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Techno-Economics Assessments

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David Walwyn
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A Scopus search of research publications using the keywords (techno-economic) AND (energy) reveals that between 1980 and 2020, nearly 6,000 articles, books, book chapter and conference proceedings (referred to collectively as academic publications) listing these two words as part of the title, abstract or as a keyword, were published, growing from about 150 in 2008 to more than 1,500 in 2020. A similar search based on levelized cost of energy (LCOE) as the indicates a growth from 4 publications in 2008 to 458 in 2020, this upward trend looking likely to continue for 2021 and onwards. The surging interest in techno-economic assessment (TEA) as a means of promoting the development of renewable energy technology has not previously been so widespread, and is partly the consequence of being able to recount a positive story. However, there remains a broader question as to whether TEA has any role in policy, and whether it has any impact of facilitating sustainability transitions. In a previous publication (Walwyn, 2020), it was argued that institutional change is only possible at the confluence of four separate preconditions, namely an escalating problem, an increasingly favourable techno-economic solution, the clear policy framework, and most importantly, coherent political support. In this presentation, the author will report on the role of TEA and LCOE in the development of policy for the support of the hydrogen economy in South Africa (Walwyn, Bertoldi and Gable, 2018). The application of TEA without a broader understanding of the socio-technical regimes is illustrated. It is argued that TEA on its own will be insufficient as a means of supporting the energy transitions. The same techniques must be used to identify weaknesses in existing socio-technical regimes and thereby develop a policy framework within which to both destabilise incumbents and gather political support.
David Walwyn
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Techno Economics of API Manufacture; A Case Study of Tenofovir Disoproxil Fumarate
David Walwyn
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Objectives To provide a set of clear guidelines to be used by gatekeepers in their evaluation of research proposals, and specifically the cost and duration estimates for each phase. Summary The information in this report arises from the conjunction of two important documents, the Project Basis Specification (PBS) and the PRTM Study. The former defines in detail the stages into which new product or process development should be divided and the deliverables for each stage. The latter provides a database of historical and cost and duration figures for each stage across a number of companies in the chemicals and plastics sector. It was noted in a recent analysis of this report, and the raw data contained therein, that the bulk of the respondents failed to derive a satisfactory return from their research and development (R&D) expenditure. However the best-in-class (BIC) admirably rewarded their R&D costs, and achieved this through strict and highly structured project management. It was concluded that setting the appropriate cost and time targets, and ensuring that these are achieved, is fundamental to making research pay. This document attempts to take the PBS one step further by providing guidelines to managers and researchers in the department for the setting of such targets. A number of fundamental constants are defined and a set of simple procedures outlined for calculating the total affordable research cost, the project burn rate, project staffing levels and stage duration. The figures are provided in both USD and SAR. It is noted that a similar approach can be applied to process support projects. An Excel spreadsheet that calculates the required parameters for both process and product R&D on the basis of total revenue and project phase, is also described and is available from the author. Finally, it is intended that this report be the first part of a sequel of two reports dealing with gatekeeping, project management and project evaluation. The final report will cover the calculation of project risk, and hence the required return, on the basis of historical volatility and the Capital Asset Pricing Model.
David Walwyn
added 2 research items
The equations for the derivation of a measured and calculated oxygen transfer coefficient are briefly described. It is then shown how an on-line comparison of these two values can be used to obtain process information for run optimisation, instrument fault detection, overdosing of reagents such as antifoam and irregular changes of broth rheology. A single example showing the unambiguous detection of fouling on a dissolved oxygen probe is finally presented and discussed.
The equations for the derivation of a measured and calculated oxygen transfer coefficient are briefly described. It is then shown how an on-line comparison of these two values can be used to obtain process information for run optimisation, instrument fault detection, overdosing of reagents such as antifoam and irregular changes of broth rheology. A single example showing the unambiguous detection of fouling on a dissolved oxygen probe is finally presented and discussed.
David Walwyn
added 2 research items
Copyright: 2002 Industrial Research Institute Inc Risk management practices in the R&D departments of many chemical and pharmaceutical companies lack much of the rigor and sophistication of the equivalent corporation in the financial sector. For instance investment decisions on research projects are guided by techno-economic indicators that do not reflect changes in the financial framework of the project such as the prevailing interest rate structure, or the risk of “project default” as a result of termination. Although much has been achieved over the last ten years in improving the returns from R&D through the implementation of quality assurance processes such as the stage-gate methodology, considerable potential still exists for improving the management of investment risk and ensuring a return for shareholders. The Jarrow and Turnbull model for credit-risky bond pricing can help to calculate the internal rate of return (IRR) spread or hurdle rate that should be applied at each stage research project.