potential energy. When the low pressure acts to draw down a wave trough, the wave potential energy increases. When the low pressure is below a wave crest, it acts to suppress the crest amplitude, leading to an overall decrease in wave potential energy. Measurements of the efficiency of energy transfer from the landslide to the wave field show that the ratio of maximum wave potential energy to maximum landslide kinetic energy is between 0.028 and 0.138, and tends to increase for shallower initial landslide submergences and heavier specific gravities. The ratio of maximum wave potential energy to maximum landslide potential energy ranges between 0.011 and 0.059 and tends to be greater for shallower initial submergences. For two experimental configurations the ratio of maximum wave potential energy to maximum fluid kinetic energy is estimated to be 0.435 and 0.588. The wave trough initially generated above the rear end of the landslide propagates in both onshore and offshore directions. The onshore-propagating trough causes a large initial draw-down at the shore. The magnitude of the maximum draw-down is related to the maximum amplitude of the offshore-propagating first wave trough. A wave crest generated by the landslide as it decelerates at the bottom of the slope causes the maximum wave run-up observed at the shore. A semi-analytical model, based on inviscid and irrotational theory, is used to investigate the wave generation process of a moving submerged object in a constant depth channel. The simplified geometry allows a variety of phenomena, observed during the experimental tests, to be investigated further in a more controlled setting. The variations in the growth, magnitude, and decay of energy as a function of time is due the interaction of the pressure distribution surrounding the moving slider with the wave field, in particular, the leading crest and trough. The largest energy transfer between slider kinetic energy and wave potential energy occurs when there is prolonged interaction between the slider's low pressure region and the leading wave trough. The generation of onshore propagating waves by a decelerating landslide is confirmed, and the magnitude of the maximum wave run-up is found to be dependent on the magnitude of the slider deceleration. The model also shows that slides with Froude number close to unity convert substantial amounts of energy into offshore propagating waves. The onshore propagating wave potential energy is not as sensitive to Froude number. A further result from the model simulations is that the specific shape of the slider has only a minor influence on the wave response, provided the slider's length and area are known. A boundary element model, based on inviscid and irrotational theory, is used to simulate the laboratory experiments. Model predictions of the wave field are generally accurate, particularly the magnitude and range of wave amplitudes within the wave packet, the arrival time of the wave group, the amplitude of the run-up and run-down at the shore, the time the maximum run-down occurs, and the form and magnitude of the wave potential energy time history. The ratios of maximum wave potential energy to maximum slider kinetic energy are predicted to within ± 29%. The model predictions of the crest arrival times are within 3.6% of the measured times. The inability of the inviscid and irrotational model to simulate the flow separation and wake motions lead to a 45% under prediction of the maximum fluid kinetic energy. Both the semi-analytical and BEM models highlight the need for the correct specification of initial slider accelerations in numerical simulations in order to accurately predict the wave energy.

S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.

The energy consumption of large-scale high-performance computer (HPC) systems has become one of the foremost concerns of both data-center operators and computer manufacturers. This has renewed interest in alternative computer architectures that could offer substantially better energy-efficiency.Yet, the for the evaluation of the potential of these architectures necessary well-optimized implementations of typical HPC benchmarks are often not available for these for the HPC industry novel architectures. The in this work presented LU factorization benchmark implementation aims to provide such a high-quality tool for the HPC industry standard high-performance LINPACK benchmark (HPL) for the eight-core Texas Instruments TMS320C6678 digitalsignal processor (DSP). The presented implementation could perform the LU factorization at up to 30.9 GF/s at 1.25 GHz core clock frequency by using all the eight DSP cores of the System-on-Chip (SoC). This is 77% of the attainable peak double-precision floating-point performance of the DSP, a level of efficiency that is comparable to the efficiency expected on traditional x86-based processor architectures. A presented detailed performance analysis shows that this is largely due to the optimized implementation of the embedded generalized matrix-matrix multiplication (GEMM). For this operation, the on-chip direct memory access (DMA) engines were used to transfer the necessary data from the external DDR3 memory to the core-private and shared scratchpad memory. This allowed to overlap the data transfer with computations on the DSP cores. The computations were in turn optimized by using software pipeline techniques and were partly implemented in assembly language. With these optimization the performance of the matrix multiplication reached up to 95% of attainable peak performance. A detailed description of these two key optimization techniques and their application to the LU factorization is included. Using a specially instrumented Advantech TMDXEVM6678L evaluation module, described in detail in related work, allowed to measure the SoC’s energy efficiency of up to 2.92 GF/J while executing the presented benchmark. Results from the verification of the benchmark execution using standard HPL correctness checks and an uncertainty analysis of the experimentally gathered data are also presented.
Energiförbrukningen av storskaliga högpresterande datorsystem (HPC) har blivit ett av de främsta problemen för såväl ägare av dessa system som datortillverkare. Det har lett till ett förnyat intresse för alternativa datorarkitekturer som kan vara betydligt mer effektiva ur energiförbrukningssynpunkt. För detaljerade analyser av prestanda och energiförbrukning av dessa för HPC-industrin nya arkitekturer krävs väloptimerade implementationer av standard HPC-bänkmärkningsproblem. Syftet med detta examensarbete är att tillhandhålla ett sådant högkvalitativt verktyg i form av en implementation av ett bänkmärkesprogram för LU-faktorisering för den åttakärniga digitala signalprocessorn (DSP) TMS320C6678 från Texas Instruments. Bänkmärkningsproblemet är samma som för det inom HPC-industrin välkända bänkmärket “high-performance LINPACK” (HPL). Den här presenterade implementationen nådde upp till en prestanda av 30,9 GF/s vid 1,25 GHz klockfrekvens genom att samtidigt använda alla åtta kärnor i DSP:n. Detta motsvarar 77% av den teoretiskt uppnåbara prestandan, vilket är jämförbart med förväntningar på effektivteten av mer traditionella x86-baserade system. En detaljerad prestandaanalys visar att detta tillstor del uppnås genom den högoptimerade implementationen av den ingående matris-matris-multiplikationen. Användandet av specialiserade “direct memory access” (DMA) hårdvaruenheter för kopieringen av data mellan det externa DDR3 minnet och det interna kärn-privata och delade arbetsminnet tillät att överlappa dessa operationer med beräkningar. Optimerade mjukvaruimplementationer av dessa beräkningar, delvis utförda i maskinspåk, tillät att utföra matris-multiplikationen med upp till 95% av den teoretiskt nåbara prestandan. I rapporten ges en detaljerad beskrivning av dessa två nyckeltekniker. Energiförbrukningen vid exekvering av det implementerade bänkmärket kunde med hjälp av en för ändamålet anpassad Advantech TMDXEVM6678L evalueringsmodul bestämmas till maximalt 2,92 GF/J. Resultat från verifikationen av bänkmärkesimplementationen och en uppskattning av mätosäkerheten vid de experimentella mätningarna presenteras också.

