Using ICT Energy consumption for monitoring ICT architecture

Energy efficient policies are being applied to network protocols, devices and classical network management systems. Researchers have already studied in depth each of those fields, including for instance a long monitoring processes of various number of individual ICT equipment from where power models are constructed. With the development of smart meters and emerging protocols such as SNMP and NETCONF, currently there is an open field to couple the power models, translated to the expected behavior, with the realtime energy measurements. The goal is to derive a comparison on the power data between both of the processes in the direction of detection for possible deviations on the expected results. The logical assumption is that a fault in the usage of a particular device will not only increase its own energy usage, but also may cause additional consumption on the other devices part of the network. A platform is developed to monitor and analyze the retrieved power data of a simulated enterprise ICT infrastructure. Moreover, smart algorithms are developed which are aware of the different states that are occurring on each device during their typical use phase, as well as to detect and isolate possible anomalies. The produced results are obtained and validated with the use of Cisco switches and routers, Dell Precision stations and Raritan PDU as part of the monitored infrastructure.

The study of the impact of demand controlled ventilation in energy consumption of offices in Portuguese commercial buildings

Indoor Air 2016 - The 14th International Conference of Indoor Air Quality and Climate

Selection of optimal operating conditions based on minimum energy consumption for an acrylonitrile recovery unit

The selection of the optimal operating conditions for an industrial acrylonitrile recovery unit was conducted by the systematic application of the response surface methodology, based on the minimum energy consumption and products specifications as process constraints. Unit models and plant simulation were validated against operating data and information. A sensitivity analysis was carried out in order to identify the set of parameters that strongly affect the trajectories of the system while keeping products specifications. The results suggest that energy savings of up to 10% are possible by systematically adjusting operating conditions.

Long-term relationship between energy consumption and GDP in Latin America: an empirical assessment using panel data

The main objetive of this research is to evaluate the long term relationship between energy consumption and GDP for some Latin American countries in the period 1980-2009 -- The estimation has been done through the non-stationary panel approach, using the production function in order to control other sources of GDP variation, such as capital and labor -- In addition to this, a panel unit root tests are used in order to identify the non-stationarity of these variables, followed by the application of panel cointegration test proposed by Pedroni (2004) to avoid a spurious regression (Entorf, 1997; Kao, 1999)

Predictive models of buildings energy consumption

Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Energy consumption prediction based on time-series models for CPU-intensive activities in the cloud

Due to the increasing energy consumption in cloud data centers, energy saving has become a vital objective in designing the underlying cloud infrastructures. A precise energy consumption model is the foundation of many energy-saving strategies. This paper focuses on exploring the energy consumption of virtual machines running various CPU-intensive activities in the cloud server using two types of models: traditional time-series models, such as ARMA and ES, and time-series segmentation models, such as sliding windows model and bottom-up model. We have built a cloud environment using OpenStack, and conducted extensive experiments to analyze and compare the prediction accuracy of these strategies. The results indicate that the performance of ES model is better than the ARMA model in predicting the energy consumption of known activities. When predicting the energy consumption of unknown activities, sliding windows segmentation model and bottom-up segmentation model can all have satisfactory performance but the former is slightly better than the later.

Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

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.

Energy consumption and energy efficiency in olive oil mills: case studies in Portugal and Spain in the frame of TESLA project

TESLA project (Transfering Energy Save Laid on Agroindustry) financed by the European Commission, had the main goals of evaluating the energy consumption and to identify the best available practices to improve energy efficiency in key agro-food sectors, such as the olive oil mills. A general analysis of energy consumptions allowed identifying the partition between electrical and thermal energy (approximately 50%) and the production processes responsible for the higher energy consumptions, as being the in the mill and paste preparation and the phases separation. Some measures for reducing energy waste and for improving energy efficiency were identified and the impact was evaluated by using the TESLA tool developed by Circe and available at the TESLA website.

Practical wireless sensor networks power consumption metrics for building energy management applications

The power consumption of wireless sensor networks (WSN) module is an important practical concern in building energy management (BEM) system deployments. A set of metrics are created to assess the power profiles of WSN in real world condition. The aim of this work is to understand and eventually eliminate the uncertainties in WSN power consumption during long term deployments and the compatibility with existing and emerging energy harvesting technologies. This paper investigates the key metrics in data processing, wireless data transmission, data sensing and duty cycle parameter to understand the system power profile from a practical deployment prospective. Based on the proposed analysis, the impacts of individual metric on power consumption in a typical BEM application are presented and the subsequent low power solutions are investigated.

Energy overview of Botswana: generation and consumption

Botswana has a basic need to explore its energy concept, this being its energy sources, generation and percentage of the population with access to electricity. At present, Botswana generates electricity from coal, which supplies about 29% (on average) of the country’s demand. The other 71% is imported mainly from South Africa (Eskom). Consequently, the dependence of Botswana on imports posses threats to the security of its energy supply. As a result, there is the need to understand the bases for a possible generation expansion that would substantiate existing documentation. In view of this need, this study investigates the existing energy sources as well as energy consumption and production levels in Botswana. The study would be further developed by making projections of the energy demand up until the year 2020. The key techniques that were used include; literature review, questionnaire survey and an empirical study. The results presented indicated that, current dependable operation capacity (i.e. 100MW) should be increased to 2,595 MW or more assuming 85% plant efficiency. This would then be able to meet the growing demand for energy use. In addition, the installed capacity would be able to support commercial and mining activities for the growth of the economy.

