Stochastic techno-economic considerations in biodiesel production

Usman Abubakar, Srinivas Sriramula (Corresponding Author), Neill C Renton

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Abstract

Biodiesel production, like other engineering projects, involves critical decisions which have to be made under uncertainties stemming from a range of sources such as the inherent variation in operating conditions and market forces featuring inflation, depreciation factors, variations in equipment/production costs, etc. Although the effect of such uncertainties on front end engineering and management decisions was recognised, these have not been considered comprehensively in the literature. In this paper, for the first time, structural reliability principles are applied to determine the prospect of a process plant achieving some performance targets under uncertainties. Considering the published case of a biodiesel production plant, this paper presents a new approach for techno-economic assessment in a stochastic framework. Mean values of the economic indicators obtained through the stochastic analysis are found to be in good agreement with previously published nominal values. The stochastic techno-economic analysis approach combines First Order Reliability Method (FORM) and Monte Carlo Simulation (MCS) to offer additional performance measures which are needed by prospective investors, governments, engineers and other stakeholders to ensure plant safety and cost-efficiency.
Original languageEnglish
Pages (from-to)1–11
Number of pages11
JournalSustainable Energy Technologies and Assessments
Volume9
Early online date18 Nov 2014
DOIs
Publication statusPublished - Mar 2015

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Biodiesel
Economics
Depreciation
Economic analysis
Costs
Engineers
Uncertainty

Keywords

  • biodiesel production process
  • techno-economic analysis
  • uncertainty
  • plant performance optimization
  • stochastic modelling

Cite this

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title = "Stochastic techno-economic considerations in biodiesel production",
abstract = "Biodiesel production, like other engineering projects, involves critical decisions which have to be made under uncertainties stemming from a range of sources such as the inherent variation in operating conditions and market forces featuring inflation, depreciation factors, variations in equipment/production costs, etc. Although the effect of such uncertainties on front end engineering and management decisions was recognised, these have not been considered comprehensively in the literature. In this paper, for the first time, structural reliability principles are applied to determine the prospect of a process plant achieving some performance targets under uncertainties. Considering the published case of a biodiesel production plant, this paper presents a new approach for techno-economic assessment in a stochastic framework. Mean values of the economic indicators obtained through the stochastic analysis are found to be in good agreement with previously published nominal values. The stochastic techno-economic analysis approach combines First Order Reliability Method (FORM) and Monte Carlo Simulation (MCS) to offer additional performance measures which are needed by prospective investors, governments, engineers and other stakeholders to ensure plant safety and cost-efficiency.",
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author = "Usman Abubakar and Srinivas Sriramula and Renton, {Neill C}",
note = "The authors wish to gratefully acknowledge the financial support granted by Petroleum Technology Development Fund (PTDF), Nigeria. Sriramula’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.",
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N2 - Biodiesel production, like other engineering projects, involves critical decisions which have to be made under uncertainties stemming from a range of sources such as the inherent variation in operating conditions and market forces featuring inflation, depreciation factors, variations in equipment/production costs, etc. Although the effect of such uncertainties on front end engineering and management decisions was recognised, these have not been considered comprehensively in the literature. In this paper, for the first time, structural reliability principles are applied to determine the prospect of a process plant achieving some performance targets under uncertainties. Considering the published case of a biodiesel production plant, this paper presents a new approach for techno-economic assessment in a stochastic framework. Mean values of the economic indicators obtained through the stochastic analysis are found to be in good agreement with previously published nominal values. The stochastic techno-economic analysis approach combines First Order Reliability Method (FORM) and Monte Carlo Simulation (MCS) to offer additional performance measures which are needed by prospective investors, governments, engineers and other stakeholders to ensure plant safety and cost-efficiency.

AB - Biodiesel production, like other engineering projects, involves critical decisions which have to be made under uncertainties stemming from a range of sources such as the inherent variation in operating conditions and market forces featuring inflation, depreciation factors, variations in equipment/production costs, etc. Although the effect of such uncertainties on front end engineering and management decisions was recognised, these have not been considered comprehensively in the literature. In this paper, for the first time, structural reliability principles are applied to determine the prospect of a process plant achieving some performance targets under uncertainties. Considering the published case of a biodiesel production plant, this paper presents a new approach for techno-economic assessment in a stochastic framework. Mean values of the economic indicators obtained through the stochastic analysis are found to be in good agreement with previously published nominal values. The stochastic techno-economic analysis approach combines First Order Reliability Method (FORM) and Monte Carlo Simulation (MCS) to offer additional performance measures which are needed by prospective investors, governments, engineers and other stakeholders to ensure plant safety and cost-efficiency.

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