Les Etudes Probabilistes de Sûreté (EPS) de niveau 2 en centrale nucléaire visent à identifier les séquences d’événements pouvant correspondre à la propagation d’un accident d’un endommagement du cœur jusqu’à une perte potentielle de l’intégrité de l’enceinte, et à estimer la fréquence d’apparition des différents scénarios possibles.

Ces accidents sévères dépendent non seulement de défaillances matérielles ou d’erreurs humaines, mais également de l’occurrence de phénomènes physiques, tels que des explosions vapeur ou hydrogène. La prise en compte de tels phénomènes dans le cadre booléen des arbres d’événements s’avère difficile, et les méthodologies dynamiques de réalisation des EPS sont censées fournir une manière plus cohérente d’intégrer l’évolution du processus physique dans les changements de configuration discrète de la centrale au long d’un transitoire accidentel.

Cette thèse décrit l’application d’une des plus récentes approches dynamiques des EPS – la Théorie de la Dynamique Probabiliste basée sur les Stimuli (SDTPD) – à différents modèles de déflagration d'hydrogène ainsi que les développements qui ont permis cette applications et les diverses améliorations et techniques qui ont été mises en oeuvre.

Level-2 Probabilistic Safety Analyses (PSA) of nuclear power plants aims to identify the possible sequences of events corresponding to an accident propagation from a core damage to a potential loss of integrity of the containment, and to assess the frequency of occurrence of the different scenarios.

These so-called severe accidents depend not only on hardware failures and human errors, but also on the occurrence of physical phenomena such as e.g. steam or hydrogen explosions. Handling these phenomena in the classical Boolean framework of event trees is not convenient, and dynamic methodologies to perform PSA studies are expected to provide a more consistent way of integrating the physical process evolution with the discrete changes of plant configuration along an accidental transient.

This PhD Thesis presents the application of one of the most recently proposed dynamic PSA methodologies, i.e. the Stimulus-Driven Theory of Probabilistic Dynamics (SDTPD), to several models of hydrogen explosion in the containment of a plant, as well as the developed methods and improvements.

Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

Multi functional health monitoring wearable devices are quite prominent these days. Usually these devices are battery-operated and consequently are limited by their battery life (from few hours to a few weeks depending on the application). Of late, it was realized that these devices, which are currently being operated at fixed voltage and frequency, are capable of operating at multiple voltages and frequencies. By switching these voltages and frequencies to lower values based upon power requirements, these devices can achieve tremendous benefits in the form of energy savings. Dynamic Voltage and Frequency Scaling (DVFS) techniques have proven to be handy in this situation for an efficient trade-off between energy and timely behavior. Within imec, wearable devices make use of the indigenously developed MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). This system is optimized for efficient and accurate collection, processing, and transfer of data from multiple (health) sensors. MUSEIC v2 has limited means in controlling the voltage and frequency dynamically. In this thesis we explore how traditional DVFS techniques can be applied to the MUSEIC v2. Experiments were conducted to find out the optimum power modes to efficiently operate and also to scale up-down the supply voltage and frequency. Considering the overhead caused when switching voltage and frequency, transition analysis was also done. Real-time and non real-time benchmarks were implemented based on these techniques and their performance results were obtained and analyzed. In this process, several state of the art scheduling algorithms and scaling techniques were reviewed in identifying a suitable technique. Using our proposed scaling technique implementation, we have achieved 86.95% power reduction in average, in contrast to the conventional way of the MUSEIC v2 chip’s processor operating at a fixed voltage and frequency. Techniques that include light sleep and deep sleep mode were also studied and implemented, which tested the system’s capability in accommodating Dynamic Power Management (DPM) techniques that can achieve greater benefits. A novel approach for implementing the deep sleep mechanism was also proposed and found that it can obtain up to 71.54% power savings, when compared to a traditional way of executing deep sleep mode.
Nuförtiden så har multifunktionella bärbara hälsoenheter fått en betydande roll. Dessa enheter drivs vanligtvis av batterier och är därför begränsade av batteritiden (från ett par timmar till ett par veckor beroende på tillämpningen). På senaste tiden har det framkommit att dessa enheter som används vid en fast spänning och frekvens kan användas vid flera spänningar och frekvenser. Genom att byta till lägre spänning och frekvens på grund av effektbehov så kan enheterna få enorma fördelar när det kommer till energibesparing. Dynamisk skalning av spänning och frekvens-tekniker (såkallad Dynamic Voltage and Frequency Scaling, DVFS) har visat sig vara användbara i detta sammanhang för en effektiv avvägning mellan energi och beteende. Hos Imec så använder sig bärbara enheter av den internt utvecklade MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). Systemet är optimerat för effektiv och korrekt insamling, bearbetning och överföring av data från flera (hälso) sensorer. MUSEIC v2 har begränsad möjlighet att styra spänningen och frekvensen dynamiskt. I detta examensarbete undersöker vi hur traditionella DVFS-tekniker kan appliceras på MUSEIC v2. Experiment utfördes för att ta reda på de optimala effektlägena och för att effektivt kunna styra och även skala upp matningsspänningen och frekvensen. Eftersom att ”overhead” skapades vid växling av spänning och frekvens gjordes också en övergångsanalys. Realtidsoch icke-realtidskalkyler genomfördes baserat på dessa tekniker och resultaten sammanställdes och analyserades. I denna process granskades flera toppmoderna schemaläggningsalgoritmer och skalningstekniker för att hitta en lämplig teknik. Genom att använda vår föreslagna skalningsteknikimplementering har vi uppnått 86,95% effektreduktion i jämförelse med det konventionella sättet att MUSEIC v2-chipets processor arbetar med en fast spänning och frekvens. Tekniker som inkluderar lätt sömn och djupt sömnläge studerades och implementerades, vilket testade systemets förmåga att tillgodose DPM-tekniker (Dynamic Power Management) som kan uppnå ännu större fördelar. En ny metod för att genomföra den djupa sömnmekanismen föreslogs också och enligt erhållna resultat så kan den ge upp till 71,54% lägre energiförbrukning jämfört med det traditionella sättet att implementera djupt sömnläge.

