Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Optimization of energy consumption in wastewater pumping

Pumppauksessa arvioidaan olevan niin teknisesti kuin taloudellisestikin huomattavia mahdollisuuksia säästää energiaa. Maailmanlaajuisesti pumppaus kuluttaa lähes 22 % sähkö-moottorien energiantarpeesta. Tietyillä teollisuudenaloilla jopa yli 50 % moottorien käyttämästä sähköenergiasta voi kulua pumppaukseen. Jäteveden pumppauksessa pumppujen toiminta perustuu tyypillisesti on-off käyntiin, jolloin pumpun ollessa päällä se käy täydellä teholla. Monissa tapauksissa pumput ovat myös ylimitoitettuja. Yhdessä nämä seikat johtavat kasvaneeseen energian kulutukseen. Työn teoriaosassa esitellään perusteet jätevesihuollosta ja jäteveden käsittelystä sekä pumppaussysteemin pääkomponentit: pumppu, putkisto, moottori ja taajuusmuuttaja. Työn empiirisessä osassa esitellään työn aikana kehitetty laskuri, jonka avulla voidaan arvioida energiansäästöpotentiaalia jäteveden pumppaussysteemeissä. Laskurilla on mandollista laskea energiansäästöpotentiaali käytettäessä pumpun tuoton ohjaustapana pyörimisnopeuden säätöä taajuusmuuttajalla on-off säädön sijasta. Laskuri ilmoittaa optimaalisimmanpumpun pyörimisnopeuden sekä ominaisenergiankulutuksen. Perustuen laskuriin, kolme kunnallista jätevedenpumppaamoa tutkittiin. Myös laboratorio-testitsuoritettiin laskurin simuloimiseksi sekä energiansäästöpotentiaalin arvioimiseksi. Tutkimukset osoittavat, että jätevedenpumppauksessa on huomattavia mandollisuuksia säästää energiaa pumpun pyörimisnopeutta pienentämällä. Geodeettisen nostokorkeuden ollessa pieni, voidaan energiaa säästää jopa 50 % ja pitkällä aikavälillä säästö voi olla merkittävä. Tulokset vahvistavat myös tarpeen jätevedenpumppaussysteemien toiminnan optimoimiseksi.

Climate change and global responsibility - the role of energy consumption, GDP and CO2 emissions

Climate change is one of the biggest challenges faced by this generation. Despite being the single most important environmental challenge facing the planet and despite over two decades of international climate negotiations, global greenhouse gas (GHG) emissions continue to rise. By the middle of this century, GHGs must be reduced by as much as 40-70% if dangerous climate change is to be avoided. In the Kyoto Protocol no quantitative emission limitation and reduction commitments were placed on the developing countries. For the planning of the future commitments period and possible participation of developing countries, information of the functioning of the energy systems, CO2 emissions development in different sectors, energy use and technological development in developing countries is essential. In addition to the per capita emissions, the efficiency of the energy system in relation to GHG emissions is crucial for the decision of future long-term burden sharing between countries. Country’s future development of CO2 emissions can be defined by the estimated CO2 intensity of the future and the estimated GDP growth. The changes in CO2 intensity depend on several factors, but generally developed countries’ intensity has been increasing in the industrialization phase and decreasing when their economy shifts more towards the system dominated by the service sector. The level of the CO2 intensity depends by a large extent on the production structure and the energy sources that are used. Currently one of the most urgent issues regarding global climate change is to decide the future of the Kyoto Protocol. Negotiations on this topic have already been initiated, with the aim of being finalised by the 2015. This thesis provides insights into the various approaches that can be used to characterise the concept of comparable efforts for developing countries in a future international climate agreement. The thesis examines the post-Kyoto burden sharing questions for developing countries using the contraction and convergence model, which is one approach that has been proposed to allocate commitments regarding future GHG emissions mitigation. This new approach is a practical tool for the evaluation of the Kyoto climate policy process and global climate change negotiations from the perspective of the developing countries.

