Academic literature on the topic 'Energy efficiency not elsewhere classified'

Energy storage is a key technology for many purposes and in particular for air conditioning plants and a successful exploitation of solar energy. Thermal storage devices are usually classified as either variable temperature (“sensible heat”) or constant temperature (“latent heat”) devices. For both models a basic question is to determine the efficiency suitably: Only exergy efficiency appears a proper way. The aim of this paper is to examine exergy efficiency in both variable and constant temperature systems. From a general statement of exergy efficiency by the present author, two types of actual definitions are proposed, depending on the fact that the exergy of the fluid leaving the thermal storage during the charge phase can be either totally lost or utilized elsewhere. In addition, specific remarks are made about the exergy of a system in a periodically varying temperature environment.

The purpose of this research is to investigate built building envelope renovation methods. Earlier studies on built building renovation have shown that the significant influence of using built building instead of the new building in terms of the energy crisis. However, these have not yet compared various renovation methods for building surface. Therefore, this study classified several reconstruction means into three types and evaluated their performances under three indicators: 1) construction; 2) material; 3) impact on original building appearance. The result shows that the integrated system of insulation and decoration is the best, and the method of additional components is the worst for building enclosure renovation.

This study fully considers the incomparable factors in city's energy efficiency assessment, and proposes a framework for city's energy efficiency assessment based on classification. In the process of classifying cities, the SVM method is used to establish a quantitative relationship model between relevant factors and city's energy consumption. Based on the model, the objective energy demand of the city is calculated, and the city is classified according to the level of objective energy demand. By comparing the actual energy consumption of the city with the objective energy demand, we can eliminate the interference of the incomparable factors on the city's energy efficiency assessment.

Abstract. This study involved performing an economic analysis on agricultural tractors classified based on energy efficiency grades using the energy efficiency index. Specifically, 131 models of agricultural tractors commonly used between 2006 and 2010 in South Korea were classified into five categories. The relationship between energy efficiency and economic value was evaluated by a numerical method, and a method of predicting cost and fuel savings based on energy efficiency was developed. Grades of energy efficiency labeled from 1–5 were assumed in order to calculate annual fuel and cost savings. The results indicated that the use of the proposed method resulted in fuel and cost savings given an upgrade from the 5th level of energy efficiency to the 1st level and indicated subsequent improvements with each grade level. This method was applied to data from the year 2008, and total fuel and cost savings were obtained. This indicated that fuel and cost savings in an arbitrary year could be predicted using the proposed method and assuming data from an arbitrary year. Keywords: Agricultural tractors, Economic analysis, Energy efficiency classification grade, Energy efficiency index.

This study investigates an energy-efficient scheme in multirelay cooperative networks with energy harvesting where multiple sessions need to communicate with each other via the relay node. A two-step optimal method is proposed which maximizes the system energy efficiency, while taking into account the receiver circuit energy consumption. Firstly, the optimal power allocation for relay nodes is determined to maximize the system throughput; this is based on directional water-filling algorithm. Secondly, using quantum particle swarm optimization (QPSO), a joint relay node selection and session grouping optimization is proposed. With this algorithm, sessions can be classified into multiple groups that are assisted by the specific relay node with the maximum energy efficiency. This approach leads to a better global optimization in searching ability and efficiency. Simulation results show that the proposed scheme can improve the energy efficiency effectively compared with direct transmission and opportunistic relay-selected cooperative transmission.

Energy efficiency programmes (EEPs) are schemes operated by utilities or other bodies in order to incentivize energy efficiency improvement, in particular by adoption of energy-efficient products and typically by means of an economic reward. Ample experience has been gained, especially in the U.S., where EEPs have been in use for decades, with the rationale of avoiding additional energy supply by improving energy efficiency. More recently, EEPs have been implemented in Europe and in Switzerland. This review paper presents insights from the U.S., the EU and especially from Switzerland, with a focus on levelised programme cost of saved energy (LPC) as a key performance indicator. These LPC values, which take the perspective of the programme operator, are typically low to very low compared to the cost of electricity supply, thereby representing an important argument in favour of their use. The country examples show that EEPs are being effectively and successfully put into practice, for example, in Switzerland both as (i) a national tender-based scheme (called ProKilowatt) and in the form of a (ii) utility-operated obligation-based scheme (in Geneva). EEPs not only call for diligent implementation but also for suitable legal settings, e.g., in the form of mandatory energy efficiency savings targets (as realised for energy efficiency obligations, EEOs) in combination with programme cost recovery. The main criticism of EEPs is the free-rider effect, which needs to be minimised. On the other hand, EEPs are accompanied by significant co-benefits (environmental, health-related and social) and spillover effects. In their currently prevalent form, EEPs allow one to effectively save energy at a (very) low cost (“low-hanging fruit”). They can hence play an important role in fostering the energy transition; however, they should be implemented as part of a policy portfolio, in combination with other policy instruments.

. Experiments of sawing granite with diamond circular blades were carried out to study the energy efficiency in circular sawing. Energy consumed by machine spindle is classified into energy used without cutting and energy used with cutting. The energy used without cutting almost increases with the improvement of peripheral speed of blade. The energy consumption coefficient, the ratio of energy used with cutting to total energy consumed by spindle, increases with the increase of material removed rate, which reveals that higher material removed rate is favor for improving energy utilization. A fixed trend of energy consumption coefficient versus material removal rate was found and it might be useful for selecting cutting parameters for low energy sawing.

Over the last few decades, energy efficiency has received increasing attention from the Architecture, Engineering, Construction and Operation (AECO) industry. Digital Twins have the potential to advance the Operation and Maintenance (O&M) phase in different application fields. With the increasing industry interest, there is a need to review the current status of research developments in Digital Twins for building energy efficiency. This paper aims to provide a comprehensive review of the applications of digital twins for building energy efficiency, analyze research trends and identify research gaps and potential future research directions. In this review, Sustainability and Energy and Buildings are among the most frequently cited sources of publications. Literature reviewed was classified into four different topics: topic 1. Optimization design; topic 2. Occupants’ comfort; topic 3. Building operation and maintenance; and topic 4. Energy consumption simulation.

