{"id":{"repo_id":"ohiolink","oai_identifier":"oai:etd.ohiolink.edu:osu1366106454"},"canonical_url":"https://search.dev.ndltd.org/etd/ohiolink/oai:etd.ohiolink.edu:osu1366106454","repository":{"repo_id":"ohiolink","name":"OhioLINK","base_url":"https://etd.ohiolink.edu/acprod/odb_etd/ws/oai/oai"},"display":{"title":"Challenges in Electric Vehicle Adoption and Vehicle-Grid Integration","abstract":"With rapid innovation in vehicle and battery technology and strong support from governmental bodies and regulators, electric vehicles (EV) sales are poised to rise. While a better and cleaner world is likely in the near future, wide adoption of EVs also raises many challenges. First, to promote wide adoption of EVs requires sufficient amount of charging infrastructures, which we do not currently have. Meanwhile, utilities, energy system operators and system planners are concerned that large EV charging load would greatly affect the energy system operation and increase generation cost. Thus, new operation schemes are badly needed for the system to better adapt to large EV load. From the perspective of system reliability, EV charging might cause many reliability issues, especially at the distribution level. This dissertation addresses these challenges by developing new analytical models using a range of operation research, simulation, and statistical methodologies. The outcome will facilitate governmental bodies in developing technology and policy roadmaps for accelerating electric vehicle deployment, and also help utilities, energy system operators, and system planners to properly recognize challenges in vehicle-grid integration and develop compatible operation and planning strategies.","abstract_html":"With rapid innovation in vehicle and battery technology and strong support from governmental bodies and regulators, electric vehicles (EV) sales are poised to rise. While a better and cleaner world is likely in the near future, wide adoption of EVs also raises many challenges. First, to promote wide adoption of EVs requires sufficient amount of charging infrastructures, which we do not currently have. Meanwhile, utilities, energy system operators and system planners are concerned that large EV charging load would greatly affect the energy system operation and increase generation cost. Thus, new operation schemes are badly needed for the system to better adapt to large EV load. From the perspective of system reliability, EV charging might cause many reliability issues, especially at the distribution level. This dissertation addresses these challenges by developing new analytical models using a range of operation research, simulation, and statistical methodologies. The outcome will facilitate governmental bodies in developing technology and policy roadmaps for accelerating electric vehicle deployment, and also help utilities, energy system operators, and system planners to properly recognize challenges in vehicle-grid integration and develop compatible operation and planning strategies.","abstract_has_math":false,"creators":["Xi, Xiaomin"],"institution":"The Ohio State University","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Industrial and Systems Engineering","degree_department":null,"school":null,"contributors":["Sioshansi, Ramteen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-07-24","date_published":"2013-07-24","updated_at":"2026-07-24T03:37:46Z","subjects":["Economics","Energy","Industrial Engineering","Operations Research","Statistics"],"languages":["English"],"rights":["unrestricted","This thesis or dissertation is protected by copyright: some rights reserved. 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Meanwhile, utilities, energy system operators and system planners are concerned that large EV charging load would greatly affect the energy system operation and increase generation cost. Thus, new operation schemes are badly needed for the system to better adapt to large EV load. From the perspective of system reliability, EV charging might cause many reliability issues, especially at the distribution level. This dissertation addresses these challenges by developing new analytical models using a range of operation research, simulation, and statistical methodologies. The outcome will facilitate governmental bodies in developing technology and policy roadmaps for accelerating electric vehicle deployment, and also help utilities, energy system operators, and system planners to properly recognize challenges in vehicle-grid integration and develop compatible operation and planning strategies."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf","3.16 MB"]},{"key":"dc:title","label":"Title","values":["Challenges in Electric Vehicle Adoption and Vehicle-Grid Integration"]}]}],"canonical_facts":{"dc:contributor":["Sioshansi, Ramteen"],"dc:creator":["Xi, Xiaomin"],"dc:date":["2013-07-24"],"dc:description":["With rapid innovation in vehicle and battery technology and strong support from governmental bodies and regulators, electric vehicles (EV) sales are poised to rise. While a better and cleaner world is likely in the near future, wide adoption of EVs also raises many challenges. First, to promote wide adoption of EVs requires sufficient amount of charging infrastructures, which we do not currently have. Meanwhile, utilities, energy system operators and system planners are concerned that large EV charging load would greatly affect the energy system operation and increase generation cost. Thus, new operation schemes are badly needed for the system to better adapt to large EV load. From the perspective of system reliability, EV charging might cause many reliability issues, especially at the distribution level. This dissertation addresses these challenges by developing new analytical models using a range of operation research, simulation, and statistical methodologies. 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