A semiotic framework for information representation of energy consumption in office buildings

Taking a perspective from a whole building lifecycle, occupier's actions could account for about 50% of energy. However occupants' activities influence building energy performance is still a blind area. Building energy performance is thought to be the result of a combination of building fabrics, building services and occupants' activities, along with their interactions. In this sense, energy consumption in built environment is regarded as a socio-technical system. In order to understand how such a system works, a range of physical, technical and social information is involved that needs to be integrated and aligned. This paper has proposed a semiotic framework to add value for Building Information Modelling, incorporating energy-related occupancy factors in a context of office buildings. Further, building information has been addressed semantically to describe a building space from the facility management perspective. Finally, the framework guides to set up building information representation system, which can help facility managers to manage buildings efficiently by improving their understanding on how office buildings are operated and used.

Safe upper-bounds inference of energy consumption for java bytecode applications

Abstract is not available.

Economics and forecast of energy consumption in NGN networks: the case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”.

On the economics of energy consumption in 4G networks: the case of Spain

Reducing energy consumption is one of the main challenges in most countries. For example, European Member States agreed to reduce greenhouse gas (GHG) emissions by 20% in 2020 compared to 1990 levels (EC 2008). Considering each sector separately, ICTs account nowadays for 2% of total carbon emissions. This percentage will increase as the demand of communication services and applications steps up. At the same time, the expected evolution of ICT-based developments - smart buildings, smart grids and smart transportation systems among others - could result in the creation of energy-saving opportunities leading to global emission reductions (Labouze et al. 2008), although the amount of these savings is under debate (Falch 2010). The main development required in telecommunication networks ?one of the three major blocks of energy consumption in ICTs together with data centers and consumer equipment (Sutherland 2009) ? is the evolution of existing infrastructures into ultra-broadband networks, the so-called Next Generation Networks (NGN). Fourth generation (4G) mobile communications are the technology of choice to complete -or supplement- the ubiquitous deployment of NGN. The risk and opportunities involved in NGN roll-out are currently in the forefront of the economic and policy debate. However, the issue of which is the role of energy consumption in 4G networks seems absent, despite the fact that the economic impact of energy consumption arises as a key element in the cost analysis of this type of networks. Precisely, the aim of this research is to provide deeper insight on the energy consumption involved in the usage of a 4G network, its relationship with network main design features, and the general economic impact this would have in the capital and operational expenditures related with network deployment and usage.

Improved static analysis and verification of energy consumption and other resources via abstract interpretation

