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dc.contributor.advisorIgnacio Pérez-Arriaga.en_US
dc.contributor.authorJenkins, Jesse D. (Jesse David)en_US
dc.contributor.otherMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.date.accessioned2014-09-19T21:36:53Z
dc.date.available2014-09-19T21:36:53Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/90052
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2014.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractOngoing changes in the use and management of electricity distribution systems - including the proliferation of distributed energy resources, smart grid technologies (i.e., advanced power electronics and information and communication technologies) and active system management techniques - present new challenges for the economic regulation of electricity distribution utilities. In particular, regulators are likely to face increased uncertainty regarding the evolution of network uses and the efficient cost of network investments and maintenance, as well as an increased informational disadvantage vis-a-vis the regulated utility. These challenges are especially important for regulatory approaches that establish some share of the utility's allowed revenues ex ante (e.g., incentive regulation, also known as revenue or price cap regulation, RPI-X, performance-based regulation, or output-based regulation). This thesis proposes a novel process for establishing the allowed revenues of an electricity distribution utility and demonstrates its application as a practical solution to the imminent regulatory challenges discussed above. The proposed method is a new combination of three established regulatory tools: an engineering-based reference network model (RNM) for forward-looking benchmarking of efficient network expenditures; an incentive compatible menu of contracts to elicit accurate forecasts from the utility and create incentives for cost saving efficiency efforts; and ex post automatic adjustment mechanisms, or "delta factors," to accommodate uncertainty in the evolution of network use and minimize forecast error. Chapter 1 reviews the theoretical economic foundations of the regulation of network monopolies, identifies emerging challenges in the regulation of electricity distribution companies, and introduces the proposed regulatory method. Chapter 2 describes the simulation of a realistic, large-scale urban distribution network used to demonstrate the novel regulatory process proposed in this thesis. Chapter 3 uses the simulated distribution network to demonstrate, step-by-step, the practical implementation of the novel regulatory process, evaluates its performance, and summarizes the advantages for the economic regulation of electricity distribution utilities under increasing penetration of distributed energy resources.en_US
dc.description.statementofresponsibilityby Jesse D. Jenkins.en_US
dc.format.extent92 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleEconomic regulation of electricity distribution utilities under high penetration of distributed energy resources : applying an incentive compatible menu of contracts, reference network model and uncertainty mechanismsen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentTechnology and Policy Program
dc.identifier.oclc890140310en_US


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