The objective of this study was the ethanol which classified as agro fuels. The aim of our research was the calculation of efficiency of bioethanol production, and evaluates the yield of maize hybrids grown for this purpose. We examined the energy demand of corn production per hectare in two vintages of 2009 and 2010. The focus of the experiment was placed in three different doze of fertilizer. Results show that the control corn plot used the least amount of non-renewable energy. Improving starch yield by adding fertilizer required additional nonrenewable energy inputs. So then the invested energy has a great impact on the efficiency.

Housing sectors have particular significance and impact on resource use, deployment and sustainability. Given this, they are inextricably enmeshed in a raft of conjoined issues, ranging from energy, production and consumption, through to effective governance structures and leveraged sustainable transformations. However, the real challenges facing the Housing sectors rest with the supportive societal structures which underpin the operationalisation of these issues. This includes such factors as consultation and engagement, and the identification of critical drivers and proven solutions – which are tangible barriers for sustainable transformations (particularly in the English housing system). This research presents a conceptual model – STRIDES (Strategic Tri-level Relational Interventions for Delivering Energy efficiency and Sustainability), which purposefully addresses the aforementioned barriers, and critically challenges thinking and engagement. STRIDES explicitly captures 5-INs, which embodies interrelated essential conditions needed for successful transformation. This conceptual model was developed using a mixed-method approach, engaging constructivism/interpretivism to guide the development and augmentation of this (to ensure maximum relevance and impact). The English housing system was used as the primary lens – which helped both shape and inform the research methodological approach. STRIDES was developed through: an online survey questionnaire (for systems-knowledge); Delphi questionnaires (for target-knowledge); and focus group discussions (for transformative-knowledge). The theoretical constructs and methods revealed exclusive hidden dialogue of composite correlated multi-perspective stakeholders, which highlighted tri-level influences on interdependent system-components for effective governance of sustainable transformations. Recognising and prioritising relationally responsive emerging strategies arising from STRIDES help stakeholders appreciate subtle nuances and forces across and beyond contexts. This helps positioning, especially to shape/tailor strategic interventions to deliver meaningful objectives of these sustainable transformations.

Over reliance on fossil fuels, rising global population, industrialization, demands for a higher standard of living and transportation have caused alarming damage to the environment. If current trend continues then catastrophic damage to the earth and its environment may not be reversible. There is an urgent need to reduce the use of fossils fuels and substituting it with renewable energy sources such as wind, tidal and hydroelectric. Solar source seems to be the most promising due to its environmental friendly nature, portability and reliability. This source was examined in terms of microbusinesses such as SMEs including hair dressing salon, education centre, fried chicken outlet and printing shop. Small businesses account for a large proportion of the economy. The analysis developed could be applied to small business to show their contribution to the carbon footprint and how this could be reduced using solar energy. The proportions of their current electricity usage that could be substituted with solar cells were calculated. Combined these have a significant impact. These businesses were considered for UK and Iraq with the former being more amenable to solar energy implementation. Analysis of the four SMEs showed that the most energy intensive business was fried chicken take away using a large amount of electricity and the least energy intensive business was the education centre. In the latter in UK 57% of the electricity usage could be replaced by solar energy compared to Kurdistan, which generated a surplus energy that could be fed into the national grid. The gents groom hairdressing and blue apple businesses gave intermediate figures. Parallel conclusions were drawn regarding CO2 emissions released into the atmosphere with education centre being the most environmentally friendly and the fried chicken the least. In addition, a larger public space, an international airport data was analysed and the value of solar replacement demonstrated. The methodology and data analysis approach used may be implemented for other business units and larger public spaces such as hospitals, shopping complexes and football stadiums.

The International Energy Agency has stated that it is more sustainable to improve the energy efficiency of already existing buildings than increasing the national energy production to provide inefficient buildings with even more energy, which would result in that an increased amount of resources required to power the existing energy inefficient building stock. Taken into consideration that buildings in Sweden consume about 40% of Sweden’s final energy consumption and count for about 36% of the total greenhouse gas emissions it becomes evident that in order to decrease Sweden’s carbon foot print, it is important to understand real estate investors decision-making process. The aspiration is to provide stakeholders both on a micro and macro level with a better understanding of the real estate investors decision making process. This will enable companies (micro level) in the field to better customize their value propositions and there by enable companies to contribute to decreasing the primary energy consumption of buildings in Sweden. The macro level, referring to governmental institutions, will be provided with a better understanding of what kind of measures can be taken, to increase investments into buildings energy efficiency. It could be found from the literature reviewed for the study that there is a gap in research what comes to the Swedish market. Majority of the existing literature covers bigger markets e.g. the USA and UK but very little or if at all the Swedish market. During the literature study an existing framework on decision drivers for real estate investors was developed. The study uses mixed method consisting of qualitative and quantitative methods to answer the research questions. The study showed that the most prominent drivers on the Swedish market were the customers strategic decisions, environmental and energy certificates, reporting protocols, investment horizon, rental agreements, internal investment policies decreased property costs and building specific characteristics. It was found that the Swedish real estate investors experience very little pressure from the government to increase the energy efficiency of their buildings. It was also found that governmental subsidies are more considered a gamble than an encouragement to invest in energy efficiency due to long processing times and heavy bureaucracy.

Molecular separations are essential in the production of many chemicals and purified products. Of all the available separation technologies, distillation, which is a thermally driven process, has been and continues to be one of the most utilized separation methods in chemical and petrochemical plants. Although distillation and other commercial technologies fulfilled most of the current separation needs, the energy-intensive nature of many molecular separations and the growing concern of reducing CO₂ emissions has led to intense research to seek for more energy-efficient separation processes.

Among the emerging separation technologies alternative to distillation, there is special attention on non-thermally driven methods, such as membranes. The growing interest in non-thermal methods, and particularly in the use of membranes, has been influenced significantly from the widespread perception that they have a potential to be markedly less energy-intensive than thermal methods such as distillation. Even though many publications claim that membranes are more energy-efficient than distillation, except for water desalination, the relative energy intensity between these processes in the separation of chemical mixtures has not been deeply studied in the literature. One of the objectives of this work focuses on introducing a framework for comparative analysis of the energy intensity of membranes and distillation.