Resource analysis aims at inferring the cost of executing programs for any possible input, in terms of a given resource, such as the traditional execution steps, time ormemory, and, more recently energy consumption or user defined resources (e.g., number of bits sent over a socket, number of database accesses, number of calls to particular procedures, etc.). This is performed statically, i.e., without actually running the programs. Resource usage information is useful for a variety of optimization and verification applications, as well as for guiding software design. For example, programmers can use such information to choose different algorithmic solutions to a problem; program transformation systems can use cost information to choose between alternative transformations; parallelizing compilers can use cost estimates for granularity control, which tries to balance the overheads of task creation and manipulation against the benefits of parallelization. In this thesis we have significatively improved an existing prototype implementation for resource usage analysis based on abstract interpretation, addressing a number of relevant challenges and overcoming many limitations it presented. The goal of that prototype was to show the viability of casting the resource analysis as an abstract domain, and howit could overcome important limitations of the state-of-the-art resource usage analysis tools. For this purpose, it was implemented as an abstract domain in the abstract interpretation framework of the CiaoPP system, PLAI.We have improved both the design and implementation of the prototype, for eventually allowing an evolution of the tool to the industrial application level. The abstract operations of such tool heavily depend on the setting up and finding closed-form solutions of recurrence relations representing the resource usage behavior of program components and the whole program as well. While there exist many tools, such as Computer Algebra Systems (CAS) and libraries able to find closed-form solutions for some types of recurrences, none of them alone is able to handle all the types of recurrences arising during program analysis. In addition, there are some types of recurrences that cannot be solved by any existing tool. This clearly constitutes a bottleneck for this kind of resource usage analysis. Thus, one of the major challenges we have addressed in this thesis is the design and development of a novel modular framework for solving recurrence relations, able to combine and take advantage of the results of existing solvers. Additionally, we have developed and integrated into our novel solver a technique for finding upper-bound closed-form solutions of a special class of recurrence relations that arise during the analysis of programs with accumulating parameters. Finally, we have integrated the improved resource analysis into the CiaoPP general framework for resource usage verification, and specialized the framework for verifying energy consumption specifications of embedded imperative programs in a real application, showing the usefulness and practicality of the resulting tool.---ABSTRACT---El Análisis de recursos tiene como objetivo inferir el coste de la ejecución de programas para cualquier entrada posible, en términos de algún recurso determinado, como pasos de ejecución, tiempo o memoria, y, más recientemente, el consumo de energía o recursos definidos por el usuario (por ejemplo, número de bits enviados a través de un socket, el número de accesos a una base de datos, cantidad de llamadas a determinados procedimientos, etc.). Ello se realiza estáticamente, es decir, sin necesidad de ejecutar los programas. La información sobre el uso de recursos resulta muy útil para una gran variedad de aplicaciones de optimización y verificación de programas, así como para asistir en el diseño de los mismos. Por ejemplo, los programadores pueden utilizar dicha información para elegir diferentes soluciones algorítmicas a un problema; los sistemas de transformación de programas pueden utilizar la información de coste para elegir entre transformaciones alternativas; los compiladores paralelizantes pueden utilizar las estimaciones de coste para realizar control de granularidad, el cual trata de equilibrar el coste debido a la creación y gestión de tareas, con los beneficios de la paralelización. En esta tesis hemos mejorado de manera significativa la implementación de un prototipo existente para el análisis del uso de recursos basado en interpretación abstracta, abordando diversos desafíos relevantes y superando numerosas limitaciones que éste presentaba. El objetivo de dicho prototipo era mostrar la viabilidad de definir el análisis de recursos como un dominio abstracto, y cómo se podían superar las limitaciones de otras herramientas similares que constituyen el estado del arte. Para ello, se implementó como un dominio abstracto en el marco de interpretación abstracta presente en el sistema CiaoPP, PLAI. Hemos mejorado tanto el diseño como la implementación del mencionado prototipo para posibilitar su evolución hacia una herramienta utilizable en el ámbito industrial. Las operaciones abstractas de dicha herramienta dependen en gran medida de la generación, y posterior búsqueda de soluciones en forma cerrada, de relaciones recurrentes, las cuales modelizan el comportamiento, respecto al consumo de recursos, de los componentes del programa y del programa completo. Si bien existen actualmente muchas herramientas capaces de encontrar soluciones en forma cerrada para ciertos tipos de recurrencias, tales como Sistemas de Computación Algebraicos (CAS) y librerías de programación, ninguna de dichas herramientas es capaz de tratar, por sí sola, todos los tipos de recurrencias que surgen durante el análisis de recursos. Existen incluso recurrencias que no las puede resolver ninguna herramienta actual. Esto constituye claramente un cuello de botella para este tipo de análisis del uso de recursos. Por lo tanto, uno de los principales desafíos que hemos abordado en esta tesis es el diseño y desarrollo de un novedoso marco modular para la resolución de relaciones recurrentes, combinando y aprovechando los resultados de resolutores existentes. Además de ello, hemos desarrollado e integrado en nuestro nuevo resolutor una técnica para la obtención de cotas superiores en forma cerrada de una clase característica de relaciones recurrentes que surgen durante el análisis de programas lógicos con parámetros de acumulación. Finalmente, hemos integrado el nuevo análisis de recursos con el marco general para verificación de recursos de CiaoPP, y hemos instanciado dicho marco para la verificación de especificaciones sobre el consumo de energía de programas imperativas embarcados, mostrando la viabilidad y utilidad de la herramienta resultante en una aplicación real.

