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dc.contributor.authorDavidson, Michael R.
dc.contributor.authorPérez-Arriaga, J. Ignacio
dc.date.accessioned2021-11-09T18:12:55Z
dc.date.available2021-11-09T18:12:55Z
dc.date.issued2018-09
dc.identifier.urihttps://hdl.handle.net/1721.1/138007
dc.description.abstract© 2018 IEEE. Restructuring an electricity sector entails a complex realignment of political and economic institutions, which may both delay and distort the achievement of satisfactorily competitive conditions. In research and planning for policy interventions in power systems under these varied regulatory environments, typical operational models may neglect important interactions between techno-economic criteria and political constraints, leading to poor understanding of underlying causes of inefficiency and to inappropriate recommendations. We develop tractable formulations of the unit commitment problem based on integer clustering of similar units that endogenize important political factors in the Northeast grid region of China. We demonstrate the importance of these interactions on operations and provide a set of options for researchers to explore further pathways for China's ongoing power system reforms. For example, wind integration, a key policy priority, is inhibited by the interaction of institutions limiting short- A nd long-term sources of flexibilities in interprovincial trade.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/TPWRS.2018.2822480en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMichael R. Davidsonen_US
dc.titleModeling unit commitment in political context: Case of China's partially restructured electricity sectoren_US
dc.typeArticleen_US
dc.identifier.citationDavidson, Michael R. and Pérez-Arriaga, J. Ignacio. 2018. "Modeling unit commitment in political context: Case of China's partially restructured electricity sector."
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.contributor.departmentMassachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change
dc.contributor.departmentSloan School of Management
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-09-26T17:13:55Z
dspace.date.submission2019-09-26T17:13:55Z
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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