abstract: According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI pertinent to the building type. The ability to identify and rank the important variables is of great importance in practical implementation of the benchmarking tools which rely on query-based building and HVAC variable filters specified by the user.
Dissertation/Thesis
M.S. Built Environment 2013

Benchmark calculations are performed for neutron transport in a two material (binary) stochastic multiplying medium. Spatial, angular, and energy dependence are included. The problem considered is based on a fuel assembly of a common pressurized water nuclear reactor. The mean chord length through the assembly is determined and used as the planar geometry system length. According to assumed or calculated material distributions, this system length is populated with alternating fuel and moderator segments of random size. Neutron flux distributions are numerically computed using a discretized form of the Boltzmann transport equation employing diffusion synthetic acceleration. Average quantities (group fluxes and k-eigenvalue) and variances are calculated from an ensemble of realizations of the mixing statistics. The effects of varying two parameters in the fuel, two different boundary conditions, and three different sets of mixing statistics are assessed. A probability distribution function (PDF) of the k-eigenvalue is generated and compared with previous research. Atomic mix solutions are compared with these benchmark ensemble average flux and k-eigenvalue solutions. Mixing statistics with large standard deviations give the most widely varying ensemble solutions of the flux and k-eigenvalue. The shape of the k-eigenvalue PDF qualitatively agrees with previous work. Its overall shape is independent of variations in fuel cross-sections for the problems considered, but its width is impacted by these variations. Statistical distributions with smaller standard deviations alter the shape of this PDF toward a normal distribution. The atomic mix approximation yields large over-predictions of the ensemble average k-eigenvalue and under-predictions of the flux. Qualitatively correct flux shapes are obtained, however. These benchmark calculations indicate that a model which includes higher statistical moments of the mixing statistics is needed for accurate predictions of binary stochastic media k-eigenvalue problems. This is consistent with previous findings.
Graduation date: 2005

