Use of Multi-Criteria Decision Analysis for Energy Planning
dc.contributor.author | Chawla, Kiran | |
dc.contributor.advisor | Miller, Shelie | |
dc.date.accessioned | 2015-04-22T13:21:44Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2015-04-22T13:21:44Z | |
dc.date.issued | 2015-05 | |
dc.date.submitted | 2015-04 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/110992 | |
dc.description.abstract | This paper uses a Multi-Criteria Decision Analysis (MCDA) to examine tradeoffs in electricity generation technologies on the basis of cost, greenhouse gas emissions, water consumption, and land use. Using a life cycle basis, the analysis compares electricity produced from coal, natural gas, nuclear energy, hydropower, solar energy via photovoltaics, solar energy via concentrating solar technology, onshore wind, offshore wind, geothermal energy and biomass. Attributional life-cycle analysis values for overall water consumption and greenhouse gas emissions associated with each generation technology are used, along with the levelized cost of electricity and levelized avoided cost of electricity’ as metrics for cost, and generation weighted land-use efficiency values for evaluation of land-footprint. Two objective scoring methods are used to determine whether scoring methodology influences the results of the MCDA. The results are consistent under the two scoring schemes, indicating that the results are robust to different objective methods of evaluation under an MCDA framework. Different weighting alternatives for determining the relative importance of the four objective functions are also considered to determine the sensitivity of the results to stakeholder preferences. If a heavy emphasis was given to costs, geothermal energy tends to dominate because of its lowest levelized cost of electricity. On the other hand, when a low weights is given to costs, wind power and nuclear energy emerge superior under a number of weighting schemes. Lastly, the results from the MCDA methods are compared to a Benefit Cost Analysis (BCA) to test for consistency, and it is found that the optimal solutions are different under the latter due to the high weights that are implicitly given to costs under a BCA. Even after a price on greenhouse gas emissions is factored into the BCA, it favors the technologies with a low levelized cost over ones that have lower greenhouse gas emissions, demonstrating that an MCDA is better at explicitly recognizing tradeoffs and incorporating stakeholder preferences into decision making. Thus, the suitability of MCDA for making more informed, context specific decisions is discussed, and the merits offered by an MCDA in contrast to a BCA are presented. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | energy | en_US |
dc.subject | multi-criteria decision analysis | en_US |
dc.subject | benefit cost analysis | en_US |
dc.title | Use of Multi-Criteria Decision Analysis for Energy Planning | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | Master of Science (MS) | en_US |
dc.description.thesisdegreediscipline | Natural Resources and Environment | en_US |
dc.description.thesisdegreegrantor | University of Michigan | en_US |
dc.contributor.committeemember | Johnson, Jeremiah | |
dc.identifier.uniqname | kchawla | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/110992/1/KiranChawla_Thesis_MCDAinEnergyPlanning_2015.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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