Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.

Prediction of Klason lignin and lignin thermal degradation products by Py-GC/MS in a collection of Lolium and Festuca grasses

A rapid method for the analysis of biomass feedstocks was established to identify the quality of the pyrolysis products likely to impact on bio-oil production. A total of 15 Lolium and Festuca grasses known to exhibit a range of Klason lignin contents were analysed by pyroprobe-GC/MS (Py-GC/MS) to determine the composition of the thermal degradation products of lignin. The identification of key marker compounds which are the derivatives of the three major lignin subunits (G, H, and S) allowed pyroprobe-GC/MS to be statistically correlated to the Klason lignin content of the biomass using the partial least-square method to produce a calibration model. Data from this multivariate modelling procedure was then applied to identify likely "key marker" ions representative of the lignin subunits from the mass spectral data. The combined total abundance of the identified key markers for the lignin subunits exhibited a linear relationship with the Klason lignin content. In addition the effect of alkali metal concentration on optimum pyrolysis characteristics was also examined. Washing of the grass samples removed approximately 70% of the metals and changed the characteristics of the thermal degradation process and products. Overall the data indicate that both the organic and inorganic specification of the biofuel impacts on the pyrolysis process and that pyroprobe-GC/MS is a suitable analytical technique to asses lignin composition. © 2007 Elsevier B.V. All rights reserved.

A comparative study on the pyrolysis of metal- and ash-enriched wood and the combustion properties of the gained char

This study aims to investigate the pyrolysis behaviour of metal-contaminated wood and the combustion properties of char derived from wood pyrolysis. Seven metals (Na, Mg, Ca, Zn, Cd, Pb and Fe(III)) were introduced to willow in cation form by ion-exchange and the thermal behaviour of demineralised samples and samples with additional ash were also investigated. The results show that the char yield increased from 21% to 24-28% and levoglucosan yield in vapour phase decreased from 88% to 62-29% after the addition of inorganic compounds, even though the metal binding capacity of wood varied from one metal ion to another. While char yield seems to be effected mainly by the concentration of the metal ions, levoglucosan yield was more dependent on the ionic species especially when sodium ions were present. When combustion experiments were carried out with char made of the metal enriched wood, two consecutive steps were observed, both effected by the presence of inorganic compounds. The first step was identified as the release and combustion of volatiles, while the second peak of the burning profile is the actual combustion of the fixed carbon. The burnout temperatures, estimated ignition indices and the conversion indicate that the type and not the amount of metal ions were the determining factors during the second step of combustion. © 2012 Published by Elsevier B.V.

Reflection and reflexivity in reviewing and evaluating CDIO:an empirical approach to evaluation

Facilitated by an Engineer and a Social Scientist, both of whom have expertise in Engineering Education Research and Evaluation (EERE), this interactive workshop is divided into three main sections, each one focusing on a different area of evaluation. It will build on research conducted at Aston University School of Engineering and Applied Science to explore and critique the value of introducing CDIO across the first year undergraduate curriculum. Participants will be invited to consider the pedagogical and engineering related challenges of evaluating the academic and practical value of CDIO as a strategy for learning and teaching in the discipline. An empirical approach to evaluation developed by the researchers to provide empirically grounded evidence of the pedagogical and vocational value of CDIO will form the theoretical and conceptual basis of the workshop. This approach is distinctive in that it encapsulates both engineering and social science methods of evaluation. It is also contemporaneous in nature, with the researchers acting as a ‘fly on the wall’ capturing data as the programme unfolds. Through facilitated discussion and participation, the workshop will provide colleagues with the opportunity to develop a cross-disciplinary, empirically grounded research proposal specifically for the purposes of critically evaluating CDIO. It is anticipated that during the workshop, colleagues will work together in small groups. Suitable pedagogical approaches and tools will be suggested and a purposefully developed Engineering Education Research Guide, written by the workshop facilitators, will be given to all participants to inform and support the Workshop approach.

Uncatalysed and potassium-catalysed pyrolysis of the cell-wall constituents of biomass and their model compounds

Cell-wall components (cellulose, hemicellulose (oat spelt xylan), lignin (Organosolv)), and model compounds (levoglucosan (an intermediate product of cellulose decomposition) and chlorogenic acid (structurally similar to lignin polymer units)) have been investigated to probe in detail the influence of potassium on their pyrolysis behaviours as well as their uncatalysed decomposition reaction. Cellulose and lignin were pretreated to remove salts and metals by hydrochloric acid, and this dematerialized sample was impregnated with 1% of potassium as potassium acetate. Levoglucosan, xylan and chlorogenic acid were mixed with CHCOOK to introduce 1% K. Characterisation was performed using thermogravimetric analysis (TGA) and differential thermal analysis (DTA). In addition to the TGA pyrolysis, pyrolysis-gas chromatography-mass spectrometry (PY-GC-MS) analysis was introduced to examine reaction products. Potassium-catalysed pyrolysis has a huge influence on the char formation stage and increases the char yields considerably (from 7.7% for raw cellulose to 27.7% for potassium impregnated cellulose; from 5.7% for raw levoglucosan to 20.8% for levoglucosan with CHCOOK added). Major changes in the pyrolytic decomposition pathways were observed for cellulose, levoglucosan and chlorogenic acid. The results for cellulose and levoglucosan are consistent with a base catalysed route in the presence of the potassium salt which promotes complete decomposition of glucosidic units by a heterolytic mechanism and favours its direct depolymerization and fragmentation to low molecular weight components (e.g. acetic acid, formic acid, glyoxal, hydroxyacetaldehyde and acetol). Base catalysed polymerization reactions increase the char yield. Potassium-catalysed lignin pyrolysis is very significant: the temperature of maximum conversion in pyrolysis shifts to lower temperature by 70 K and catalysed polymerization reactions increase the char yield from 37% to 51%. A similar trend is observed for the model compound, chlorogenic acid. The addition of potassium does not produce a dramatic change in the tar product distribution, although its addition to chlorogenic acid promoted the generation of cyclohexane and phenol derivatives. Postulated thermal decomposition schemes for chlorogenic acid are presented. © 2008 Elsevier B.V. All rights reserved.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.