Application of stochastic analytic hierarchy process for evaluating algal cultivation systems for sustainable biofuel production

Springer Science and Business Media LLC - Tập 18 - Trang 1281-1294 - 2015
Aristotle T. Ubando1,2, Joel L. Cuello3, Mahmoud M. El-Halwagi4, Alvin B. Culaba1,2, Michael Angelo B. Promentilla5,2, Raymond R. Tan5,2
1Mechanical Engineering Department, De La Salle University, 0922 Manila, Philippines
2Center for Engineering and Sustainable Development Research (CESDR), De La Salle University, 0922 Manila, Philippines
3Department of Agricultural and Biosystems Engineering, The University of Arizona, Tucson, USA
4The Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, USA
5Chemical Engineering Department, De La Salle University, 0922 Manila, Philippines

Tóm tắt

Algal biomass is considered as a promising source of alternative fuel energy given its high yield per land area and other potential benefits. Categorized as an advanced generation biofuel feedstock, microalgae are grown in non-conventional ways through different cultivation systems. A preference of a cultivation system may vary depending on a given scenario and its inherent configuration (strength and weakness). Hence, the usage of a specific cultivation system to sustainably produce algal biofuels depends on various factors. Thus, a multi-criteria approach based on analytic hierarchy process (AHP) is proposed for evaluating alternative cultivation systems for sustainable production of algal biofuels. The main criteria considered to evaluate the alternatives based on consultation with a panel of expert and from literature are environmental impact, energy consumption, economic viability, social acceptability, and system robustness. Sub-criteria were identified under each main criterion to further qualify the analysis into relevant sub-factors in the sustainable production of algal biofuels. Three cultivations systems were used as an example to demonstrate the developed decision model using qualitative data and quantitative data. Probabilistic scenarios were analyzed using stochastic approach via Monte Carlo simulation. The results of the stochastic-based AHP showed which cultivation system is preferred for conservative (risk-averse) and optimistic (risk-inclined) scenarios.

Tài liệu tham khảo

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