Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Improving the ultra-low-power performance of IEEE 802.15.6 by adaptive synchronisation

In ultra-low data rate wireless sensor networks (WSNs) waking up just to listen to a beacon every superframe can be a major waste of energy. This study introduces MedMAC, a medium access protocol for ultra-low data rate WSNs that achieves significant energy efficiency through a novel synchronisation mechanism. The new draft IEEE 802.15.6 standard for body area networks includes a sub-class of applications such as medical implantable devices and long-term micro miniature sensors with ultra-low power requirements. It will be desirable for these devices to have 10 years or more of operation between battery changes, or to have average current requirements matched to energy harvesting technology. Simulation results are presented to show that the MedMAC allows nodes to maintain synchronisation to the network while sleeping through many beacons with a significant increase in energy efficiency during periods of particularly low data transfer. Results from a comparative analysis of MedMAC and IEEE 802.15.6 MAC show that MedMAC has superior efficiency with energy savings of between 25 and 87 for the presented scenarios. © 2011 The Institution of Engineering and Technology.

Integrating wind power using intelligent electric water heating

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

Retrofit versus new-build house using life-cycle assessment

This paper reports the findings of research on the environmental performance of two case-study houses, a retrofit and new build. The retrofit was completed to a Passivhaus standard while the new build was completed to current Irish building regulations. Environmental performance of the retrofit and new build was measured using life-cycle assessments, examining the assembly, operational and end-of-life stage over life spans of 50 and 80 years. Using primary information, life-cycle assessment software and life-cycle assessment databases the environmental impacts of each stage were modelled. The operational stage of both case studies was found to be the source of the most significant environmental damage, followed by the assembly and the end-of-life stage respectively. The relative importance of the assembly and end-of-life stage decreased as the life span increased. It was found that the retrofit house studied outperformed the new build in the assembly and operational stage, whereas the new build performed better in the end-of-life stage; however, this is highly sensitive, depending on the standards to which both are completed. Operational energy savings pre- and post-retrofit were significant, indicating the future potential for adoption of high-quality retrofitting practices.

RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Gas Hydrate Inhibition: A Review of the Role of Ionic Liquids

Ionic liquids (ILs) are popular designer green chemicals with great potential for use in diverse energy-related applications. Apart from the well-known low vapor pressure, the physical properties of ILs, such as hydrogen-bond-forming capacity, physical state, shape, and size, can be fine-tuned for specific applications. Natural gas hydrates are easily formed in gas pipelines and pose potential problems to the oil and natural gas industry, particularly during deep-sea exploration and production. This review summarizes the recent advances in IL research as dual-function gas hydrate inhibitors. Almost all of the available thermodynamic and kinetic inhibition data in the presence of ILs have been systematically reviewed to evaluate the efficiency of ILs in gas hydrate inhibition, compared to other conventional thermodynamic and kinetic gas hydrate inhibitors. The principles of natural gas hydrate formation, types of gas hydrates and their inhibitors, apparatuses and methods used, reported experimental data, and theoretical methods are thoroughly and critically discussed. The studies in this field will facilitate the design of advanced ILs for energy savings through the development of efficient low-dosage gas hydrate inhibitors.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

Algoritmos inteligentes de baixa complexidade

A domótica é uma área com grande interesse e margem de exploração, que pretende alcançar a gestão automática e autónoma de recursos habitacionais, proporcionando um maior conforto aos utilizadores. Para além disso, cada vez mais se procuram incluir benefícios económicos e ambientais neste conceito, por forma a garantir um futuro sustentável. O aquecimento de água (por meios elétricos) é um dos fatores que mais contribui para o consumo de energia total de uma residência. Neste enquadramento surge o tema “algoritmos inteligentes de baixa complexidade”, com origem numa parceria entre o Departamento de Eletrónica, Telecomunicações e Informática (DETI) da Universidade de Aveiro e a Bosch Termotecnologia SA, que visa o desenvolvimento de algoritmos ditos “inteligentes”, isto é, com alguma capacidade de aprendizagem e funcionamento autónomo. Os algoritmos devem ser adaptados a unidades de processamento de 8 bits para equipar pequenos aparelhos domésticos, mais propriamente tanques de aquecimento elétrico de água. Uma porção do desafio está, por isso, relacionada com as restrições computacionais de microcontroladores de 8 bits. No caso específico deste trabalho, foi determinada a existência de sensores de temperatura da água no tanque como a única fonte de informação externa aos algoritmos, juntamente com parâmetros pré-definidos pelo utilizador que estabelecem os limiares de temperatura máxima e mínima da água. Partindo deste princípio, os algoritmos desenvolvidos baseiam-se no perfil de consumo de água quente, observado ao longo de cada semana, para tentar prever futuras tiragens de água e, consequentemente, agir de forma adequada, adiantando ou adiando o aquecimento da água do tanque. O objetivo é alcançar uma gestão vantajosa entre a economia de energia e o conforto do utilizador (água quente), isto sem que exista necessidade de intervenção direta por parte do utilizador final. A solução prevista inclui também o desenvolvimento de um simulador que permite observar, avaliar e comparar o desempenho dos algoritmos desenvolvidos.

Estudo comparativo de sistemas em aquecimento

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Controlo preditivo distribuído em edifícios para conforto térmico e alocação de cargas

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Reabilitação energética de um edifício de índole cultural: Centro Cultural de Belém

Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Nano-CF: a Coordination Framework for macro-programming in wireless sensor networks

Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.

Inter-application redundancy elimination in sensor networks with compiler-assisted scheduling

Most current-generation Wireless Sensor Network (WSN) nodes are equipped with multiple sensors of various types, and therefore support for multi-tasking and multiple concurrent applications is becoming increasingly common. This trend has been fostering the design of WSNs allowing several concurrent users to deploy applications with dissimilar requirements. In this paper, we extend the advantages of a holistic programming scheme by designing a novel compiler-assisted scheduling approach (called REIS) able to identify and eliminate redundancies across applications. To achieve this useful high-level optimization, we model each user application as a linear sequence of executable instructions. We show how well-known string-matching algorithms such as the Longest Common Subsequence (LCS) and the Shortest Common Super-sequence (SCS) can be used to produce an optimal merged monolithic sequence of the deployed applications that takes into account embedded scheduling information. We show that our approach can help in achieving about 60% average energy savings in processor usage compared to the normal execution of concurrent applications.

A case study on the eco-efficiency performance of a composite processing industry: evaluation and quantification of potential improvements

In this study, an attempt was made in order to measure and evaluate the eco-efficiency performance of a pultruded composite processing company. For this purpose the recommendations of World Business Council for Sustainable Development (WCSD) and the directives of ISO 14301 standard were followed and applied. The main general indicators of eco-efficiency, as well as the specific indicators, were defined and determined. With basis on indicators’ figures, the value profile, the environmental profile, and the pertinent eco-efficiency ratios were established and analyzed. In order to evaluate potential improvements on company eco-performance, new indicators values and eco-efficiency ratios were estimated taking into account the implementation of new proceedings and procedures, at both upstream and downstream of the production process, namely: i) Adoption of a new heating system for pultrusion die-tool in the manufacturing process, more effective and with minor heat losses; ii) Recycling approach, with partial waste reuse of scrap material derived from manufacturing, cutting and assembly processes of GFRP profiles. These features lead to significant improvements on the sequent assessed eco-efficiency ratios of the present case study, yielding to a more sustainable product and manufacturing process of pultruded GFRP profiles.