INTRODUÇÃO: O CrossFit é caracterizado por movimentos funcionais constantemente variados realizados a uma intensidade elevada. Apesar da sua popularidade, os dados científicos sobre a sua prática e efeitos são escassos. Logo, o objetivo desta investigação foi: 1) Caracterizar a resposta fisiológica a tarefas típicas de CrossFit®; 2) Averiguar o efeito de um período de treino de CrossFit® nas capacidades aeróbia e anaeróbia. MÉTODOS: Participaram 12 atletas do sexo masculino no estudo I (Idade: 28,67 ± 5anos; Peso: 75,34 ± 8,26kg; Altura: 175,5 ± 6,10cm; %MG: 10,64 ± 3,30%; MIG: 65,07 ± 6,10kg; $̇O2PICO: 49,33 ± 4,23ml.kg- 1min-1) e 8 atletas no estudo II (Idade: 28,62 ± 7,63anos; Peso: 78,39 ± 10,03kg; Altura: 175,9 ± 4,28cm; %MG: 12,51 ± 5,33%; MIG: 65,05 ± 4,85kg; $̇O2PICO: 48,88 ± 4,91ml.kg-1min-1;). O estudo 1 envolveu a caraterização da resposta fisiológica a duas tarefas típicas da modalidade, executados de modo a que o tempo da sua realização seja o mínimo possível, (Wod1: 3x (500metros em remoergómetro + 12 x Peso Morto + 21 saltos para a caixa com 61cm e Wod2: (21 x Peso Morto + 21 x “HSPU”) + (15 x Peso Morto + 15 x “HSPU”) + (9 x Peso Morto + 9 x “HSPU”) e a verificação da sua associação com parâmetros da capacidade aeróbia e anaeróbia para o que realizaram dois testes laboratoriais, um progressivo máximo e supramáximo. Nos testes laboratoriais, todos os atletas foram avaliados em passadeira, sendo as trocas gasosas quantificadas com a utilização de um analisador portátil (Metamax 3B, Cortex, Alemanha). A concentração de lactato no sangue [La-] foi medida usando o dispositivo portátil Lactate Pro 2™ (Arkray, Koji, Japão). A estimativa do custo aeróbio foi realizada a partir do volume de oxigénio acumulado utilizado durante a tarefa (WAER). A estimação da componente anaeróbia lática (W[La-]) foi realizada levando em conta o gradiente de lactatemia antes e depois do esforço a caracterizar. O custo anaeróbio alático (WALA) foi calculado a partir da fase rápida da curva de V̇ O2 de recuperação (EPOCRAPIDO). De modo a modelar a curva do V̇O2 (ml.kg-1.min- 1) para estimação da respetiva cinética, os dados foram recolhidos no modo “respiração a respiração” e sujeitos a uma modelação monoexponencial. No estudo 2 foram determinados os mesmos parâmetros fisiológicos antes e após 6 semanas de treino de CrossFit® tipificado e após 3 semanas de destreino. Foi ainda avaliado, nos mesmos momentos, o desempenho e a resposta fisiológica ao Wod1. RESULTADOS: No estudo I, a contribuição energética relativa (WAER; W[La-] e WALA) foi, no Wod1, 73,75 ± 3,4%; 17,61 ± 3,9% e 8,63 ± 4,9%, e no Wod2 46,83 ± 13,5%, 36,45 ± 14,2% e 16,7 ± 8% manifestando predominância do sistema aeróbio em ambos. As diferenças são decorrentes da duração exigida para a realização de cada um. No Wod1 foi encontrada uma correlação positiva entre a DuraçãoTOT e a constante temporal da cinética do V̇O2(tp) (r=0.582; p = 0.046), denotando a importância das adaptações aeróbias musculares para o desempenho. No Wod2 o V̇O2PICO mostrou-se associado à DuraçãoTOT (r=0,635; p=0,027), provavelmente indicando que o melhor desempenho depende das adaptações anaeróbias dos indivíduos. Relativamente ao estudo II, foram verificadas diferenças significativas no teste progressivo em: $̇O2PICO (ml.kg-1.min-1) (p = 0,000; +4,6% [pré - pós]); $̇O2PICO (L.min-1) (p = 0,016; +4,3% [pré - pós]) and LV2 (p = 0,000; +4,4% [pré - pós]) e no teste supramáximo, em: $̇O2PICO (ml.kg-1min-1) p = 0.03; [+4,4%]) e no $̇O2PICO (L.min-1) p = 0.03; [+4.8%]). Ainda no supramáximo, verificou-se um decréscimo da capacidade anaeróbia dos momentos de pré e pós treino para o destreino (p = <0,05). No Wod1 observou-se uma melhoria na vi DuraçãoTOT do Wod1 (p=0.000 [-3.3%]) diminuição significativa na FCPICO (bat.min-1) (p=0.010[-4.69%]); %FCPICO (p=0.014 [-5,29%]); $̇O2PICO (p=0.009 [-7,38%]) . Simultaneamente, verificou-se um aumento da contribuição do WAER (p=0.028; [+4,45%]). Relativamente à $̇O2k (intensidade moderada), observaram-se diferenças significativas ao nível da Ap (p=0.042); tdp (p=0.023) do pré para o pós treino e do pré-treino para o destreino (p=0,017) e (p=0,022) respetivamente. Na $̇O2k na intensidade supramáxima verificaram-se diferenças do pós-treino e pré-treino para o destreino na Ap (p=0.030 [pós]; p=0,046[pré]); $̇O2PICO (ml.kg- 1.min-1) (p=0.043 [pós]; p=0,045[pré]). CONCLUSÃO: Tanto quanto sabemos este é o primeiro estudo a caracterizar a resposta fisiológica a tarefas típicas de CrossFit® e averiguar o efeito de um período de treino de CrossFit® nas capacidades aeróbia e anaeróbia. Os dados indicam uma alta taxa metabólica no CrossFit®. Embora os exercícios com cargas adicionais elevadas exijam intensidades quase máximas sendo dominantemente anaeróbias, o elevado volume dos exercícios tornam a exigência dos Wod’s mais dependente da capacidade anaeróbia, mas também da potência aeróbia. Quer sejam longos (>10min) ou curtos (<2:30min), os Wod’s promovem concentrações láticas muito altas. Os dados também mostram que seis semanas de CrossFit®, induzem mudanças positivas nos indicadores cardiorrespiratórios e metabólicos, e que um período de destreino de três semanas é suficiente para causar perdas significativas nestes mesmos indicadores, no desempenho, assim como alterações na composição corporal.
PURPOSE: CrossFit is characterized by high intensity, constantly varied, functional movement. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the aim of this study was to: 1) characterize the physiological response in different CrossFit® Wod's and 2) to evaluate training effect in six weeks on aerobic and anaerobic capacity’s. METHODS Twelve male athletes participated in study I (Age: 28,67 ± 5.00yrs; Height: 175,50 ± 6.10cm; Weight: 75,34 ± 8,26kg; %BF:10,64 ± 3,30%; FFM: 65,07 ± 6.10kg; V̇O2PEAK: 49,33 ± 4,23ml.kg-1min-1) and 8 athletes in the study II (Age: 28.62 ± 7.63 years; Weight: 78.39 ± 10,03kg; Height: 175.9 ± 4.28cm;%BF: 12.51 ± 5.33; FFM: 65,05 ± 4,85kg; V̇O2PEAK: 48.88 ± 4.91ml.kg-1min-1; 3,82 ± 0,33L.min-1). Study I involved characterization of physiological response to two typical workouts (Wod’s), performed as quickly as possible (Wod1: 3x (500m on an indoor rower + 12x Dead Lifts + 21x box jump at 61cm and Wod2 (21x Dead Lifts + 21x HandStand Push-Up “HSPU”) + (15x Dead Lifts + 15x “HSPU”) + (9x Dead Lifts + 9x “HSPU”) and identify its association with aerobic and anaerobic capacity parameters for which two laboratory tests were performed, a maximal incremental test and a supramaximal test (110% Maximal Aerobic Speed). In the laboratory test, all athletes were evaluated on a treadmill, where the gas exchanges being quantified with the use of a portable analyzer (Metamax 3B, Cortex, Germany). Blood lactate [La-] was measured using the Lactate Pro 2 ™ portable device (Arkray, Koji, Japan). The estimation of aerobic cost (WAER) was performed from the accumulated oxygen volume used during the task. The estimation of lactic anaerobic component (W[La-]) was performed by taking into account the gradient of lactatemia before and after the effort to be characterized. The alactic anaerobic component (WPCR) was calculated from the V̇ O2 fast recovery phase curve (EPOCFAST). In order to modelling V̇O2 kinetics curve, data were collected by breath-by-breath mode and exposed to a monoexponential modelling. In study II, the same physiological parameters were determined before and after 6 weeks of CrossFit® training, and after 3 detraining weeks. Was also assessed at the same period, the performance and physiological response to Wod1. RESULTS: In study I, the relative energy contribution (WAER; W[La-] e WPCR) was, in, Wod1, 73,75 ± 3,4%; 17,61 ± 3,9% e 8,63 ± 4,9%, e no Wod2 46,83 ± 13,5%, 36,45 ± 14,2% e 16,7 ± 8% revealing aerobic system predominance in both Wod’s. The differences are due to the duration required for each one. In Wod1, a positive correlation was found between TimeTOT and the time constant of V̇ O2 kinetics (tp) (r=0.582; p=0.046), indicating the meaning of aerobic muscular adaptations for the performance. In Wod2 V̇ O2PEAK was associated to TimeTOT (r=0,635; p=0,027), denoting probably that the best performance depends of the anaerobic adaptations of the athletes. Regarding to study II, significant differences were shown in the maximal incremental test in: V̇ O2PEAK (ml.kg-1.min-1) (p=0,000; +4,6%[pre - post]); V̇ O2PEAK (L.min-1) (p=0,016; 4,3%[pre - post]) and VT2 (p=0,000;4,4% [pre - post]), and in the supramaximal test in: V̇ O2PEAK (ml.kg-1min-1) p=0.03 [+4,4%]) e no V̇ O2PEAK (L.min-1)p=0.03 [+4.8%]). Yet, in the supramaximal test there was a decrease in the anaerobic capacity from pre and post training to detraining (DT)(p= 10min) or short (<2:30min), Wod's endorse very high lactic concentrations. Data also shows that six weeks of CrossFit® induce positive changes in cardiorespiratory and metabolic indicators and that three week detraining period is enough to cause significant losses in these same performance indicators as well as changes in body composition.