A complication generally encountered when comparing the energy consumption of membranes against an alternative process is that often the purity and recovery that can be achieved through a single membrane stage is limited. While using a multi-stage membrane process is a plausible solution to achieve both high purity and recovery, even for a simple binary separation, finding the most suitable multistage membrane process is a difficult task. This is because, for a given separation, there exists multiple cascades that fulfill the separation requirements but consume different amounts of energy. Moreover, the energy requirement of each cascade depends on the operating conditions. The first part of this work is dedicated to the development of a Mixed Integer Non-linear Program (MINLP) which allows for a given gaseous or liquid binary separation, finding the most energy-efficient membrane cascade. The permeator model, which is derived from a combination of the cross-flow model and the solution diffusion theory, and is originally expressed as a differential-algebraic equation (DAE) system, was integrated analytically before being incorporated in the optimization framework. This is in contrast to the common practice in the literature, where the DAE system is solved using various discretization techniques. Since many of the constraints have a non-convex nature, local solvers could get trapped in higher energy suboptimal solutions. While an option to overcome this limitation is to use a global solver such as BARON, it fails to solve the MINLP to the desired optimality in a reasonable amount of time for most of the cases. For this reason, we derive additional cuts to the problem by exploiting the mathematical properties of the governing equations and from physical insights. Through numerical examples, we demonstrate that the additional cuts aid BARON in expediting the convergence of branch-and-bound and solve the MINLP within 5%-optimality in all the cases tested in this work.

The proposed optimization model allows identifying membrane cascades with enhanced energy efficiency that could be potentially used for existing or new separations. In addition, it allows to compare the optimum energy consumption of a multistage membrane process against alternative separations methods and aid in the decision of whether or not to use a membrane system. Nevertheless, it should be noted that when a membrane process or any other non-thermal separation process is compared with a thermal process such as distillation, an additional complication often arises because these processes usually use different types of energies. Non-thermal processes, such as membranes, consume electrical energy as work, whereas thermal processes, such as distillations, usually consume heat, which is available in a wide range of temperatures. Furthermore, the amount of fuel consumed by a separation process strongly depends on how its supplied energy is produced, and how it is energy integrated with the rest of the plant. Unfortunately, common approaches employed to compare the energy required by thermal and non-thermal methods often lead to incorrect conclusions and have driven to the flawed perception that thermal methods are inherently more energy-intensive than non-thermal counterparts. In the second part of this work, we develop a consistent framework that enables a proper comparison of the energy consumption between processes that are driven by thermal and non-thermal energy (electrical energy). Using this framework, we refute the general perception that thermal separation processes are necessarily the most energy-intensive and conclusively show that in several industrially important separations, distillation processes consume remarkably lower fuel than non-thermal membrane alternatives, which have often been touted as more energy efficient.

In order to gain more understanding of the conditions where membranes or distillation are more energy-efficient, we carried out a comprehensive analysis of the energy consumed by these two processes under different operating conditions. The introduced energy comparison analysis was applied to two important separation examples; the separation of p-xylene/o-xylene, and propylene/propane. Our results showed that distillation is more energy favored than membranes when the target purity and recovery of the most volatile (resp. most permeable) component in the distillate (resp. permeate) are high, and particularly when the feed is not too concentrated in the most volatile (resp. most permeable) component. On the other hand, when both the recovery and purity of the most volatile (resp. most permeable) component are required at moderate levels, and particularly when the feed is highly enriched in the most volatile (resp. most permeable) component, membranes show potential to save energy as compared to distillation.

Modern computing platforms, from servers to mobile devices, demand ever-increasing amounts of memory to keep up with the growing amounts of data they process, and to bridge the widening processor-memory gap. A large and growing fraction of chip area and energy is expended in memories, which face challenges with technology scaling due to increased leakage, process variations, and unreliability. On the other hand, data intensive workloads such as machine learning and data analytics pose increasing demands on memory systems. Consequently, improving the energy-efficiency and performance of memory systems is an important challenge for computing system designers.

Spintronic memories, which offer several desirable characteristics - near-zero leakage, high density, non-volatility and high endurance - are of great interest for designing future memory systems. However, these memories are not drop-in replacements for current memory technologies, viz. Static Random Access Memory (SRAM) and Dynamic Random Access Memory (DRAM). They pose unique challenges such as variable access times, and require higher write latency and write energy. This dissertation explores new approaches to improving the energy efficiency of spintronic memory systems.

The dissertation first explores the design of approximate memories, in which the need to store and access data precisely is foregone in return for improvements in energy efficiency. This is of particular interest, since many emerging workloads exhibit an inherent ability to tolerate approximations to their underlying computations and data while still producing outputs of acceptable quality. The dissertation proposes that approximate spintronic memories can be realized either by reducing the amount of data that is written to/read from them, or by reducing the energy consumed per access. To reduce memory traffic, the dissertation proposes approximate memory compression, wherein a quality-aware memory controller transparently compresses/decompresses data written to or read from memory. For broader applicability, the quality-aware memory controller can be programmed to specify memory regions that can tolerate approximations, and conforms to a specified error constraint for each such region. To reduce the per-access energy, various mechanisms are identified at the circuit and architecture levels that yield substantial energy benefits at the cost of small probabilities of read, write or retention failures. Based on these mechanisms, a quality-configurable Spin Transfer Torque Magnetic RAM (STT-MRAM) array is designed in which read/write operations can be performed at varying levels of accuracy and energy at runtime, depending on the needs of applications. To illustrate the utility of the proposed quality-configurable memory array, it is evaluated as an L2 cache in the context of a general-purpose processor, and as a scratchpad memory for a domain-specific vector processor.

The dissertation also explores the design of caches with Domain Wall Memory (DWM), a more advanced spintronic memory technology that offers unparalleled density arising from a unique tape-like structure. However, this structure also leads to serialized access to the bits in each bit-cell, resulting in increased access latency, thereby degrading overall performance. To mitigate the performance overheads, the dissertation proposes a reconfigurable DWM-based cache architecture that modulates the active bits per tape with minimal overheads depending on the application's memory access characteristics. The proposed cache is evaluated in a general purpose processor and improvements in performance are demonstrated over both CMOS and previously proposed spintronic caches.