Energy supply, consumption and access dynamics in Botswana

The growing dependence on electricity for economic growth in all countries prompts the need to manage current resources for future sustainability. In today’s world, greater emphasis is placed on energy conservation for energy security and for the development of every economy. However, for some countries understanding the basic drivers to such achievements is farfetched. The research presented in this paper investigates the electricity generation and access potential for Botswana. In addition detailed documentation and 13 years energy consumption and generation trends are investigated. Using questionnaires and empirical studies the energy demand for the entire nation was estimated. From the research it was established that current energy generation trends account for 38- 39% of the country’s population with access to electricity. Considering the percentage rate of sector energy demand, the proposed total installed capacity of 1332 MW, would not meet the country's energy demand at 100% access. The likely consequence of the lack of adequate supply would cumulate to significant increase of imports and/or load shedding to meet demand.

Indicators to the consumption of electric energy and agriculture cattle farming production for the elaboration of clusters with cities of the state of São Paulo, Brazil

The issue in this matter is that rules for use of electricity in rural areas are limited to the provision of inputs. Adopting guidelines to consider managed sub regions can generate poor results. The focus of this study was to present parameters for indicators of electric energy and agricultural production to allow the formation of city groups in Sao Paulo State, Brazil, with similar electric energy consumption and rural agricultural production. The methodology was the development of indicators that characterize the electric energy consumption/agricultural production and the preparation of groups using indicators with ward of statistical method of groups. The main conclusions were the formation of six homogeneous groups with similar characteristics regarding agricultural production/consumption of electricity. The application of these groups in cities with similar characteristics would produce more satisfactory results than the division of administrative Rural Development Offices (RDO).

Energy/power consumption model for an embedded processor board

This dissertation, whose research has been conducted at the Group of Electronic and Microelectronic Design (GDEM) within the framework of the project Power Consumption Control in Multimedia Terminals (PCCMUTE), focuses on the development of an energy estimation model for the battery-powered embedded processor board. The main objectives and contributions of the work are summarized as follows: A model is proposed to obtain the accurate energy estimation results based on the linear correlation between the performance monitoring counters (PMCs) and energy consumption. the uniqueness of the appropriate PMCs for each different system, the modeling methodology is improved to obtain stable accuracies with slight variations among multiple scenarios and to be repeatable in other systems. It includes two steps: the former, the PMC-filter, to identify the most proper set among the available PMCs of a system and the latter, the k-fold cross validation method, to avoid the bias during the model training stage. The methodology is implemented on a commercial embedded board running the 2.6.34 Linux kernel and the PAPI, a cross-platform interface to configure and access PMCs. The results show that the methodology is able to keep a good stability in different scenarios and provide robust estimation results with the average relative error being less than 5%. Este trabajo fin de máster, cuya investigación se ha desarrollado en el Grupo de Diseño Electrónico y Microelectrónico (GDEM) en el marco del proyecto PccMuTe, se centra en el desarrollo de un modelo de estimación de energía para un sistema empotrado alimentado por batería. Los objetivos principales y las contribuciones de esta tesis se resumen como sigue: Se propone un modelo para obtener estimaciones precisas del consumo de energía de un sistema empotrado. El modelo se basa en la correlación lineal entre los valores de los contadores de prestaciones y el consumo de energía. Considerando la particularidad de los contadores de prestaciones en cada sistema, la metodología de modelado se ha mejorado para obtener precisiones estables, con ligeras variaciones entre escenarios múltiples y para replicar los resultados en diferentes sistemas. La metodología incluye dos etapas: la primera, filtrado-PMC, que consiste en identificar el conjunto más apropiado de contadores de prestaciones de entre los disponibles en un sistema y la segunda, el método de validación cruzada de K iteraciones, cuyo fin es evitar los sesgos durante la fase de entrenamiento. La metodología se implementa en un sistema empotrado que ejecuta el kernel 2.6.34 de Linux y PAPI, un interfaz multiplataforma para configurar y acceder a los contadores. Los resultados muestran que esta metodología consigue una buena estabilidad en diferentes escenarios y proporciona unos resultados robustos de estimación con un error medio relativo inferior al 5%.

Improvements in sustainable energy and water practice in the food processing industry : an in depth analysis of the manufacture of Ghee at the Butter Producers' Cooperative Federation Limited, Brisbane

This thesis is a documented energy audit and long term study of energy and water reduction in a ghee factory. Global production of ghee exceeds 4 million tonnes annually. The factory in this study refines dairy products by non-traditional centrifugal separation and produces 99.9% pure, canned, crystallised Anhydrous Milk Fat (Ghee). Ghee is traditionally made by batch processing methods. The traditional method is less efficient, than centrifugal separation. An in depth systematic investigation was conducted of each item of major equipment including; ammonia refrigeration, a steam boiler, canning equipment, pumps, heat exchangers and compressed air were all fine-tuned. Continuous monitoring of electrical usage showed that not every initiative worked, others had pay back periods of less than a year. In 1994-95 energy consumption was 6,582GJ and in 2003-04 it was 5,552GJ down 16% for a similar output. A significant reduction in water usage was achieved by reducing the airflow in the refrigeration evaporative condensers to match the refrigeration load. Water usage has fallen 68% from18ML in 1994-95 to 5.78ML in 2003-04. The methods reported in this thesis could be applied to other industries, which have similar equipment, and other ghee manufacturers.