碩士
國立臺北科技大學
機電整合研究所
91
Knowledge of energy consumption benchmark is very important to perform the energy conservation work in semiconductor fabs. In view of the importance, this thesis developed an energy analysis model especially for semiconductor fabs. The model was used in a standard 8’’ DRAM wafer fab, which has an annual wafer starts of 420,000。 The detailed energy benchmark of facility system, including the chiller plant, makeup air unit, recirculation air system, exhaust air system, compressed dry air, process cooling water, vacuum and ultra-pure water system was studied. The energy benchmark provided in this thesis can be used as a reference data to the similar research for other 8” wafer fabs. Some approaches to reduce energy consumption and their associated benefits are proposed and discussed.

碩士
國立臺北大學
自然資源與環境管理研究所
102
Energy use and carbon emissions increased after the Industrial Revolution. The industrial sector consumes over 40% energy end-use. Taiwan is transferring to a developed country that the proportion of service sector grows with time. However, the energy demand of the industrial sector was about 50 % in 2012, the industrial sector just contributed 38 % of GDP. Hence this represents that the energy input is unequal to the value of output. Energy efficiency is a”no regret strategy”. Green industry is a global trend; in consequence, the industrial sector needs to decrease the resource use. It’s a common situation that industrial energy efficiency policies are composed of benchmarks and the energy price. This study focuses on the “energy audit annual report for manufacturing industries” which large energy users submit to the Bureau of Energy. The conclutions of this study show that the energy intensity of metal industries, non-metallic mineral products manufacturings, paper mills and paper manufacturings, and computers, electronic and optical products manufacturings decrease significantly after the energy efficiency laws administering. The submission of data from the large energy users shows that as more energy used causes more investment in EE equipment; investing more capital would result in more energy conservation, thus makes more profits; the shorter payback is an incentive to invest; the longer payback leads the unit conservation cost to lessen. In Taiwan, the large-scale companies invest more EE equipment. Electricity, fuel-coal, and purchased steam are the key factors in investing behaviors; the higher proportion of electricity used and the more investment; but the higher proportion of electricity and lower energy conservation potentials.

博士
國立臺北科技大學
設計學院設計博士班
107
Aiming to evaluate power consumption in government office buildings and energy conservation strategies, this study targeted county and city government offices at all levels as sample buildings through the collection of power consumption information and purposive sampling, acquiring original source material through field investigations and personnel interviews. This research applied statistical analysis of building electricity evaluation indicators and equipment-specific capacity recommendations to obtain future projections for the same type of office buildings to incorporate a recommendation value of per capita power consumption into the calculation of the number of personnel. This recommendation value of power consumption evaluation was 0.7 kWh /person.㎡.year. Meanwhile, through the review of construction equipment specific load benchmarks, the surveyed data of suitable equipment was analyzed statistically to explore such equipment capacity benchmarks as applicable to specific office buildings. Finally, for suitable equipment, the capacity evaluation obtained was 0.022 kW/㎡, along with 0.065 kW/㎡ of air conditioning equipment and 0.011 kW/㎡ of lighting equipment. If the distribution of space in the building was clearly known in the evaluation stage, the air-conditioned area would be able to divide as follows: 0.027 kW/㎡of equipment capacity, 0.073 kW/㎡of the air-conditioning equipment and 0.013 kW/㎡of the lighting equipment. To understand the 3-way impact of building power consumption, user management behavior, and degree of personnel comfort, this study, after having confirmed that the impact factor on building characteristics was the direct solar radiation through regression, and affirming the selection of a building with external shading by technical analysis, an office building located in Yunlin was chosen as the model. After applying Design Builder, a dynamic energy consumption software, to simulate the building, the results indicated that the difference in annual power consumption of the air conditioner between human intervention mode and the non-intervention mode was 9%. The annual power consumption of non-intervention mode and the application that met the energy efficiency and relevant specifications would gain reduction by 3% and 11%, respectively. When the air conditioning operated in non-human intervention mode, the degree of comfort for people in the building would increase, thus greatly reducing those uncomfortable hours. This paper also applied simulation to explore the relevant impact factors of air conditioning power consumption operation and buildings under thermal equilibrium conditions. The results showed that, when a building is of equal area in all directions, the external condition depends on the obtained heat of the building exposed to solar radiation, which is as follows: open areas receive direct solar radiation throughout the year; in the northern and central part of the country the level of intensity decreases in the following order, with eastward > westward > southward > northward; and in the southern part the intensity decreases with westward > southward > eastward > north. When the density of personnel increased, the power consumption of air conditioners also increased through the obtained heat of personnel. The obtained heat on the air conditioners was simulated by the installation position of the LED lamps and the fluorescent lamps. The effect of the annual power consumption was as follows: the level of intensity decreases in this order, with T5 recessed Fluorescent Luminaire > T5 suspended Fluorescent Luminaire > T5 surface mount Fluorescent Luminaire > LED recessed Luminaire > LED suspended Luminaire> LED surface mount Luminaire. At the same time, this study also reviewed the selected sample buildings. Through the energy-saving strategy and simulation of the scheme, we obtained a conclusion that the improvement scheme would help reduce the power consumption of air-conditioning. The results of the final output of this study can provide a reference for the future development of assessment benchmarks for building power consumption, as well as the application strategies and procedures for efficiency improvement and benefit assessment of building energy conservation.