In summary, the dissertation suggests directions to improve the energy efficiency of spintronic memories and re-affirms their potential for the design of future memory systems.

Cyber physical systems are deployed in a wide range of applications from sensor nodes in a factory setting to drones in defense applications. This distributed setting of nodes or processes often needs to reach agreement on a set of values. Byzantine Agreement protocols address this issue of reaching an agreement in an environment where a malicious entity can take control over a set of nodes and deviates the system from its normal operation. However these protocols do not consider the energy consumption of the nodes. We explore Byzantine Agreement protocols from an energy efficient perspective providing both energy resilience where the actions of the Byzantine nodes can not adversely effect the energy consumption of non-malicious nodes as well as fairness in energy consumption of nodes over multiple rounds of agreement.

Spiking Neural Networks (SNNs), widely known as the third generation of artificial neural networks, offer a promising solution to approaching the brains' processing capability for cognitive tasks. With more biologically realistic perspective on input processing, SNN performs neural computations using spikes in an event-driven manner. The asynchronous spike-based computing capability can be exploited to achieve improved energy efficiency in neuromorphic hardware. Furthermore, SNN, on account of spike-based processing, can be trained in an unsupervised manner using Spike Timing Dependent Plasticity (STDP). STDP-based learning rules modulate the strength of a multi-bit synapse based on the correlation between the spike times of the input and output neurons. In order to achieve plasticity with compressed synaptic memory, stochastic binary synapse is proposed where spike timing information is embedded in the synaptic switching probability. A bio-plausible probabilistic-STDP learning rule consistent with Hebbian learning theory is proposed to train a network of binary as well as quaternary synapses. In addition, hybrid probabilistic-STDP learning rule incorporating Hebbian and anti-Hebbian mechanisms is proposed to enhance the learnt representations of the stochastic SNN. The efficacy of the presented learning rules are demonstrated for feed-forward fully-connected and residual convolutional SNNs on the MNIST and the CIFAR-10 datasets.

STDP-based learning is limited to shallow SNNs (<5 layers) yielding lower than acceptable accuracy on complex datasets. This thesis proposes block-wise complexity-aware training algorithm, referred to as BlocTrain, for incrementally training deep SNNs with reduced memory requirements using spike-based backpropagation through time. The deep network is divided into blocks, where each block consists of few convolutional layers followed by an auxiliary classifier. The blocks are trained sequentially using local errors from the respective auxiliary classifiers. Also, the deeper blocks are trained only on the hard classes determined using the class-wise accuracy obtained from the classifier of previously trained blocks. Thus, BlocTrain improves the training time and computational efficiency with increasing block depth. In addition, higher computational efficiency is obtained during inference by exiting early for easy class instances and activating the deeper blocks only for hard class instances. The ability of BlocTrain to provide improved accuracy as well as higher training and inference efficiency compared to end-to-end approaches is demonstrated for deep SNNs (up to 11 layers) on the CIFAR-10 and the CIFAR-100 datasets.

Feed-forward SNNs are typically used for static image recognition while recurrent Liquid State Machines (LSMs) have been shown to encode time-varying speech data. Liquid-SNN, consisting of input neurons sparsely connected by plastic synapses to randomly interlinked reservoir of spiking neurons (or liquid), is proposed for unsupervised speech and image recognition. The strength of the synapses interconnecting the input and liquid are trained using STDP, which makes it possible to infer the class of a test pattern without a readout layer typical in standard LSMs. The Liquid-SNN suffers from scalability challenges due to the need to primarily increase the number of neurons to enhance the accuracy. SpiLinC, composed of an ensemble of multiple liquids, where each liquid is trained on a unique input segment, is proposed as a scalable model to achieve improved accuracy. SpiLinC recognizes a test pattern by combining the spiking activity of the individual liquids, each of which identifies unique input features. As a result, SpiLinC offers comparable accuracy to Liquid-SNN with added synaptic sparsity and faster training convergence, which is validated on the digit subset of TI46 speech corpus and the MNIST dataset.

As discussed in the preceding chapter, wind resources available from nonforested, nonurban, land-based environments in the United States are more than sufficient to meet present and projected future US demand for electricity. Wind resources are comparably abundant elsewhere. As indicated in Table 10.2, a combination of onshore and offshore wind could accommodate prospective demand for electricity for all of the countries classified as top- 10 emitters of CO2. Solar energy reaching the Earth’s surface averages about 200 W m– 2 (Fig. 4.1). If this power source could be converted to electricity with an efficiency of 20%, as little as 0.1% of the land area of the United States (3% of the area of Arizona) could supply the bulk of US demand for electricity. As discussed later in this chapter, the potential source of power from the sun is significant even for sun- deprived countries such as Germany. Wind and solar energy provide potentially complementary sources of electricity in the sense that when the supply from one is low, there is a good chance that it may be offset by a higher contribution from the other. Winds blow strongest typically at night and in winter. The potential supply of energy from the sun, in contrast, is highest during the day and in summer. The source from the sun is better matched thus than wind to respond to the seasonal pattern of demand for electricity, at least for the United States (as indicated in Fig. 10.5).There are two approaches available to convert energy from the sun to electricity. The first involves using photovoltaic (PV) cells, devices in which absorption of radiation results directly in production of electricity. The second is less direct. It requires solar energy to be captured and deployed first to produce heat, with the heat used subsequently to generate steam, the steam applied then to drive a turbine. The sequence in this case is similar to that used to generate electricity in conventional coal, oil, natural gas, and nuclear- powered systems. The difference is that the energy source is light from the sun rather than a carbon- based fossil fuel or fissionable uranium.

In this chapter, the authors present a literature review for MAC, routing, and cross layer design protocols proposed for WSN. This chapter consists of three sections. In the first section, the authors discuss in depth the most well-known MAC protocols for WSN. A comparison among theses protocols will be presented. Moreover, the major advantages and disadvantages of each protocol are discussed. The routing protocols for WSN are discussed in the second section. The discussed protocols are classified into data centric routing protocols, Hierarchical routing protocols, location based protocols, and QoS aware routing protocols. Moreover, A Classification of Routing Protocols based on the Application is presented in this section. In the third section, some cross layer design protocols are discussed. A comparison among the discussed protocols according to layers integrated, intended applications, cross-layer objectives, and the evaluation approach, is presented.

