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.

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.

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.

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.

Carnosine:can understanding its actions on energy metabolism and protein homeostasis inform its therapeutic potential?

The dipeptide carnosine (β-alanyl-L-histidine) has contrasting but beneficial effects on cellular activity. It delays cellular senescence and rejuvenates cultured senescent mammalian cells. However, it also inhibits the growth of cultured tumour cells. Based on studies in several organisms, we speculate that carnosine exerts these apparently opposing actions by affecting energy metabolism and/or protein homeostasis (proteostasis). Specific effects on energy metabolism include the dipeptide's influence on cellular ATP concentrations. Carnosine's ability to reduce the formation of altered proteins (typically adducts of methylglyoxal) and enhance proteolysis of aberrant polypeptides is indicative of its influence on proteostasis. Furthermore these dual actions might provide a rationale for the use of carnosine in the treatment or prevention of diverse age-related conditions where energy metabolism or proteostasis are compromised. These include cancer, Alzheimer's disease, Parkinson's disease and the complications of type-2 diabetes (nephropathy, cataracts, stroke and pain), which might all benefit from knowledge of carnosine's mode of action on human cells. © 2013 Hipkiss et al.; licensee Chemistry Central Ltd.

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.

A study of the behaviour of the single phase induction type energy meter and the design of an instrumentation system for its calibration

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

A review of the effects of distributed energy resources and power-electronic controlled loading on distribution network stability

This paper looks at potential distribution network stability problems under the Smart Grid scenario. This is to consider distributed energy resources (DERs) e.g. renewable power generations and intelligent loads with power-electronic controlled converters. The background of this topic is introduced and potential problems are defined from conventional power system stability and power electronic system stability theories. Challenges are identified with possible solutions from steady-state limits, small-signal, and large-signal stability indexes and criteria. Parallel computation techniques might be included for simulation or simplification approaches are required for a largescale distribution network analysis.

Vortex-density fluctuations, energy spectra, and vortical regions in superfluid turbulence

Measurements of the energy spectrum and of the vortex-density fluctuation spectrum in superfluid turbulence seem to contradict each other. Using a numerical model, we show that at each instance of time the total vortex line density can be decomposed into two parts: one formed by metastable bundles of coherent vortices, and one in which the vortices are randomly oriented. We show that the former is responsible for the observed Kolmogorov energy spectrum, and the latter for the spectrum of the vortex line density fluctuations.

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.