Energy conversion assessment of vacuum, slow and fast pyrolysis processes for low and high ash paper waste sludge

The performance of vacuum, slow and fast pyrolysis processes to transfer energy from the paper waste sludge (PWS) to liquid and solid products was compared. Paper waste sludges with low and high ash content (8.5 and 46.7 wt.%) were converted under optimised conditions for temperature and pellet size to maximise both product yields and energy content. Comparison of the gross energy conversions, as a combination of the bio-oil/tarry phase and char (ECsum), revealed that the fast pyrolysis performance was between 18.5% and 20.1% higher for the low ash PWS, and 18.4% and 36.5% higher for high ash PWS, when compared to the slow and vacuum pyrolysis processes respectively. For both PWSs, this finding was mainly attributed to higher production of condensable organic compounds and lower water yields during FP. The low ash PWS chars, fast pyrolysis bio-oils and vacuum pyrolysis tarry phase products had high calorific values (∼18-23 MJ kg-1) making them promising for energy applications. Considering the low calorific values of the chars from alternative pyrolysis processes (∼4-7 MJ kg-1), the high ash PWS should rather be converted to fast pyrolysis bio-oil to maximise the recovery of usable energy products.

On the role of surface roughness in the aerodynamic performance and energy conversion of horizontal wind turbine blades:a review

Summary: Renewable energy is one of the main pillars of sustainable development, especially in developing economies. Increasing energy demand and the limitation of fossil fuel reserves make the use of renewable energy essential for sustainable development. Wind energy is considered to be one of the most important resources of renewable energy. In North African countries, such as Egypt, wind energy has an enormous potential; however, it faces quite a number of technical challenges related to the performance of wind turbines in the Saharan environment. Seasonal sand storms affect the performance of wind turbines in many ways, one of which is increasing the wind turbine aerodynamic resistance through the increase of blade surface roughness. The power loss because of blade surface deterioration is significant in wind turbines. The surface roughness of wind turbine blades deteriorates because of several environmental conditions such as ice or sand. This paper is the first review on the topic of surface roughness effects on the performance of horizontal-axis wind turbines. The review covers the numerical simulation and experimental studies as well as discussing the present research trends to develop a roadmap for better understanding and improvement of wind turbine performance in deleterious environments.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Energy saving and solar electricity in fan-ventilated greenhouses

Greenhouse cultivation is an energy intensive process therefore it is worthwhile to introduce energy saving measures and alternative energy sources. Here we show that there is scope for energy saving in fan ventilated greenhouses. Measurements of electricity usage as a function of fan speed have been performed for two models of 1.25 m diameter greenhouse fans and compared to theoretical values. Reducing the speed can cut the energy usage per volume of air moved by more than 70%. To minimize the capital cost of low-speed operation, a cooled greenhouse has been built in which the fan speed responds to sunlight such that full speed is reached only around noon. The energy saving is about 40% compared to constant speed operation. Direct operation of fans from solar-photovoltaic modules is also viable as shown from experiments with a fan driven by a brushless DC motor. On comparing the Net Present Value costs of the different systems over a 10 year amortization period (with and without a carbon tax to represent environmental costs) we find that sunlight-controlled system saves money under all assumptions about taxation and discount rates. The solar-powered system, however, is only profitable for very low discount rates, due to the high initial capital costs. Nonetheless this system could be of interest for its reliability in developing countries where mains electricity is intermittent. We recommend that greenhouse fan manufacturers improve the availability of energy-saving designs such as those described here.