This research presents a survey of energy efficient routing protocols in sensor network by categorizing into a main classification as architecture based routing. Architecture based routing is further classified into two main areas: flat or location based routing protocol, and hierarchical based routing protocols. Flat based routing is more suitable when a huge number of sensor nodes are deployed, and location based routing is employed when nodes are aware of their location. Hierarchical routing look into alternative approach by placing intermediate nodes in terms of cluster heads, gateway nodes, or mobile entities for efficient handling of energy. The survey is presented in order to highlight the advantage of hierarchical based routing, mainly the deployment of mobility routing. As not many surveys have been conducted in mobility based routing, this chapter can be helpful for looking into a new perspective and paradigm of energy efficient routing protocols.

Underwater Wireless Sensor Networks (UWSNs) are finding different applications for offshore exploration and ocean monitoring. In most of these applications, the network consists of a significant number of sensor nodes deployed at different depth levels throughout the area of interest. Sensor nodes on the sea bed cannot communicate directly with the nodes near the surface level, so they require multihop communication assisted by an appropriate routing scheme. However, this appropriateness not only depends on network resources and application requirements, but environment constraints are involved as well. These factors all provide a platform where a resource aware routing strategy plays a vital role in fulfilling different application requirements with dynamic environment conditions. Realizing this fact, much of the attention has been given to construct a reliable scheme, and many routing protocols have been proposed in order to provide efficient route discoveries between the source and sink. In this chapter, the authors present a review and comparison of different algorithms proposed recently for underwater sensor networks. Later on, all of these have been classified into different groups according to their characteristics and functionalities.

This chapter presents the studies and analysis on the approaches, the concepts, and the ideas on data packet size optimization for data packets transmission in underwater wireless sensor network (UWSN) and terrestrial wireless sensor network (TWSN) communications. These studies are based on the related prior works accomplished by the UWSN and TWSN research communities. It should be mentioned here that the bulk of the studies and analysis would be on the data packet size optimization techniques or approaches rather than on the communication channel modeling, but the channel model is deemed essential to support the optimization approaches. The various optimization solutions proposed in the prior arts are dealt with in depth to explore their feasibilities to accommodate the data packet size optimization algorithm proposed by the various researchers. This chapter starts off with the studies and analysis on prior arts found in UWSN and then moves on to the similar works found elsewhere in the TWSN communications counterparts. A comparison on some important issues related to data packet size optimization approaches used in UWSN and TWSN communications are summarized in a table at the end of this chapter. The findings in this chapter may be helpful to readers who are interested in the R&D of data packet size optimization techniques with the intention to formulate new data packet size optimization framework or algorithms.

The solar energy is able to supply humanity energy for almost another 1 billion years. Optical nano-antennas (ONAs) are an attractive technology for high efficiency, and low-cost solar cells. These devices can be classified to semiconductor nano-wires and metallic nano-antenna. Extensive studies have been carried out on ONAs to investigate their ability to harvest solar energy. Inspired by these studies, the scope of the chapter is to highlight the latest designs of the two main types of ONAs. The metallic nano-antennas are discussed based on the following points: plasmon, modeling, and performance of antenna designs using different configurations and materials. Moreover, the semiconductor nano-wires are studied thoroughly in terms of photonic crystals, antenna design with different patterns, nano-wire forms and materials. Also, the applications of ONAs and their fabrication aspects such as diode challenges are presented in detail. Finally, three novel designs of ONAs are presented and numerically simulated to maximize the harvesting efficiency.

This study examined the distributional effects of energy subsidy reduction in Kuwait. A computable general equilibrium (CGE) model was calibrated on a Kuwaiti social accounting matrix (SAM). A simulation experiment was conducted by applying a 25% energy subsidy reduction. The SAM consisted of 10 household groups, categorized into nationals and expatriates, and subsequently classified into five income levels. The employed labor force was classified into two groups (nationals and expatriates), each disaggregated by four skill levels. Industries were disaggregated into 65 branches. The CGE model was specified in such a way that it would be possible to quantify welfare effects on each household group and then trace the changes to distributional effects, factor income, and employment by industrial origins. When accompanied by compensation, the energy subsidy led to an aggregate efficiency (increase in GDP) and welfare gains. The welfare gains among Kuwaiti nationals were progressive; the lower-income groups gained more than higher-income groups.

The solar energy is able to supply humanity energy for almost another 1 billion years. Optical nano-antennas (ONAs) are an attractive technology for high efficiency, and low-cost solar cells. These devices can be classified to semiconductor nano-wires and metallic nano-antenna. Extensive studies have been carried out on ONAs to investigate their ability to harvest solar energy. Inspired by these studies, the scope of the chapter is to highlight the latest designs of the two main types of ONAs. The metallic nano-antennas are discussed based on the following points: plasmon, modeling, and performance of antenna designs using different configurations and materials. Moreover, the semiconductor nano-wires are studied thoroughly in terms of photonic crystals, antenna design with different patterns, nano-wire forms and materials. Also, the applications of ONAs and their fabrication aspects such as diode challenges are presented in detail. Finally, three novel designs of ONAs are presented and numerically simulated to maximize the harvesting efficiency.

All around the world, taking stock of buildings older than 1970, when the first energy efficiency arose, is an important one. Today, all urban agglomerations confront themselves with environmental problems generated by air pollution, cars, and buildings, vie for the first place as the highest polluters. In the future, cities will become increasingly populated, and as a result these problems will more and more affect the quality of life. A way to prevent this scenario is a gradual transition to smart cities. In this approach, smart houses will become indispensable. In order to maintain unaltered cities' specificity, the only acceptable solution is to retrofit old buildings, especially of those classified as historical monuments or as iconic buildings. By retrofitting these buildings, they could be prepared for integration in future cities.

