Managing energy demand is essential to energy security and climate change mitigation. The industrial sector accounts for over a fifth of UK primary energy demand and greenhouse gas emissions. Energy intensive industry is uniquely restricted in the way it uses energy and emits greenhouse gasses. In this thesis, the potential of radical measures to achieve significant energy demand reduction and emissions abatement in UK energy intensive industry is assessed. Adopted is a multidisciplinary approach combining thermodynamic and techno-economic analysis techniques. Bottom-up assessments are applied to key energy intensive sectors of industry to capture the diverse and interactive array of technological characteristics invisible from a top-down perspective. Detailed projection models are built to design and analyse technology roadmaps for the sectors out to 2050. In an illustrative roadmap assessment, the technological pathways of radical process transition and carbon sequestration were each shown to achieve about 80% abatement in 2050 from 1990 emissions levels. Radical process transition achieved greater abatement before 2030 and this was reflected in lower cumulative emissions over the full period. Higher risk is associated with carbon sequestration from its reliance on timely access to CO2 transport and storage technology to compensate for lower short-medium term abatement. Although, combining carbon sequestration with high levels of biomass combustion indicated the largest potential abatement to 2050. Abatement economics in the iron and steel sector are notably sensitive to resource costs and the carbon trading price. The carbon trading price influences relative production costs in favour of higher abating pathways, but increases absolute costs. This signals the need for supportive policy measures that accelerate technology development and deployment while mitigating the risk of the carbon trading price to competitiveness. Some carbon capture technologies reduce relative production cost even in the absence of a carbon price, but this excludes the cost of CO2 transport and storage. Meanwhile, radical process transition pathways have a higher dependence on the future prices of natural gas, electricity, and scrap. Future work should focus on expanding the economic appraisal to other sectors and to indirect costs, as well as incorporating wider material efficiency strategies and running different future scenarios.

Os atuais sistemas de HPC tem realizado simulações mais complexas possíveis, produzindo benefícios para diversas áreas de pesquisa. Para atender à crescente demanda de processamento dessas simulações, novos equipamentos estão sendo projetados, visando à escala exaflops. Um grande desafio para a construção destes sistemas é a potência que eles vão demandar, onde perspectivas atuais alcançam GigaWatts. Para resolver este problema, esta tese apresenta uma abordagem para aumentar a eficiência energética usando recursos de HPC, objetivando reduzir os efeitos do desequilíbrio de carga e economizar energia. Nós desenvolvemos uma estratégia baseada no consumo de energia, chamada ENERGYLB, que considera características da plataforma, irregularidade e dinamicidade de carga das aplicações para melhorar a eficiência energética. Nossa estratégia leva em conta carga computacional atual e a frequência de clock dos cores, para decidir entre chamar uma estratégia de balanceamento de carga que reduz o desequilíbrio de carga migrando tarefas, ou usar técnicas de DVFS par ajustar as frequências de clock dos cores de acordo com suas cargas computacionais ponderadas. Como as diferentes arquiteturas de processador podem apresentam dois níveis de granularidade de DVFS, DVFS-por-chip ou DVFS-por-core, nós criamos dois diferentes algoritmos para a nossa estratégia. O primeiro, FG-ENERGYLB, permite um controle fino da frequência dos cores em sistemas que possuem algumas dezenas de cores e implementam DVFS-por-core. Por outro lado, CG-ENERGYLB é adequado para plataformas de HPC composto de vários processadores multicore que não permitem tal refinado controle, ou seja, que só executam DVFS-por-chip. Ambas as abordagens exploram desbalanceamentos residuais em aplicações interativas e combinam balanceamento de carga dinâmico com técnicas de DVFS. Assim, eles reduzem a frequência de clock dos cores com menor carga computacional os quais apresentam algum desequilíbrio residual mesmo após as tarefas serem remapeadas. Nós avaliamos a aplicabilidade das nossas abordagens utilizando o ambiente de programação paralela CHARM++ sobre benchmarks e aplicações reais. Resultados experimentais presentaram melhorias no consumo de energia e na demanda potência sobre algoritmos do estado-da-arte. A economia de energia com ENERGYLB usado sozinho foi de até 25% com nosso algoritmo FG-ENERGYLB, e de até 27% com nosso algoritmo CG-ENERGYLB. No entanto, os desequilíbrios residuais ainda estavam presentes após as serem tarefas remapeadas. Neste caso, quando as nossas abordagens foram empregadas em conjunto com outros balanceadores de carga, uma melhoria na economia de energia de até 56% é obtida com FG-ENERGYLB e de até 36% com CG-ENERGYLB. Estas economias foram obtidas através da exploração do desbalanceamento residual em aplicações interativas. Combinando balanceamento de carga dinâmico com DVFS nossa estratégia é capaz de reduzir a demanda de potência média dos sistemas paralelos, reduzir a migração de tarefas entre os recursos disponíveis, e manter o custo de balanceamento de carga baixo. / Current HPC systems have made more complex simulations feasible, yielding benefits to several research areas. To meet the increasing processing demands of these simulations, new equipment is being designed, aiming at the exaflops scale. A major challenge for building these systems is the power that they will require, which current perspectives reach the GigaWatts. To address this problem, this thesis presents an approach to increase the energy efficiency using of HPC resources, aiming to reduce the effects of load imbalance to save energy. We developed an energy-aware strategy, called ENERGYLB, which considers platform characteristics, and the load irregularity and dynamicity of the applications to improve the energy efficiency. Our strategy takes into account the current computational load and clock frequency, to decide whether to call a load balancing strategy that reduces load imbalance by migrating tasks, or use Dynamic Voltage and Frequency Scaling (DVFS) technique to adjust the clock frequencies of the cores according to their weighted loads. As different processor architectures can feature two levels of DVFS granularity, per-chip DVFS or per-core DVFS, we created two different algorithms for our strategy. The first one, FG-ENERGYLB, allows a fine control of the clock frequency of cores in systems that have few tens of cores and feature per-core DVFS control. On the other hand, CGENERGYLB is suitable for HPC platforms composed of several multicore processors that do not allow such a fine-grained control, i.e., that only perform per-chip DVFS. Both approaches exploit residual imbalances on iterative applications and combine dynamic load balancing with DVFS techniques. Thus, they reduce the clock frequency of underloaded computing cores, which experience some residual imbalance even after tasks are remapped. We evaluate the applicability of our approaches using the CHARM++ parallel programming system over benchmarks and real world applications. Experimental results present improvements in energy consumption and power demand over state-of-the-art algorithms. The energy savings with ENERGYLB used alone were up to 25%with our FG-ENERGYLB algorithm, and up to 27%with our CG-ENERGYLB algorithm. Nevertheless, residual imbalances were still present after tasks were remapped. In this case, when our approaches were employed together with these load balancers, an improvement in energy savings of up to 56% is achieved with FG-ENERGYLB and up to 36% with CG-ENERGYLB. These savings were obtained by exploiting residual imbalances on iterative applications. By combining dynamic load balancing with the DVFS technique, our approach is able to reduce the average power demand of parallel systems, reduce the task migration among the available resources, and keep load balancing overheads low.