Pyrolysis of contaminated energy crops and the characterisation of the gained biochar

The simultaneous use of willow as a vegetation filter and an energy crop can respond both to the increasing energy demand and to the problem of the soil and water contamination. Its characteristics guarantee that the resources are used economically. As a vegetation filter, willow uptakes organic and inorganic contaminants. As a fast growing energy crop it meets the requirements of rural areas without the exploitation of existing forestry. The aim of the research was to gather knowledge on the thermal behaviour of willow, uptaking contaminants and then used as an energy crop. For this reason pyrolysis experiments were performed in two different scales. In analytical scale metal-contaminated wood was investigated and bench scale pyrolysis experiments were performed with nitrogen-enriched willow, originated from a wastewater treatment plant. Results of the pyrolysis showed that 51-81 % of the wastewater derived nitrogen of willow was captured in the char product. Char had low surface area (1.4 to 5.4 m2/g), low bulk density (0.15–0.18 g/cm3), high pH values (7.8–9.4) and high water-holding capacity (1.8 to 4.3 cm3/g) while the bioavailability of char nutrients was low. Links were also established between the pyrolysis temperature and the product properties for maximising the biochar provided benefits for soil applications. Results also showed that the metal binding capacity of wood varied from one metal ion to another, char yield increased and levoglucosan yield decreased in their presence. While char yield was mainly affected by the concentration of the metal ions, levoglucosan yield was more dependent on the type of the ionic species. Combustion experiments were also carried out with metal-enriched char. The burnout temperatures, estimated ignition indices and the conversion indicate that the metal ions type and not the amount were the determining factors during the combustion. Results presented in the Thesis provide better understanding on the thermal behaviour of nitrogen-enriched and metal contaminated biomass which is crucial to design effective pyrolysis units and combustors. These findings are relevant for pyrolysis experiments, where the goal is to yield char for energetic or soil applications.

Bio-based chemicals from biorefining:carbohydrate conversion and utilisation

The quest for sustainable sources of fuels and chemicals to meet the demands of a rapidly rising global population represents one of this century's grand challenges. Biomass offers the most readily implemented, and low cost, solution for transportation fuels, and the only non-petroleum route to organic molecules for the manufacture of bulk, fine and speciality chemicals and polymers. Chemical processing of such biomass-derived building blocks requires catalysts compatible with hydrophilic, bulky substrates to facilitate the selective deoxygenation of highly functional bio-molecules to their target products. This chapter addresses the challenges associated with carbohydrate utilisation as a sustainable feedstock, highlighting innovations in catalyst and process design that are needed to deliver high-value chemicals from biomass-derived building blocks. © 2014 Woodhead Publishing Limited. All rights reserved.

Surface plasmon resonance-induced photocatalysis by Au nanoparticles decorated mesoporous g-C3N4 nanosheets under direct sunlight irradiation

In recent years, surface plasmon-induced photocatalytic materials with tunable mesoporous framework have attracted considerable attention in energy conversion and environmental remediation. Herein we report a novel Au nanoparticles decorated mesoporous graphitic carbon nitride (Au/mp-g-C3N4) nanosheets via a template-free and green in situ photo-reduction method. The synthesized Au/mp-g-C3N4 nanosheets exhibit a strong absorption edge in visible and near-IR region owing to the surface plasmon resonance effect of Au nanoparticles. More attractively, Au/mp-g-C3N4 exhibited much higher photocatalytic activity than that of pure mesoporous and bulk g-C3N4 for the degradation of rhodamine B under sunlight irradiation. Furthermore, the photocurrent and photoluminescence studies demonstrated that the deposition of Au nanoparticles on the surface of mesoporous g-C3N4 could effectively inhibit the recombination of photogenerated charge carriers leading to the enhanced photocatalytic activity. More importantly, the synthesized Au/mp-g-C3N4 nanosheets possess high reusability. Hence, Au/mp-g-C3N4 could be promising photoactive material for energy and environmental applications.