As discussed in Chapter 3, the transportation sector accounts for approximately a third of total emissions of CO2 in the United States, with a smaller fraction but a rapidly growing total in China. Combustion of oil, either as gasoline or diesel, is primarily responsible for the transportation- related emissions of both countries. Strategies to curtail overall emissions of CO2 must include plans for a major reduction in the use of oil in the transportation sector. This could be accomplished (1) by reducing demand for trans¬portation services; (2) by increasing the energy efficiency of the sector; or (3) by transitioning to an energy system less reliant on carbon- emitting sources of energy. Assuming continuing growth in the economies of both countries, option 1 is unlikely, certainly for China. Significant success has been achieved already in the United States under option 2, prompted by the application of increasingly more stringent corporate average fuel economy (CAFE) standards. And the technological advances achieved under this program are likely to find application in China and elsewhere, given the global nature of the automobile/ truck industry. The topic for discussion in this chapter is whether switching from oil to a plant- or animal- based fuel could contribute to a significant reduction in CO2 emissions from the transportation sector of either or both countries, indeed from the globe as a whole. The question is whether plant- based ethanol can substitute for gasoline and whether additional plant- and animal- derived products can cut back on demand for diesel. The related issue is whether this substitution can contribute at acceptable social and economic cost to a net reduction in overall CO2 emissions when account is taken of the entire lifecycle for production of the nonfossil alternatives. There is an extensive history to the use of ethanol as a motor fuel. Nicolas Otto, cred¬ited with the development of the internal combustion engine, used ethanol as the energy source for one of his early vehicle inventions in 1860. Henry Ford designed his first auto¬mobile, the quadricycle, to run on pure ethanol in 1896.

With dwindling water supplies and the impacts of climate change, many cities are turning to water sources previously considered unusable. One such source for inland cities is brackish groundwater. With prolonged drought throughout Texas, cities such as El Paso, Lubbock, and San Antonio are desalinating brackish groundwater to supplement existing water sources. Similar projects are under consideration elsewhere in Texas. While brackish groundwater contains fewer total dissolved solids than seawater, desalination of brackish groundwater is still an energy-intensive process. Brackish water desalination using reverse osmosis, the most common desalination membrane treatment process, consumes 20 to 40 times more energy than traditional surface water treatment using local water sources. This additional energy consumption leads to increased carbon emissions when using fossil fuel-generated electricity. As a result of concern over greenhouse gas emissions from additional energy consumption, some desalination plants are powered by wind-generated electricity. West Texas is a prime area for desalination of brackish groundwater using wind power, since both wind and brackish groundwater resources are abundant in the area. Most of the Texas Panhandle and Plains region has wind resource potential classified as Class 3 or higher. Additionally, brackish groundwater is found at depths less than 150 m in most of west Texas. This combination of wind and brackish groundwater resources presents opportunities for the production of alternative drinking water supplies without severe carbon emissions. Additionally, since membrane treatment is not required to operate continuously, desalination matches well with variable wind power. Implementing a brackish groundwater desalination project using wind-generated electricity requires economic feasibility, in addition to the geographic availability of the two resources. Using capital and operating cost data for wind turbines and desalination membranes, we conducted a thermoeconomic analysis for three parameters: 1) transmission and transport, 2) geographic proximity, and 3) aquifer volume. Our first parameter analyzes the cost effectiveness of tradeoffs between building infrastructure to transmit wind-generated electricity to the desalination facility versus pipelines to transport brackish groundwater to the wind turbines. Secondly, we estimate the maximum distance between the wind turbines and brackish groundwater at which desalination using wind power remains economically feasible. Finally, we estimate the minimum available brackish aquifer volume necessary to make such a project profitable. Our analysis illustrates a potential drinking water option for Texas (and other parts of the world with similar conditions) using renewable energy to treat previously unusable water. Harnessing these two resources in an economically efficient manner may help reduce future strain on the energy-water nexus.

Shanghai is the largest city of elevators in the world with 165000 elevators and escalators. According to latest research, elevators typically account for about 3% to 8% of the overall electricity consumption of a building. Therefore, it is significantly to study the energy efficiency of elevators in Shanghai. However, elevators have received little attention from an efficiency perspective in the past. To recover this gap, this paper analyses classification method on energy efficiency of elevators in Shanghai and suggests policy measures for energy conservation. First, Representative elevators in Shanghai were collected as research objects; second, a new energy efficiency classification method was established on the modification of VDI4707 according to actual situations in China, then, energy consumption of these elevators were measured and classified according to the new method. Finally, the influence factors of elevator energy efficiency were studied, and suggestion on the improvement of the energy efficiency of elevators in Shanghai was given.

Early experiences with energy savings certificates (ESCs) have revealed their merits and the challenges associated with them. While in the United States ESC markets have yet to gain significant traction, lessons can be drawn from early experiences in the states of Connecticut and New York, as well as from established markets in Italy, France, and elsewhere. The staying power of European examples demonstrates that ESCs can help initiate more efficiency projects. This article compares ESCs with renewable energy certificates (RECs), looks at the unique opportunities and challenges they present, and reviews solutions and best practices demonstrated by early ESC markets. Three major potential ESC market types are also reviewed: compliance, voluntary, and carbon. Additionally, factors that will benefit ESC markets in the United States are examined: new state EEPS policies, public interest in tools to mitigate climate change, and the growing interest in a voluntary market for ESCs.

Energy consumption in the United States’ residential sector has been marked by a steady growth over the past few decades, in spite of the implementation of several energy efficiency policies. To develop effective energy policies for the residential sector, it is of utmost importance to study the various factors affecting residential energy consumption. Earlier studies have identified and classified various individual factors responsible for the increment in household energy consumption, and have also analyzed the effect of socio-economic factors such as standard-of-living and income on overall household energy consumption. This research study identifies the socio-economic factors affecting household energy consumption. Potential reasons for the variation in residential energy efficiency consumption have been investigated in previous studies that only represent viewpoints of investigators analyzing specific problems. Additionally, a comprehensive review of literature failed to reveal existing research that had systematically explored the interdependencies among the various factors that could possibly affect residential energy consumption to give an overall perspective of these factors. Widely used academic and scholarly scientific databases were employed by two independent investigators to search for original research investigations. A total of more than 200 research studies were found by the investigators, with almost ninety percent agreement between the two investigators. Based on the inclusion and exclusion criteria of this research study the authors systematically reviewed 51 prominent research studies to create a comprehensive list of factors affecting residential energy consumption. The results are discussed in this review.