The ability of generating precise numerical forecasts is important to successful Enterprises in order to prepare themselves for undetermined future developments. For Utility companies, forecasts of prospective energy demand are a crucial component in order to maintain the physical stability and reliability of electricity grids. The constantly increasing capacity of fluctuating renewable energy sources creates a challenge in balancing power supply and demand. To allow for better integration, supply forecasting has become an important topic in the research field of energy data management and many new forecasting methods have been proposed in the literature. However, choosing the optimal solution for a specific forecasting problem remains a time- and work-intensive Task as meaningful benchmarks are rare and there is still no standard, easy-to-use, and robust approach. Many of the models in use are obtained by executing black-box machine learning tools and then manually optimized by human experts via trial-and-error towards the requirements of the underlying use case. Due to the lack of standardized Evaluation methodologies and access to experimental data, these results are not easily comparable. In this thesis, we address the topic of systematic benchmarks for renewable Energy supply forecasts. These usually include two stages, requiring a weather- and an energy forecast model. The latter can be selected amongst the classes of physical, statistical, and hybrid models. The selection of an appropriate model is one of the major tasks included in the forecasting process. We conducted an empirical analysis to assess the most popular forecasting methods. In contrast to the classical time- and resource intensive, mostly manual evaluation procedure, we developed a more efficient decision-support solution. With the inclusion of contextual information, our heuristic approach HMR is able to identify suitable examples in a case base and generates a recommendation out of the results from already existing solutions. The usage of time series representations reduces the dimensions of the original data thus allowing for an efficient search in large data sets. A context-aware evaluation methodology is introduced to assess a forecast’s quality based on its monetary return in the corresponding market environment. Results otherwise usually evaluated using statistical accuracy criteria become more interpretable by estimating real-world impacts. Finally, we introduced the ECAST framework as an open and easy to-use online platform that supports the benchmarking of energy time series forecasting methods. It aides inexperienced practitioners by supporting the execution of automated tasks, thus making complex benchmarks much more efficient and easy to handle. The integration of modules like the Ensembler, the Recommender, and the Evaluator provide additional value for forecasters. Reliable benchmarks can be conducted on this basis, while analytical functions for output explanation provide transparency for the user.:1 INTRODUCTION 11 2 ENERGY DATA MANAGEMENT CHALLENGES 17 2.1 Market Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.2 EDMS Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.1 Core Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.2 Typical Energy Data Management Processes . . . . . . . . . . . 23 2.2.3 System Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.3 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.3.1 Smart Metering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.3.2 Energy Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.3.3 Energy Saving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.3.4 Mobile Consumption Devices . . . . . . . . . . . . . . . . . . . . . 30 2.3.5 Smart Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3 ENERGY SUPPLY FORECASTING CONCEPTS 35 3.1 Energy Supply Forecasting Approaches . . . . . . . . . . . . . . . . . . . 36 3.1.1 Weather Forecast Models . . . . . . . . . . . . . . . . . . . . . . . . 36 3.1.2 Energy Forecast Models . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2 Energy Forecasting Process . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.2.1 Iterative Standard Process Model . . . . . . . . . . . . . . . . . . . 43 3.2.2 Context-Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3 Model Selection - A Benchmark Case Study . . . . . . . . . . . . . . . . 48 3.3.1 Use Case Description . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.3.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.3.3 Result Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4 RELEVANCE OF RENEWABLE ENERGY FORECASTING METHODS 55 4.1 Scientific Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.1.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.1.2 Quantitative Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.1.3 Qualitative Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4.2 Practical Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.2.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.2.2 Feedback from Software Providers . . . . . . . . . . . . . . . . . . 61 4.2.3 Feedback from Software Users . . . . . . . . . . . . . . . . . . . . . 62 4.3 Forecasting Competitions . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5 HEURISTIC MODEL RECOMMENDATION 67 5.1 Property-based Similarity Determination . . . . . . . . . . . . . . . . . . 67 5.1.1 Time Series Similarity . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.1.2 Reducing Dimensionality with Property Extraction . . . . . . . . . 69 5.1.3 Correlation Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5.2 Feature Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2.1 Feature Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2.2 Feature Pre-Selection . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5.2.3 Property-based Least Angle Regression . . . . . . . . . . . . . . . 85 5.3 HMR Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.3.1 Formalized Foundations . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.3.2 Procedure Description . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.3.3 Quality Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 5.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.4.1 Case Base Composition . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.4.2 Classifier Performance on univariate Models . . . . . . . . . . . . 95 5.4.3 HMR performance on multivariate models . . . . . . . . . . . . . 99 5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 6 VALUE-BASED RESULT EVALUATION METHODOLOGY 105 6.1 Accuracy evaluation in energy forecasting . . . . . . . . . . . . . . . . 106 6.2 Energy market models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.3 Value-based forecasting performance . . . . . . . . . . . . . . . . . . . 110 6.3.1 Forecast Benefit Determination . . . . . . . . . . . . . . . . . . . . 110 6.3.2 Multi-dimensional Ranking Scores . . . . . . . . . . . . . . . . . . . 113 6.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 6.4.1 Use Case Description . . . . . . . . . . . . . . . . . . . . . . . . . . 117 6.4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 6.4.3 Result Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 7 ECAST BENCHMARK FRAMEWORK 129 7.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 7.1.1 Objective Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 7.1.2 Fundamental Design Principles . . . . . . . . . . . . . . . . . . . . 131 7.2 System Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 7.2.1 Task Automation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 7.2.2 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 7.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 7.3.1 Step 1: Create a new Benchmark . . . . . . . . . . . . . . . . . . 137 7.3.2 Step 2: Build Ensembles . . . . . . . . . . . . . . . . . . . . . . . . . 139 7.3.3 Step 3: Evaluate the Output . . . . . . . . . . . . . . . . . . . . . . 141 7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 8 CONCLUSIONS 145 BIBLIOGRAPHY 149 LIST OF FIGURES 167 LIST OF TABLES 169 A LIST OF REVIEWED JOURNAL ARTICLES 171 B QUESTIONNAIRES 175 C STANDARD ERRORS FOR RANKING SCORES 179 D ERROR DISTRIBUTION FOR BENCHMARKED PREDICTORS 183

