SFBC MIMO energy efficiency improvements of common packet schedulers for the long term evolution downlink

It is desirable that energy performance improvement is not realized at the expense of other network performance parameters. This paper investigates the trade off between energy efficiency, spectral efficiency and user QoS performance for a multi-cell multi-user radio access network. Specifically, the energy consumption ratio (ECR) and the spectral efficiency of several common frequency domain packet schedulers in a cellular E-UTRAN downlink are compared for both the SISO transmission mode and the 2x2 Alamouti Space Frequency Block Code (SFBC) MIMO transmission mode. It is well known that the 2x2 SFBC MIMO transmission mode is more spectrally efficient compared to the SISO transmission mode, however, the relationship between energy efficiency and spectral efficiency is undecided. It is shown that, for the E-UTRAN downlink with fixed transmission power, spectral efficiency improvement results into energy efficiency improvement. The effect of SFBC MIMO versus SISO on the user QoS performance is also studied. © 2011 IEEE.

A non-parametric data envelopment analysis approach for improving energy efficiency of grape production

Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production.In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming.The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts. © 2013.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

Drying processess in the United Kingdom:assessment of industrial energy utilisation and efficiency of drying systems and the modelling of drying characters using neural networks (BL)

Drying is an important unit operation in process industry. Results have suggested that the energy used for drying has increased from 12% in 1978 to 18% of the total energy used in 1990. A literature survey of previous studies regarding overall drying energy consumption has demonstrated that there is little continuity of methods and energy trends could not be established. In the ceramics, timber and paper industrial sectors specific energy consumption and energy trends have been investigated by auditing drying equipment. Ceramic products examined have included tableware, tiles, sanitaryware, electrical ceramics, plasterboard, refractories, bricks and abrasives. Data from industry has shown that drying energy has not varied significantly in the ceramics sector over the last decade, representing about 31% of the total energy consumed. Information from the timber industry has established that radical changes have occurred over the last 20 years, both in terms of equipment and energy utilisation. The energy efficiency of hardwood drying has improved by 15% since the 1970s, although no significant savings have been realised for softwood. A survey estimating the energy efficiency and operating characteristics of 192 paper dryer sections has been conducted. Drying energy was found to increase to nearly 60% of the total energy used in the early 1980s, but has fallen over the last decade, representing 23% of the total in 1993. These results have demonstrated that effective energy saving measures, such as improved pressing and heat recovery, have been successfully implemented since the 1970s. Artificial neural networks have successfully been applied to model process characteristics of microwave and convective drying of paper coated gypsum cove. Parameters modelled have included product moisture loss, core gypsum temperature and quality factors relating to paper burning and bubbling defects. Evaluation of thermal and dielectric properties have highlighted gypsum's heat sensitive characteristics in convective and electromagnetic regimes. Modelling experimental data has shown that the networks were capable of simulating drying process characteristics to a high degree of accuracy. Product weight and temperature were predicted to within 0.5% and 5C of the target data respectively. Furthermore, it was demonstrated that the underlying properties of the data could be predicted through a high level of input noise.

Economic and socio-economic evaluation of bioenergy schemes fueled with energy crops in Greece

The main aim of this thesis is to evaluate the economic and socio-economic viability of energy crops as raw material for bioenergy schemes at the local level. The case examined is Greece, a southern Mediterranean country. Based on the current state, on foreseen trends and on the information presented in the literature review (conducted at the beginning of the study), the main goal was defined as follows: To examine the evidence supporting a strong role for dedicated energy crops local bioenergy developments in Greece, a sector that is forecasted to be increasingly important in the short to medium term.' Two perennial energy crops, cardoon (Cynara cardunculus L.) and giant reed (Arundo donax L.) were evaluated. The thesis analysed their possible introduction in the agricultural system of Rhodope, northern Greece, as alternative land use, through comparative financial appraisal with the main conventional crops. Based on the output of this comparative analysis, the breakeven for the two selected energy crops was defined along with a sensitivity analysis for the risk of the potential implementation. Following, the author performed an economic and socio-economic evaluation of a district heating system fuelled with energy crops in the selected region. Finally, the author, acknowledging that bioenergy deployment should be studied in the context of innovations proceeded in examining the different perceptions of the key groups involved, farmers and potential end users. Results indicated that biomass exploitation for energy purposes is more likely to be accepted when it is seen clearly as one strand in a national energy, environmental and agricultural policy which embraces several sources of renewable energy, and which also encourages energy efficiency and conservation.