The art and science of gas turbine has traditionally seen a gradual and continuous change over the past few decades. Gas turbines are classified into impulse and reaction types and further into turbojet, turbofan, turboprop, after burning turbojet and micro gas turbine. These turbines find applications in airplanes, large scale industries etc. but these are less suitable for the small scale power generation units due to several factors. Micro gas turbines are set to play a significant role particularly in small-scale power generation using combined heat and power generation among all these types of turbines as the future of power generation lies in decentralised and distributed power generation systems. In the light of making use of the high temperature exhaust of a gas turbine, combined heat and power generation systems are being used to increase the power output and overall efficiency. Micro gas turbines are essentially single-stage, single-shaft and low pressure gas turbines whose capacity ranges from 30–150 KW. In comparison to the conventional turbines, micro gas turbines are compact and have low lubricating oil consumption leading to a simpler lube and sump oil system and because they have fewer rotating parts, this leads to lesser balancing problems. The analysis of micro gas turbines has shown that they are capable of meeting current emission standards of NOx and other pollutants. Even though the installation costs of micro gas turbines are high due to the complexity in adjusting to electrical grid frequency, still these distributed energy systems may prove to be more attractive in a competitive market to those seeking increased reliability as they empower these entities with the capacity of self-generation. The following text reviews the developments in the micro gas turbines with a special focus on the efficiency of its components such as the recuperator, the combustion chamber design and also explores the future prospects of the technology in terms of viability of its application in the automobile sector.

Abstract In this paper, Computational Fluid Dynamics (CFD) is employed to investigate the heat transfer characteristics of Reverse Osmosis Concentrate (ROC) as an alternative, low-cost thermal energy storage medium. Thermal energy storage is a critical component for increasing efficiency and dispatchability of solar thermal and combined heat and power plants. The byproduct of water desalination, ROC, is classified as an industrial waste by the U.S. Environmental Protection Agency as it has negative effects on vegetation and sea-life. Currently, ROC disposal includes deep-well injection, surface discharge to rivers, discharge to the ocean, and evaporation ponds. The composition and thermal properties of ROC salt vary depending on the original source of feedwater. Transient models are utilized to understand the heat transfer between the heat transfer fluid and storage fluid (i.e., ROC) over time. This simulation also provides valuable information in determining the optimal operating conditions of the thermal energy storage system. This information will be used in conjunction with a cost analysis, focused on the transportation, processing and containment cost of the energy storage, that aims to determine the economic feasibility of ROC technology in large scale, commercial applications.

This study deals with types of micro cogeneration (or micro combined heat and power, MCHP) systems and reviews energetic and exergetic analysis of MCHP systems, which are also called building cogeneration systems. These are classified as micro and macro cogeneration systems and figured within subgroups. Previously conducted studies on exergy and energy analyses of internal combustion engines (micro turbines), external combustion engines (Ericsson engines), fuel cells (solid oxide fuel cells) and thermophotovoltaic systems are treated in this paper. The main objectives of this study are to classify MCHP systems used in building cogeneration systems, to introduce types of MCHP systems and to better define micro cogeneration systems in the light of previously conducted studies. In this regard, energetic and exergetic efficiencies of various MCHP systems are graphically obtained. Under grouping presented MCHP systems, internal combustion engines based MCHP systems are defined to be the best choice with energetic and exergetic efficiency values of 86.0% and 40.31%, respectively. Micro gas turbines and Ericson engine based micro cogeneration systems are also obtained as valuable systems with the energetic values of 75.99% and 65.97% and exergetic values of 35.8% and 38.5%, respectively. However, in this building cogeneration group, energetic and exergetic efficiencies of the thermophotovoltaic systems have 65.0% and 15.0%, respectively. It may be concluded that system choice depends on the type of the system, energy flow of the system, system parts and developments, while building, system capacity, comfort and maintenance are the other factors to be considered.

This study deals with bio-ethanol distilled from disposed alcoholic beverages. Through the various experiments while using a small displacement engine which is equipped with electric fuel injection (E.F.I.) system, the feasibility of the disposed alcoholic beverages; leftover-beer is investigated as one of the bio-mass sources. Currently bio-masses are classified into the following seven bio-mass sources, livestock excreta, sewage sludge, human waste sludge, waste of food, agricultural residue, wood-based (wood chips) bio-mass and crops. In those bio-mass sources, the authors pay their attention to the amount of leftover-beer after a banquet. Our investigation clarifies that about 12 l of beer is left and disposed after a banquet of 150 people. Since beer contains 5% alcohols, 600 cc of ethanol can be obtained without fermentation process. Thus in order to obtain alcohol as a fuel, in collaboration with some hotels, leftover-beer is collected. As to a fuel, higher concentration of distilled alcoholic beverages is preferable. Therefore a new double distillation system is developed to separate water, and 85.9% bio-ethanol fuel is produced from 5% alcoholic density of leftover-beer. The ethanol evaporation characteristic of this bio-ethanol is investigated, it is equal to 98% ethanol reagent. This showed that it can be mixed with gasoline. Also, in order to confirm its performance as a fuel, the obtained ethanol is experimented with 121 cc of small displacement engine which is equipped with E.F.I. system. The results of this experiment are compared to unleaded gasoline and showed that it has the same performance of engine power, especially in case of before top dead center (B.T.D.C.) 15.0 deg.. We also calculated the volume of CO2 emission discharged in distilled ethanol under driving conditions B.T.D.C. 15.0 deg., 4000 rpm, for 1 hour. The CO2 production of distilled ethanol is 34.4 kgCO2, on the other hand, CO2 production of unleaded gasoline is 2.82 kgCO2. This result shows that the system with high energy efficiency to separate ethanol and water is desired. Furthermore, the density of acetaldehyde from exhaust gas is analyzed. An extremely low reading of 28 ppm is obtained. The results prove the effect of acetaldehyde to the human body is negligible. Finally, employing 50 cc motorcycles with our developed E.F.I. system, experiment with bio-mass ethanol is executed. The results proved the feasibility of our developed bio-ethanol can be a new low emission bio-mass source.