碩士
國立高雄應用科技大學
土木工程與防災科技研究所
103
Taiwan belongs to subtropical regions of the island-type climate, high heat and humidity of the special environment. Because of the high humidity will affect the temperature of the body to feel, so this study based on the climate and environment in Taiwan, collecting energy data to be used from National Taiwan University student dormitory, reference to the Energy Star model of US energy use benchmarks, deduced from the primary energy use efficiency estimate models of National Taiwan University student dormitory to establish the energy use benchmarks of Taiwan localization. 　　In this paper, based on the collection of questionnaire from National University dormitory energy use data. When the parameters are a linear correlation analysis, we found the relevant of Soure Energy is higher than Energy Use Intensity (EUI), therefore this study based on Soure Energy. To consider the humidity, present study use HI-CDD, enthalpy difference (ED) as a parameter of a cooling load linear correlation analysis; when the humidity is not considered, R2 is 0.732195. Humidity in HI-CDD as a parameter, R2 is 0.775933; humidity in the enthalpy difference as a parameter, R2 is 0.747091.From the three data comparison, after considering the humidity, the correlation is improved, proof humidity considerations have a positive impact on energy use analysis. Collecting 33 student dormitories energy use data, we can establish the estimate energy efficiency model of the dormitory in Taiwan; by the way, we can already assess the scores of dormitory energy use by this estimate model, dormitory energy use of the scores. Using HI-CDD, ED estimate model parameters respectively to establish a comparison and found that these two parameters taking into account the temperature and humidity,it will be a consistent rationality. 　　Finally, Using a south of dormitory as a Ecotect model to simulate, we found that direction change will affect the hot environment, but there is no direct impact on the amount of energy used, mainly due to the higher proportion of electricity in the dormitory equipment. It was found that in the summer, Air exchange rate will be converted from 1 simulated 0.5, it should be the high Air exchange rate, then consume more energy; contrarily, in the winter, there will bean energy-efficient phenomenon, it may be the outside air temperature is lower than it is in summer,and it can reduce the energy consumption of the heat exchange; for this reason, it reduce the burden on air-conditioning equipment.

碩士
國立臺北科技大學
冷凍與低溫科技研究所
97
The electronic, semiconductor, opto-electric & material technology have been highly developed in the past years in Taiwan, as the maturity in the mass production skill, The manufacturing industries of the LCD relative product in Taiwan have shared a very important role in the world and consume a lot of energy. The research was under the Energy Bureau of Taiwan government and ITRI, as a part of the annual energy-survey program to the electrical industries. For this time, we shall focus on the specific energy consumption of the product of polarizer and TN/STN LCD . We recommended, the benchmark value of the specific energy consumption of polarizer & TN/STN LCD product, shall be 1.62kWH/m2 & 5.0Mcal/m2 for polarizer, and 339.1 kWH/m2 (758.2Mcal/m2), 111.5kWH/m2 (249.4Mcal/m2), 36.6kWH/m2 (81.9Mcal/m2) for process type A (total process), type B (without CF process) & type C (without CF, Module, SMT process) of TN/STN LCD product.