Comparison of energy consumption between West Germany and the United States

"Contract no. 14-01-001-1885."

ASSESSMENT OF ENERGY CONSUMPTION IN GREENHOUSE PRODUCTION IN THE WEST REGION OF PORTUGAL

Greenhouse production is a very important activity in the West region of Portugal, with an area of approximately 800 ha where the regular production consists in two crops per year, one in winter-spring and the other in summer-autumn. Many growers are now prepared to better exploit market opportunities, since they know that the big export window opportunity is from June to September, when the production is difficult in other regions of south due to high temperatures. Grower’s use new and more productive varieties, either in soil or hydroponic systems, mostly in unheated greenhouses, naturally ventilated, and equipped with modern fertigation systems. Greenhouse production causes some environmental impacts due to the high use of inputs. Several improvements in technologies and crop practices may contribute to increase the use efficiency of resources, decreasing the negative environmental impacts. Greenhouse vegetable production in Northern EU countries is based on the supply of heating and differs significantly from the production system in the Southern EU countries. In the Northern countries, direct energy inputs, mostly for heating, are predominant while in the South the indirect energy input is also important, mainly associated with fertilizers, plastic cover materials and other auxiliary materials. The main objective of this work was to characterise the greenhouse production systems in the West region of Portugal, in order to evaluate the energetic consumptions (direct and indirect), the GHH emissions, the production costs and the farmer’s income. With this work the mostly important inputs were identified, allowing proposing alternative measures to improve efficiency and sustainability. All the data was obtained by surveys performed directly with growers, previously selected to be representative of the crop practices and greenhouse type of the region. However, more research should be performed in order to develop and to test technologies capable to improve resources use efficiency in greenhouse production.

Modelling Energy Consumption of a Switch using Fuzzy-Rule Classifier

The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

A data framework for measuring the energy consumption of the non-domestic building stock

The transition to a low-carbon economy urgently demands better information on the drivers of energy consumption. UK government policy has prioritized energy efficiency in the built stock as a means of carbon reduction, but the sector is historically information poor, particularly the non-domestic building stock. This paper presents the results of a pilot study that investigated whether and how property and energy consumption data might be combined for non-domestic energy analysis. These data were combined in a ‘Non-Domestic Energy Efficiency Database’ to describe the location and physical attributes of each property and its energy consumption. The aim was to support the generation of a range of energy-efficiency statistics for the industrial, commercial and institutional sectors of the non-domestic building stock, and to provide robust evidence for national energy-efficiency and carbon-reduction policy development and monitoring. The work has brought together non-domestic energy data, property data and mapping in a ‘data framework’ for the first time. The results show what is possible when these data are integrated and the associated difficulties. A data framework offers the potential to inform energy-efficiency policy formation and to support its monitoring at a level of detail not previously possible.

Energy Consumption Forecast in 4G Networks: The Case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”. • Next Generation Networks (NGN)  One of the most relevant upcoming ICT development • The role of energy consumption seems mostly absent from the main analysis and the debate on NGN deployment.

Energy consumption of passenger land transport modes

This paper shows how the methodologies used in current practice might lead to an underestimation of energy consumption by different passenger transport modes, and also offers recommendations for improvements to these methodologies. The first recommendation is related to energy consumption rates. The studies reviewed use traditional energy consumption rates based on transportation demand, such as kilowatts-hour per vehicle-kilometre or kilowatts-hour per passenger-kilometre, and include other rates based on transportation supply which might prove useful. Second, energy consumption rates are dependent on factors, and the introduction of homogeneous units which are independent of these factors therefore offers a significant improvement when comparing transport modes. Third, the use of a vehicle energy consumption equation will improve the quality of the assessments. Fourth, we propose that the coefficients which define the energy consumption equation should be broken down to determine market niches and sources for improvements in energy consumption in the vehicle categories.