Multiple-input multiple-output (MIMO) systems are a mature technology that has been incorporated into current wireless broadband standards to improve the channel capacity and link reliability. Nevertheless, due to the continuous increasing demand for wireless data traffic new strategies are to be adopted. Very large MIMO antenna arrays represents a paradigm shift in terms of theory and implementation, where the use of tens or hundreds of antennas provides significant improvements in throughput and radiated energy efficiency compared to single antennas setups. Since design constraints limit the number of usable antennas, virtual systems can be seen as a promising technique due to their ability to mimic and exploit the gains of multi-antenna systems by means of wireless cooperation. Considering these arguments, in this work, energy efficient coding and network design for large virtual MIMO systems are presented. Firstly, a cooperative virtual MIMO (V-MIMO) system that uses a large multi-antenna transmitter and implements compress-and-forward (CF) relay cooperation is investigated. Since constructing a reliable codebook is the most computationally complex task performed by the relay nodes in CF cooperation, reduced complexity quantisation techniques are introduced. The analysis is focused on the block error probability (BLER) and the computational complexity for the uniform scalar quantiser (U-SQ) and the Lloyd-Max algorithm (LM-SQ). Numerical results show that the LM-SQ is simpler to design and can achieve a BLER performance comparable to the optimal vector quantiser. Furthermore, due to its low complexity, U-SQ could be consider particularly suitable for very large wireless systems. Even though very large MIMO systems enhance the spectral efficiency of wireless networks, this comes at the expense of linearly increasing the power consumption due to the use of multiple radio frequency chains to support the antennas. Thus, the energy efficiency and throughput of the cooperative V-MIMO system are analysed and the impact of the imperfect channel state information (CSI) on the system's performance is studied. Finally, a power allocation algorithm is implemented to reduce the total power consumption. Simulation results show that wireless cooperation between users is more energy efficient than using a high modulation order transmission and that the larger the number of transmit antennas the lower the impact of the imperfect CSI on the system's performance. Finally, the application of cooperative systems is extended to wireless self-backhauling heterogeneous networks, where the decode-and-forward (DF) protocol is employed to provide a cost-effective and reliable backhaul. The associated trade-offs for a heterogeneous network with inhomogeneous user distributions are investigated through the use of sleeping strategies. Three different policies for switching-off base stations are considered: random, load-based and greedy algorithms. The probability of coverage for the random and load-based sleeping policies is derived. Moreover, an energy efficient base station deployment and operation approach is presented. Numerical results show that the average number of base stations required to support the traffic load at peak-time can be reduced by using the greedy algorithm for base station deployment and that highly clustered networks exhibit a smaller average serving distance and thus, a better probability of coverage.