New integrated multilevel converter for switched reluctance motor drives in plug-in hybrid electric vehicles with flexible energy conversion

This paper presents an integrated multilevel converter of switched reluctance motors (SRMs) fed by a modular front-end circuit for plug-in hybrid electric vehicle (PHEV) applications. Several operating modes can be achieved by changing the on-off states of the switches in the front-end circuit. In generator driving mode, the battery bank is employed to elevate the phase voltage for fast excitation and demagnetization. In battery driving mode, the converter is reconfigured as a four-level converter, and the capacitor is used as an additional charge capacitor to produce multilevel voltage outputs, which enhances the torque capability. The operating modes of the proposed drive are explained and the phase current and voltage are analyzed in details. The battery charging is naturally achieved by the demagnetization current in motoring mode and by the regenerative current in braking mode. Moreover, the battery can be charged by the external AC source or generator through the proposed converter when the vehicle is in standstill condition. The SRM-based PHEV can operate at different speeds by coordinating the power flow between the generator and battery. Simulation in MATLAB/Simulink and experiments on a three-phase 12/8 SRM confirm the effectiveness of the proposed converter topology.

Eigen-Adaptation and Distributed Representation of 2-D Phase, Energy, Scale and Orientation in Spatial Vision

Distributed representations (DR) of cortical channels are pervasive in models of spatio-temporal vision. A central idea that underpins current innovations of DR stems from the extension of 1-D phase into 2-D images. Neurophysiological evidence, however, provides tenuous support for a quadrature representation in the visual cortex, since even phase visual units are associated with broader orientation tuning than odd phase visual units (J.Neurophys.,88,455–463, 2002). We demonstrate that the application of the steering theorems to a 2-D definition of phase afforded by the Riesz Transform (IEEE Trans. Sig. Proc., 49, 3136–3144), to include a Scale Transform, allows one to smoothly interpolate across 2-D phase and pass from circularly symmetric to orientation tuned visual units, and from more narrowly tuned odd symmetric units to even ones. Steering across 2-D phase and scale can be orthogonalized via a linearizing transformation. Using the tiltafter effect as an example, we argue that effects of visual adaptation can be better explained by via an orthogonal rather than channel specific representation of visual units. This is because of the ability to explicitly account for isotropic and cross-orientation adaptation effect from the orthogonal representation from which both direct and indirect tilt after-effects can be explained.

Direct cavity assessment and mode optimisation technique for DFB fibre laser

A technique for direct real-time assessment of a distributed feedback fibre laser cavity conditions during operation is demonstrated and used to provide a cavity mode conditioning feedback mechanism to optimise output performance. Negligible wavelength drift is demonstrated over a 52 mW pump power range.

All-optical TDM to WDM signal conversion and partial regeneration using XPM with triangular pulses

We propose a new all-optical, all-fibre scheme for conversion of time-division multiplexed to wavelength-division multiplexed signals using cross-phase modulation with triangular pulses. Partial signal regeneration using this technique is also demonstrated.

Parasitic infections and storage iron deficiency in children in improverished regions of Mauritius

Using a combination of techniques including relative deprivation index developed by the Government, school performance, household survey and drawing of lots, a sample frame constituting of poverty areas of Mauritius was constructed and four test areas identified. Relevant haematological, parasitological and biochemical parameters of all school-going children living in the four test areas were determined so as to study the possibility of correlation between parasitic infections, plasma ferritin, haemoglobin concentration, white blood cells count, packed cells volume and blood group. It was found that there is a negative correlation between the number of parasites and haemoglobin concentration, packed cells volume of blood and degree of infestation, number of parasites and ferritin and number of parasites and age of subject. It has also been found that, children with blood group 'A' and blood group '0' tend to harbour the most parasites. As regards to storage iron depletion, this is significant only with hookworm infestation. Additionally it has been noted that hookworm infestation is directly related to age contrary to other parasitic infestations.

Capture and storage of respiratory test data

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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.

EEC energy policy and the UK:the Birmingham energy model

This paper examines the implications of the EEC common energy policy for the UK energy sector as represented by a long-term programming model. The model suggests that the UK will be a substantial net exporter of energy in 1985 and will therefore make an important contribution towards the EEC's efforts to meet its import dependency target of 50% or less of gross inland consumption. Furthermore, the UK energy sector could operate within the 1985 EEC energy policy constraints with relatively low extra cost up to the year 2020 (the end of the period covered by the model). The main effect of the constraints would be to bring forward the production of synthetic gas and oil from coal.