A hybrid approach to prioritize risk mitigation strategies for biomass polygeneration systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F20%3APU134702" target="_blank" >RIV/00216305:26210/20:PU134702 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1364032119308846" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1364032119308846</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rser.2019.109679" target="_blank" >10.1016/j.rser.2019.109679</a>
Alternative languages
Result language
angličtina
Original language name
A hybrid approach to prioritize risk mitigation strategies for biomass polygeneration systems
Original language description
Biomass polygeneration system is one of the most attractive biomass technologies due to its technicality, feasibility and high associated investment returns. The synthesis, design and economic aspects of constructing a processing system using this technology are well-developed and have recently reached the stage of industrial implementation. Nonetheless, the early stage of technology development focuses on process and product safety and tends to ignore other risk aspects that are closely associated with the biomass value chain. Due to the complex nature of the biomass value chain, conventional risk mitigation strategies are ineffective in mitigating risks at the management level. More recent approaches, particularly stochastic programming methods, have yielded robust results in addressing technological risks and design uncertainties. However, such approaches are still unable to effectively consider non-quantitative risks such as business risks and regulatory risks. Hence, this study proposes a combined method of an analytical model and stochastic programming approach to prioritize risks and risk mitigation strategies for decision-making purposes. This work presents a novel multiple-criteria decision-making expert system based on fuzzy set theory, which is the Decision and Evaluation-based Fuzzy Analytic Network Process (DEFANP) method. The novel method functions to prioritize risk mitigation strategies within a network relationship of project goals, key components of the biomass industry and industrial stakeholders. As the stochastic risk mitigation counterpart, the fluctuations and uncertainties in operations, transportation, market supply-demand and price are modeled using the Monte Carlo simulation method. From this, risks of implementing biomass polygeneration systems can be mitigated by selecting a strategy that yields the highest analytical indicator while reconciling with the corresponding probabilities of achieving management goals. A palm biomass polygenera
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20704 - Energy and fuels
Result continuities
Project
<a href="/en/project/EF16_026%2F0008413" target="_blank" >EF16_026/0008413: Strategic Partnership for Environmental Technologies and Energy Production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
ISSN
1364-0321
e-ISSN
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Volume of the periodical
121
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
27
Pages from-to
109679-109784
UT code for WoS article
000512410200015
EID of the result in the Scopus database
2-s2.0-85077315115