Cavitation is an important and common phenomena in fluid flow in which a fluid becomes two-phase through pressure variation. In devices such as valves, orifices, and metering devices, as well as loss of coolant situations in power plants, cavitation can be of interest due to erosion, energy efficiency, safety, and other concerns. It is possible for a cavitating flow to become sonic, accelerating and imposing additional energy losses that would not have occurred had the flow remained below the speed of sound. Models of this aspect of two-phase flow have not been fully explored and often have only been developed for the case of constant area. In the present paper, the homogeneous equilibrium model is developed by applying the integral forms of the conservation of mass, momentum, and energy equations to a control volume of variable cross-sectional area with adiabatic walls. The developed model is then applied to experimental data with R-134a as the fluid of interest for an instrumented converging-diverging nozzle for which mass flow, pressure, and temperature are measured. Applying the model to the experimental data yields interesting results in both the relationship between velocity and void fraction and in the predicted shear stresses down the length of the nozzle. The model predicts negative shear stresses near the nozzle’s throat an order of magnitude higher than those seen elsewhere in the nozzle. For this reason, the homogeneous model is likely not sufficient to accurately describe this variant of cavitating flow.

Behavioural interventions are policies and programmes that incorporate insights from scientists who study human behaviour (such as psychology and behavioural economics), with the aim of encouraging socially desirable behaviours by removing barriers and creating incentives or disincentives (Cornago, 2021). Very few behavioural interventions for energy efficiency have been documented in Eastern Europe and the Western Balkans, and none in North Macedonia. The limited experience that has been documented in the region consists of a few small trials which used behavioural principles to inform households about approaches to energy conservation, but none of these trials have demonstrated a significant effect on behaviour. Behavioural interventions have been widely used elsewhere in the world, particularly in North America, Western Europe, and Australia, and there are many studies evaluating their impacts in these regions (Andor & Fels, 2018, p. 182). This report focuses primarily on household energy efficiency, and particularly on the most widespread and well-documented interventions, which are those related to providing feedback on energy consumption and labelling consumer goods. Although behavioural interventions have been shown to produce significant impacts and to be cost-effective in many situations, the available evidence has some limitations. Many examples that have been documented are small-scale trials or pilot projects; large-scale, institutionalised policy interventions based on behavioural insights are rare (Users TCP and IEA, 2020, p. 22). In many studies, experiments with small sample sizes and short durations show larger impacts than larger and longer-term studies, suggesting that pilot studies may over-estimate the savings that might be achieved by large-scale programmes (Andor & Fels, 2018, p. 182; Erhardt-Martinez et al., 2010, p. iv). The amount of energy saved by behavioural interventions is often fairly small and varies widely from one programme to another, suggesting that the effectiveness of these interventions may be highly dependent on local context and on details of design and implementation. Finally, many studies rely on participants reporting their intentions, and on hypothetical rather than actual purchasing decisions, and some studies have found a divergence between stated intentions and actual behaviour (Grünig et al., 2010, p. 41; Users TCP and IEA, 2020, pp. 75–76; Yang et al., 2015, pp. 21–22).

Feed inputs represent the largest variable cost of producing meat and milk from ruminant animals. Thus, strategies that improve the efficiency of feed utilization are needed to improve the global competitiveness of Israeli and U.S. cattle industries, and mitigate their environmental impact through reductions in nutrient excretions and greenhouse gas emissions. Implementation of innovative technologies that will enhance genetic merit for feed efficiency is arguably one of the most cost-effective strategies to meet future demands for animal-protein foods in an environmentally sustainable manner. While considerable genetic variation in feed efficiency exist within cattle populations, the expense of measuring individual-animal feed intake has precluded implementation of selection programs that target this trait. Residual feed intake (RFI) is a trait that quantifies between-animal variation in feed intake beyond that expected to meet energy requirements for maintenance and production, with efficient animals being those that eat less than expected for a given size and level of production. There remains a critical need to understand the biological drivers for genetic variation in RFI to facilitate development of effective selection programs in the future. Therefore, the aim of this project was to determine the biological basis for phenotypic variation in RFI of growing and lactating cattle, and discover metabolic biomarkers of RFI for early and more cost-effective selection of cattle for feed efficiency. Objectives were to: (1) Characterize the phenotypic relationships between RFI and production traits (growth or lactation), (2) Quantify inter-animal variation in residual HP, (3) Determine if divergent RFIphenotypes differ in HP, residual HP, recovered energy and digestibility, and (4) Determine if divergent RFI phenotypes differ in physical activity, feeding behavior traits, serum hormones and metabolites and hepatic mitochondrial traits. The major research findings from this project to date include: In lactating dairy cattle, substantial phenotypic variation in RFI was demonstrated as cows classified as having low RMEI consumed 17% less MEI than high-RMEI cows despite having similar body size and lactation productivity. Further, between-animal variation in RMEI was found to moderately associated with differences in RHP demonstrating that maintenance energy requirements contribute to observed differences in RFI. Quantifying energetic efficiency of dairy cows using RHP revealed that substantial changes occur as week of lactation advances—thus it will be critical to measure RMEI at a standardized stage of lactation. Finally, to determine RMEI in lactating dairy cows, individual DMI and production data should be collected for a minimum of 6 wk. We demonstrated that a favorably association exists between RFI in growing heifers and efficiency of forage utilization in pregnant cows. Therefore, results indicate that female progeny from parents selected for low RFI during postweaning development will also be efficient as mature females, which has positive implications for both dairy and beef cattle industries. Results from the beef cattle studies further extend our knowledge regarding the biological drivers of phenotypic variation in RFI of growing animals, and demonstrate that significant differences in feeding behavioral patterns, digestibility and heart rate exist between animals with divergent RFI. Feeding behavior traits may be an effective biomarker trait for RFI in beef and dairy cattle. There are differences in mitochondrial acceptor control and respiratory control ratios between calves with divergent RFI suggesting that variation in mitochondrial metabolism may be visible at the genome level. Multiple genes associated with mitochondrial energy processes are altered by RFI phenotype and some of these genes are associated with mitochondrial energy expenditure and major cellular pathways involved in regulation of immune responses and energy metabolism.