Multi criteria analysis in the renewable energy industry by Jose Ramón San Cristóbal Mateo

By Jose Ramón San Cristóbal Mateo

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H. Rogers, D. A. Belluck, and A. Meyer (2006). ” Risk Analysis 26(1): 61–78. 5 MAUT This chapter will build upon the problem setup from the previous two chapters involving both the New York–New Jersey Harbor and the Cocheco River dredging projects. While the projects are generally similar, the differences in alternatives and criteria between the two will show how different situations can play out. MAUT (or Multi-Attribute Utility Theory) will be applied to both cases. MAUT converts the preferences of stakeholders and the performance of alternatives into a utility (or value) score that aggregates the criteria used to assess the various alternatives proposed.

And S. J. Masten (2009). Principles of Environmental Engineering and Science. Boston, McGraw-Hill. Fargo, T. R. and D. B. Truslow (2005). Cocheco River Watershed Environmental Quality Report. Rye, NH. Institution of Civil Engineers (2004). International Conference on Maintenance Dredging II. London, Thomas Telford Publishing. Problem Formulation and MCDA Model 31 Kiker, G. , T. S. Bridges, and J. Kim (2008). ” Human and Ecological Risk Assessment 14(3): 495–511. Librizzi, W. J. (1997). Regulatory Implications to Successful Dredging Program.

The project, the slices would represent the amount of the overall importance given to a specific criterion. In this case, participants would be asked to give each criterion a percentage that indicates its importance, while the sum of the percentages across all criteria must equal 100%. 1 This GUI from DECERNS shows the direct weighting of criteria. 1 captures ~10% of the overall importance). , Estimated Fish COC is more important than Impacted Area). parameters by which alternatives are judged are present in the criteria.

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