A decision model for prioritizing geographic regions for cellulosic renewable energy - Majid Azizi (Taylor & Francis Group, 2016)
This paper proposes a decision model for prioritizing geographic provinces in Iran to produce renewable energy from cellulosic materials by applying the Analytic Network Process (ANP). Biomass (forest residues, agricultural waste and wood) is a cellulosic material that can be used to produce thermal energy, electricity, and transportation fuels. The abundance, renewability, versatility, and carbon-neutrality make biomass a suitable feedstock for energy applications, and as an alternative for fossil fuels. Nine provinces in Iran are considered as possible locations for establishing renewable energy units. The ANP is used to synthesize and analyze the model. In different situations, all the decisions were affected by external factors; hence, the value-weighted competency model (benefits, costs, opportunities and risks) is calculated in the first stage with the influence of external factors on the competency model. Hierarchical designs of decisions are made for each of the competencies and their subsets. Paired comparison matrices associated with the degree of importance of each of the competencies were achieved in the second stage. In the final stage, subsets of competencies’ weighting values and their sub-options are identified through combination of the competencies and the best location is obtained. Finally, a sensitivity analysis of the model is performed and evaluated.