Decision Analysis and Policy Formulation for Technology-Specific Renewable Energy Targets
1 online resource (229 pages) : PDF
University of North Carolina at Charlotte
This study establishes a decision making procedure using Analytic Hierarchy Process (AHP) for a U.S. national renewable portfolio standard, and proposes technology-specific targets for renewable electricity generation for the country. The study prioritizes renewable energy alternatives based on a multi-perspective view: from the public, policy makers, and investors’ points-of-view, and uses multiple criteria for ranking the alternatives to generate a unified prioritization scheme. During this process, it considers a ‘quadruple bottom-line’ approach (4P), i.e. reflecting technical "progress", social "people", economic ‘profits", and environmental "planet" factors. The AHP results indicated that electricity generation from solar PV ranked highest, and biomass energy ranked lowest. A "Benefits/Cost Incentives/Mandates" (BCIM) model was developed to identify where mandates are needed, and where incentives would instead be required to bring down costs for technologies that have potential for profitable deployment. The BCIM model balances the development of less mature renewable energy technologies, without the potential for rising near-term electricity rates for consumers. It also ensures that recommended policies do not lead to growth of just one type of technology – the "highest-benefit, least-cost" technology. The model indicated that mandates would be suited for solar PV, and incentives generally for geothermal and concentrated solar power. Development for biomass energy, as a "low-cost, low-benefits" alternative was recommended at a local rather than national level, mainly due to its low resource potential values. Further, biomass energy generated from wastewater treatment plants (WWTPs) had the least resource potential compared to other biomass sources. The research developed methodologies and recommendations for biogas electricity targets at WWTPs, to take advantage of the waste-to-energy opportunities.
AHPANALYTIC HIERARCHY PROCESSENERGY POLICYENERGY PORTFOLIOENERGY PRIORITIZATIONRENEWABLE ENERGY
Infrastructure & Environmental Systems
Wu, JyDiemer, JohnMalinowski, PatriciaMunir, Mariya
Thesis (Ph.D.)--University of North Carolina at Charlotte, 2017.
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