Significant savings in CO2 emissions can be won from fabric upgrades, and improved forms of heating. An increase in the number of building retrofits and installations of energy efficient plant such as biomass boilers or CCHPs must be the aim if the UK is serious in meeting its commitment to CO2 reduction at both the domestic and EU level. A way of achieving this increase, which will need to be significant, would be to tap into the vast funds under management by institutional investors who are required to invest those funds to optimise its monetary return, taking into account the level of risk. The aim of the research is to identify the enabling conditions that would need to exist to attract institutional investment in energy efficiency at scale. The UK Green Investment Bank has invested £50m into three energy efficiency funds, requiring each fund manager to match the amount by attracting investment from institutional investors. It is these funds that have been analysed as a single Green Investment Bank case study. Embedded units of analysis are on two levels with the individual funds being the first, and the institutional investors investing in those funds as the second. A hybrid deductive and inductive qualitative approach to the research was taken employing thematic analysis. The findings of the research reported here indicate that the emerging key enabling conditions that would make energy efficiency an attractive proposition are firstly, the way energy efficiency investments are classified in terms of an investment asset class, secondly the contractual structure of the individual transactions made by the funds, and finally, the experience and familiarity of the fund manager.

Rapid device-miniaturization keeps on inducing challenges in building energy efficient microprocessors. As the size of the transistors continuously decreasing, more uncertainties emerge in their operations. On the other hand, integrating more and more transistors on a single chip accentuates the need to lower its supply-voltage. This dissertation investigates one of the primary device uncertainties - timing error, in microprocessor performance bottleneck in NTC era. Then it proposes various innovative techniques to exploit these opportunities to maintain processor energy efficiency, in the context of emerging challenges. Evaluated with the cross-layer methodology, the proposed approaches achieve substantial improvements in processor energy efficiency, compared to other start-of-art techniques.

This thesis seeks to address energy efficient design in a temperate climate in typical small, medium density housing, particularly in housing for the aged. The connections between energy efficient design and small, medium density housing were identified as contemporary issues related to Australian Government policies in two disparate areas. One policy area is reflected in the Government's commitment to assist older people, whether they are active, early retirees or the frail elderly, wealthy or poor, to live in their chosen place of residence. Increasingly this chosen place of residence may be a small, medium density dwelling. The other policy area is that related to reducing energy consumption in buildings. This policy is reflected in recently proclaimed building regulations aimed at reducing space heating/cooling requirements in housing. The building regulations include details of acceptable construction practice for energy efficiency that may not be appropriate in small, medium density housing. It was proposed in this thesis that extensive use of space heating and cooling in housing for the aged was required because well-established benchmarks for energy efficient design in a temperate climate were not generally appropriate in small, medium density dwellings and were particularly inappropriate in housing for the aged. `Appropriate' in this context referred to: indoor temperatures being acceptable without the need for space heating and cooling; retaining the site planning and general form of typical, medium density aged persons housing developments in suburban Australia; cost effectiveness over the life of a building; and fitting the needs of physically and financially vulnerable older people. / The methods used to examine the notion of appropriateness commenced with a literature review that related to the general physical and economic status of older people and their needs and responses to space heating and cooling in the home. Further, the literature review considered the principles of energy efficient design and benchmark criteria for energy efficiency. Arising from the literature review, two tools of study were used in order to develop a set of data encapsulating the salient features of small, medium density housing. The first was a multiple case study of typical housing for the aged. This was conceived as a way of determining if small, medium density dwellings could provide appropriate indoor thermal conditions and/or were designed to be energy efficient. The indoor temperatures were monitored in summer and winter and annual energy consumption was established and statistically analysed. The building designs were analysed in terms of their orientation, glazing areas, wall areas, volumes of thermal mass and ventilation capacity and compared with benchmarks for energy efficient design. The second tool involved a series of computer simulations of a typical small, medium density dwelling. The simulation process was utilised to determine if a new set of benchmarks for energy efficient small, medium density dwellings were required that would incorporate the notion of appropriateness. From the multiple case study it was found that, irrespective of design, indoor temperatures in 98% of dwellings were above the acceptable maximum summer temperature of 27.4°C in still air and indoor temperatures in all dwellings were found to be below the acceptable minimum daytime temperature of 19.8°C. / The findings also showed that some aspects of the benchmarks for energy efficient design were not appropriate in typical, medium density housing constructed specifically for the aged. From the simulation process it was discovered that acceptable temperatures could be achieved in small medium density housing if the principles of energy efficient design, incorporated within a new set of benchmarks, were integrated with appropriateness criteria for housing for the aged. The approach taken with the new benchmarks was to create both performance based and prescriptive design solutions. The performance model differs from the current benchmarks for energy efficient design in that it establishes key functional objectives for energy efficient design. Compared to the current benchmarks, the prescriptive design solutions show significant reductions in the areas of northerly glazing and total glazing. To compensate for the reduced area of northerly glazing, both direct and indirect means of solar gain are utilised for passive heating. The thesis outcomes have implications for three areas of the construction industry. The prescriptive design solutions presented in building regulations for energy efficiency in housing need to be qualified, the design briefs prepared for energy efficient construction of small, medium density housing need amendment and the approach taken by designers involved in energy efficient small, medium density housing needs to be reconsidered.