The development of a regional energy assessment model

Shropshire Energy Team initiated this study to examine consumption and associated emissions in the predominantly rural county of Shropshire. Current use of energy is not sustainable in the long term and there are various approaches to dealing with the environmental problems it creates. Energy planning by a local authority for a sustainable future requires detailed energy consumption and environmental information. This information would enable target setting and the implementation of policies designed to encourage energy efficiency improvements and exploitation of renewable energy resources. This could aid regeneration strategies by providing new employment opportunities. Associated reductions in carbon dioxide and other emissions would help to meet national and international environmental targets. In the absence of this detailed information, the objective was to develop a methodology to assess energy consumption and emissions on a regional basis from 1990 onwards for all local planning authorities. This would enable a more accurate assessment of the relevant issues, such that plans are more appropriate and longer lasting. A first comprehensive set of data has been gathered from a wide range of sources and a strong correlation was found between population and energy consumption for a variety of regions across the UK. In this case the methodology was applied to the county of Shropshire to give, for the first time, estimates of primary fuel consumption, electricity consumption and associated emissions in Shropshire for 1990 to 2025. The estimates provide a suitable baseline for assessing the potential contribution renewable energy could play in meeting electricity demand in the country and in reducing emissions. The assessment indicated that in 1990 total primary fuel consumption was 63,518,018 GJ/y increasing to 119,956,465 GJ/y by 2025. This is associated with emissions of 1,129,626 t/y of carbon in 1990 rising to 1,303,282 t/y by 2025. In 1990, 22,565,713 GJ/y of the primary fuel consumption was used for generating electricity rising to 23,478,050 GJ/y in 2025. If targets to reduce primary fuel consumption are reached, then emissions of carbon would fall to 1,042,626 by 2025, if renewable energy targets were also reached then emissions of carbon would fall to 988,638 t/y by 2025.

A heat metering system for energy management on an industrial site

Faced with a future of rising energy costs there is a need for industry to manage energy more carefully in order to meet its economic objectives. A problem besetting the growth of energy conservation in the UK is that a large proportion of energy consumption is used in a low intensive manner in organisations where they would be responsibility for energy efficiency is spread over a large number of personnel who each see only small energy costs. In relation to this problem in the non-energy intensive industrial sector, an application of an energy management technique known as monitoring and targeting (M & T) has been installed at the Whetstone site of the General Electric Company Limited in an attempt to prove it as a means for motivating line management and personnel to save energy. The objective energy saving for which the M & T was devised is very specific. During early energy conservation work at the site there had been a change from continuous to intermittent heating but the maintenance of the strategy was receiving a poor level of commitment from line management and performance was some 5% - 10% less than expected. The M & T is concerned therefore with heat for space heating for which a heat metering system was required. Metering of the site high pressure hot water system posed technical difficulties and expenditure was also limited. This led to a ‘tin-house' design being installed for a price less than the commercial equivalent. The timespan of work to achieve an operational heat metering system was 3 years which meant that energy saving results from the scheme were not observed during the study. If successful the replication potential is the larger non energy intensive sites from which some 30 PT savings could be expected in the UK.

The modelling of energy efficient drying for DSM (BL)

This thesis investigates the modelling of drying processes for the promotion of market-led Demand Side Management (DSM) as applied to the UK Public Electricity Suppliers. A review of DSM in the electricity supply industry is provided, together with a discussion of the relevant drivers supporting market-led DSM and energy services (ES). The potential opportunities for ES in a fully deregulated energy market are outlined. It is suggested that targeted industrial sector energy efficiency schemes offer significant opportunity for long term customer and supplier benefit. On a process level, industrial drying is highlighted as offering significant scope for the application of energy services. Drying is an energy-intensive process used widely throughout industry. The results of an energy survey suggest that 17.7 per cent of total UK industrial energy use derives from drying processes. Comparison with published work indicates that energy use for drying shows an increasing trend against a background of reducing overall industrial energy use. Airless drying is highlighted as offering potential energy saving and production benefits to industry. To this end, a comprehensive review of the novel airless drying technology and its background theory is made. Advantages and disadvantages of airless operation are defined and the limited market penetration of airless drying is identified, as are the key opportunities for energy saving. Limited literature has been found which details the modelling of energy use for airless drying. A review of drying theory and previous modelling work is made in an attempt to model energy consumption for drying processes. The history of drying models is presented as well as a discussion of the different approaches taken and their relative merits. The viability of deriving energy use from empirical drying data is examined. Adaptive neuro fuzzy inference systems (ANFIS) are successfully applied to the modelling of drying rates for 3 drying technologies, namely convective air, heat pump and airless drying. The ANFIS systems are then integrated into a novel energy services model for the prediction of relative drying times, energy cost and atmospheric carbon dioxide emission levels. The author believes that this work constitutes the first to use fuzzy systems for the modelling of drying performance as an energy services approach to DSM. To gain an insight into the 'real world' use of energy for drying, this thesis presents a unique first-order energy audit of every ceramic sanitaryware manufacturing site in the UK. Previously unknown patterns of energy use are highlighted. Supplementary comments on the timing and use of drying systems are also made. The limitations of such large scope energy surveys are discussed.