The continuously increasing energy intensity internationally is recognised as one of the greatest dangers the human race is facing nowadays with regards to future climate change and its detrimental consequences. Improving the intensity of energy consumption is an important step towards decreasing greenhouse gas emissions originating from fossil fuel-based electricity generation and consumption. As a result of this, South Africa took the bold step in 2010 to commit itself to the Secretariat of the United Nations Framework Convention on Climate Change (UNFCCC) in taking all the necessary actions to decrease the country’s greenhouse gas emissions by 34% to below the “business-as-usual” scenario by 2020 (Republic of South Africa, 2010). In order to do so, the country has to substantially reduce its energy consumption. This should be done without affecting the economic output; however, major energy consumers might prefer to decrease their output in order to comply with the rules focusing on the reduction of energy use. In South Africa, harmful environmental effects are created mainly from the electricity consumption’s unprecedented rise. The bulk of the country’s greenhouse gas emissions (more than 60%) originate from the electricity generation sector which is heavily dependent on coal-fired power stations. The purpose of this study is to promote a benchmark-and-trade system to improve electricity efficiency in South Africa with the ultimate objective to improve the country’s greenhouse gas emissions. The uniqueness of this study is two-fold. On the one side, South African policy-makers have rarely discussed or proposed the implementation of a cap-and- trade system. On the other side, the same mechanism has never been proposed regarding electricity efficiency. In order to do so, it is first required to acquire an in-depth knowledge of the electricity consumption and efficiency of the South African economy in its entirety and on a sectoral level. The key findings of the empirical analysis are as follows: A decreasing effect of electricity prices to electricity consumption existed during the period 1980 to 2005, contrary to the increasing effect of total output to electricity consumption. Also, the results indicated that the higher the prices, the higher the price sensitivity of consumers to changes in prices (price elasticity) and vice versa. The relationship between electricity consumption and electricity prices differ among various sectors. The findings of the exercise point towards ambiguous results and even lack of behavioural response towards price changes in all but the industrial sector, where electricity consumption increased with price decreases. On the other side, economic output affected the electricity consumption of two sectors (industrial and commercial) presenting high and statistically significant coefficients. Based on a decomposition exercise, the change in production was the main factor that increased electricity consumption, while efficiency improvement was a driver in the decrease of electricity consumption. In the sectoral analysis, increases in production were part of the rising electricity usage for all the sectors with ‘iron and steel’, ‘transport’ and ‘non-ferrous metals’ being the main contributors to the effect. On the decreasing side of consumption, only five out of fourteen sectors were influenced by efficiency improvements. The country’s electricity intensity more than doubled from 1990 to 2007 and the country’s weighted growth of intensity was higher than the majority of the OECD countries by a considerable margin. Also, nine of the thirteen South African sectors were substantially more intensive than their OECD counterparts. Although the picture presented is rather dismal, there is scope for improvement. This study proposes a sectoral benchmark-and-trade system. This system aspires to steadily improve the participants’ efficiency performance by awarding the successful participants with monetary incentives through trading with the less successful ones. The benchmark is chosen to be subject to the average of OECD members for each sector. Depending on the sectors’ performance compared with the standard chosen, they will be awarded credits or allowances to sell if they do better than the benchmark. If they are worse-off, they will have to buy credits in the market created. The price per credit will be determined by the interaction of demand and supply in the market. The findings of a comparison with a carbon tax system show that the proposed system benefits the majority of the sectors and gives them better incentives to change their behaviour and production methods to more efficient ones. The system also fulfils the desired characteristics of a benchmark-and-trade system: certainty of environmental performance; business certainty; flexibility; administrative ease and transparency.
Thesis (PhD)--University of Pretoria, 2011.
Economics
unrestricted

碩士
國立臺北科技大學
能源與冷凍空調工程系碩士班
95
The study in this thesis is to establish the figure of specific energy consumption. Methods are depended on the present industries’ structures, sorting characteristics of products with different or similar specifications, and in the similar manufacturing processes. Through the examined data from the ITRI’s reports (Industry Technology Research Institute of Taiwan) and visiting manufacturers and information from the relative economic researches, it then inducts the characteristics of manufacturing processes and products types. Thereafter, datasheets are designed and provided to each industry as to return their figures on different products. Moreover, the utilization rate of capacity is obtained by the designed production quantities in the beginning stage of building plant and its actual quantities in real working situation. Later, all the various energies are transformed by means of caloric values to be the uniform energy consumptions as standardizations. Next, summing all the energy consumptions and corresponding to the year quantities so as to gain the specific energy consumption. After dealing with the figures, the specific energy consumption for each sampling manufacturer is obtained. The main four target products in this project are epitaxy Si wafers, LEDs, and lead-acid battery for auto and motorcycles. Those above products are defined by the uni-specification in manufacturing area that is to say all the specific energy consumptions including the manufacturing tools’ and the utilities’ are summed and corresponded to the utilization rate of month capacity for the month specific energy consumption. Furthermore, powers regression equation of Microsoft Excell is utilized to set up curves charts for each sampling manufacturer, and is used as the standardization of the specific energy consumption when the utilization rate of capacity is at 100%. In addition, selecting secondary values from those sampling manufacturers to be of the recommended notice values as benchmarks, meantime, taking place seminar with each sampling manufacturer’s representatives, and having discussions with scholars, the figures are surely acknowledged at length, and listed in the following table. The Recommended Notice Value Specific Energy Consumption in this Project Products Indicating manufacturers specification Manufacturing processes The recommended notice value of the specific energy consumption kwh/k Mcal/k kwh/in2 Mcal/in2 kwh/set Mcal/set LEDs LED-I LED-J Regular brightness Chips 0.57 1.27 NA NA NA NA LEDs LED-E Higher brightness Chips 1.86 4.15 NA NA NA NA LEDs LED-H Higher brightness/2 inches Epitaxy NA NA 10.43 23.32 NA NA LEDs LED-E Higher brightness Epitaxy combining chips 3.09 6.9 NA NA NA NA Epitaxy Si wafers EPI-A 4~8 inches Si epitaxy NA NA 1.03 2.3 NA NA Epitaxy Si wafers EPI-C 8 inches Si epitaxy NA NA 0.34 0.76 NA NA Lead-acid batteries C-BT-B Auto Including assembly NA NA NA NA 8.73 19.52 Lead-acid batteries B-BT-A Motorcycles Including assembly NA NA NA NA 5.34 11.94

Loyaltyprogramshavetobeadjustedforthepurchasingbehaviourofthetargetclient.ThisresearchprojectexploreshowGalp’scurrentB2Bprogramadaptstothistypeofclient,usingquantitativeandqualitativestudiestocomparetheperceiveddiscountwiththecompetition’sprograms,tofindthepainpointsfortheconsumerandtounderstandhowtheprogramimpactsconsumption.Inthefinalpartofthestudy,variousloyaltyprogramsofsuccessfulinternationalfuelcompaniesarebenchmarkedinordertohaveabetterunderstandingofthebestpracticesinthisfield.