The issue of sustainability has gained significance in the past two decades or so particularly inthe business sector throughout the globe. Companies from various industries have inculcatedaspects of sustainability in their portfolios due to reasons ranging from stakeholder demandsto industry competition and profit. In fact, with the issues of climate change and resourcedepletion now gaining global political and economic significance; not going ‘green’ is not anoption for companies anymore.This paper sheds light on the ways that companies are becoming more environmental friendlyand benefitting from this process. All aspects of the business process ranging fromprocurement of materials to waste management and recycling have been viewed from asustainability perspective. This also includes the manner in which firms practice ‘greenmarketing’ for their environmental friendly practices and products. Since this paper will actas a guiding strategy for a company ‘Ascom’, the industry under focus is thetelecommunications industry. More specifically, the activities of three of Ascom’s majorcompetitors namely Siemens, Alcatel and Cisco have been thoroughly reviewed to providebenchmarks for Ascom. Coupled with the current theories and frameworks on the issue ofsustainability in business, the benchmarks set by these competitors will be used torecommend Ascom on how they can become more ‘green’.

The thesis project explores the use of an optimization methodology for selecting the lowest monetary cost combinations of technologies to meet a set operational energy efficiency targets for buildings. The optimization approach, which is operated on a normative energy model, is compared with existing prescriptive methodologies for selecting technology combinations and a metric is developed for ranking their effectiveness; the E/C Ratio. The energy savings/ cost ratio is also the objective function that the optimization algorithm is set to maximize. The optimization routine is coded in to a custom MATLAB script and is used in two case studies to optimize a proto-typical Korean apartment and office building. The optimization methodology finds technology combinations that are much more cost effective than the prescriptive methodology at meeting an energy savings target and can generically be applied to other buildings given a palette of technology alternatives and the corresponding cost data.

IEEE 802.15.4 is a standard used for low rate personal area networks (PANs). It offers device level connectivity in applications with limited ower and relaxed throughput requirements. Devices with IEEE 802.15.4 technology can be used in many potential applications, such as home networking, industry/environments monitoring, healthcare equipments, etc, due to its extremely low power features. Although the superframe beacons play the key role in synchronizing channel access in IEEE 802.15.4, they are sources for energy inefficiency. This research focuses on exploring how to optimize the beacons, and designing novel schemes to distribute the information that are supposed to be delivered to a subset of PAN devices. In this work, an acknowledgement based scheme is proposed to reduce the energy consumption in the distribution of guaranteed time slot (GTS) descriptors. Based on the observation that the superframe beacon frame has global impact on all PAN devices, an energy-efficient channel reservation scheme is presented to deliver the information (GTS descriptors and pending addresses). In addition, the problem of channel underutilization is studied in the contention free period. To address the problem, a new GTS allocation scheme is proposed to improve the bandwidth utilization.

Wireless Sensor Networks (WSN) are used in many applications, for example industrial applications, automatic control applications, monitoring applications, to name but a few. Although WSN can employ different standards in order to achieve short range wireless communication, the mainstream of the market is toadopt the low-power, low-rate IEEE 802.15.4 standard. However, this standard does not specify any block codes on the Physical layer (PHY) and the MAC sublayer. Reliability and energy efficiency are two important metrics used to evaluate the WSN performance. In order to enhance the reliability of the WSN performance, schemes such as Forward Error Correction (FEC) and HybridAutomatic Repeat-reQuest (HARQ) can be introduced on the PHY and MACsublayer when transmitting signals. However, this will reduce the energy efficiency of the WSN. In order to investigate what does affect the reliability and energy efficiency, this thesis has been conducted with the assistance of Matlab simulations, which simulate different transmission schemes proposed by the authors. Based on the simulations, both the reliability and energy efficiency can be evaluated and the results are illustrated for both metrics. The objective of this thesis is to determine a scheme that is able to meet these metric requirements.