Planning and decision-making for energy recovery from waste at the sub-regional level

This research project has developed a novel decision support system using Geographical Information Systems and Multi Criteria Decision Analysis and used it to develop and evaluate energy-from-waste policy options. The system was validated by applying it to the UK administrative areas of Cornwall and Warwickshire. Different strategies have been defined by the size and number of the facilities, as well as the technology chosen. Using sensitivity on the results from the decision support system, it was found that key decision criteria included those affected by cost, energy efficiency, transport impacts and air/dioxin emissions. The conclusions of this work are that distributed small-scale energy-from-waste facilities score most highly overall and that scale is more important than technology design in determining overall policy impact. This project makes its primary contribution to energy-from-waste planning by its development of a Decision Support System that can be used to assist waste disposal authorities to identify preferred energy-from-waste options that have been tailored specifically to the socio-geographic characteristics of their jurisdictional areas. The project also highlights the potential of energy-from-waste policies that are seldom given enough attention to in the UK, namely those of a smaller-scale and distributed nature that often have technology designed specifically to cater for this market.

Survey and applications of standardized energy metrics to mobile networks

The energy consumption and the energy efficiency have become very important issue in optimizing the current as well as in designing the future telecommunications networks. The energy and power metrics are being introduced in order to enable assessment and comparison of the energy consumption and power efficiency of the telecommunications networks and other transmission equipment. The standardization of the energy and power metrics is a significant ongoing activity aiming to define the baseline energy and power metrics for the telecommunications systems. This article provides an up-to-date overview of the energy and power metrics being proposed by the various standardization bodies and subsequently adopted worldwide by the equipment manufacturers and the network operators. © Institut Télécom and Springer-Verlag 2012.and Springer-Verlag 2012.

Energy efficient radio access architectures for green radio:large versus small cell size deployment

In this paper new architectural approaches that improve the energy efficiency of a cellular radio access network (RAN) are investigated. The aim of the paper is to characterize both the energy consumption ratio (ECR) and the energy consumption gain (ECG) of a cellular RAN when the cell size is reduced for a given user density and service area. The paper affirms that reducing the cell size reduces the cell ECR as desired while increasing the capacity density but the overall RAN energy consumption remains unchanged. In order to trade the increase in capacity density with RAN energy consumption, without degrading the cell capacity provision, a sleep mode is introduced. In sleep mode, cells without active users are powered-off, thereby saving energy. By combining a sleep mode with a small-cell deployment architecture, the paper shows that the ECG can be increased by the factor n = (R/R) while the cell ECR continues to decrease with decreasing cell size.

Energy efficient transmission protocol for distributed source coding in sensor networks

Distributed source coding (DSC) has recently been considered as an efficient approach to data compression in wireless sensor networks (WSN). Using this coding method multiple sensor nodes compress their correlated observations without inter-node communications. Therefore energy and bandwidth can be efficiently saved. In this paper, we investigate a randombinning based DSC scheme for remote source estimation in WSN and its performance of estimated signal to distortion ratio (SDR). With the introduction of a detailed power consumption model for wireless sensor communications, we quantitatively analyze the overall network energy consumption of the DSC scheme. We further propose a novel energy-aware transmission protocol for the DSC scheme, which flexibly optimizes the DSC performance in terms of either SDR or energy consumption, by adapting the source coding and transmission parameters to the network conditions. Simulations validate the energy efficiency of the proposed adaptive transmission protocol. © 2007 IEEE.

Energy hole mitigation through cooperative transmission in wireless sensor networks

The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense.

Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.