{"id":{"repo_id":"uno","oai_identifier":"oai:scholarworks.uno.edu:td-2318"},"canonical_url":"https://search.dev.ndltd.org/etd/uno/oai:scholarworks.uno.edu:td-2318","repository":{"repo_id":"uno","name":"University of New Orleans","base_url":"https://scholarworks.uno.edu/do/oai/"},"display":{"title":"Optimization of Financial Transmission Right Portfolios Using Risk-Reward Analysis of Deregulated Power Systems","abstract":"Financial Transmission Rights (FTR) is an investment that protects the market customers from price uncertainty in the case of transmission line congestion. Pennsylvania-New Jersey-Maryland Interconnection (PJM) allows bidding of FTR's on various transmission paths. This thesis investigates quantitative methods for portfolio optimization to produce a risk-minimum portfolio of FTR's to bid. A computer model based on Security-Constrained Unit Commitment Problem and Risk-Reward Analysis is developed to simulate various operating conditions of a power system and predict the variations of power flows and corresponding electricity prices. It offers guidelines about the bidding cost and the amount of megawatts to bid for each transmission path, in order to obtain a certain profit with the corresponding minimum risk. The method for calculating the risk and reward is Markowitz Mean-Variance Analysis. The computer model also includes the LMP determination for which a MATLAB code has been developed. The model is tested on a 6-bus power system.","abstract_html":"Financial Transmission Rights (FTR) is an investment that protects the market customers from price uncertainty in the case of transmission line congestion. Pennsylvania-New Jersey-Maryland Interconnection (PJM) allows bidding of FTR's on various transmission paths. This thesis investigates quantitative methods for portfolio optimization to produce a risk-minimum portfolio of FTR's to bid. A computer model based on Security-Constrained Unit Commitment Problem and Risk-Reward Analysis is developed to simulate various operating conditions of a power system and predict the variations of power flows and corresponding electricity prices. It offers guidelines about the bidding cost and the amount of megawatts to bid for each transmission path, in order to obtain a certain profit with the corresponding minimum risk. The method for calculating the risk and reward is Markowitz Mean-Variance Analysis. The computer model also includes the LMP determination for which a MATLAB code has been developed. The model is tested on a 6-bus power system.","abstract_has_math":false,"creators":["Nandedkar, Aashay"],"institution":null,"degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Leevongwat, Ittiphong","Rastgoufard, Parviz","Charalampidis, Dimitrios"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-20T07:00:00Z","date_published":"2011-05-20T07:00:00Z","updated_at":"2026-07-24T05:29:24Z","subjects":["Electrical Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uno.edu/td/1334","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Leevongwat, Ittiphong","Rastgoufard, Parviz","Charalampidis, Dimitrios"]},{"key":"dc:creator","label":"Author","values":["Nandedkar, Aashay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uno.edu/td/1334"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Financial Transmission Rights (FTR) is an investment that protects the market customers from price uncertainty in the case of transmission line congestion. Pennsylvania-New Jersey-Maryland Interconnection (PJM) allows bidding of FTR's on various transmission paths. This thesis investigates quantitative methods for portfolio optimization to produce a risk-minimum portfolio of FTR's to bid. A computer model based on Security-Constrained Unit Commitment Problem and Risk-Reward Analysis is developed to simulate various operating conditions of a power system and predict the variations of power flows and corresponding electricity prices. It offers guidelines about the bidding cost and the amount of megawatts to bid for each transmission path, in order to obtain a certain profit with the corresponding minimum risk. The method for calculating the risk and reward is Markowitz Mean-Variance Analysis. The computer model also includes the LMP determination for which a MATLAB code has been developed. The model is tested on a 6-bus power system."]},{"key":"dc:title","label":"Title","values":["Optimization of Financial Transmission Right Portfolios Using Risk-Reward Analysis of Deregulated Power Systems"]}]}],"canonical_facts":{"dc:contributor":["Leevongwat, Ittiphong","Rastgoufard, Parviz","Charalampidis, Dimitrios"],"dc:creator":["Nandedkar, Aashay"],"dc:description.abstract":["Financial Transmission Rights (FTR) is an investment that protects the market customers from price uncertainty in the case of transmission line congestion. Pennsylvania-New Jersey-Maryland Interconnection (PJM) allows bidding of FTR's on various transmission paths. This thesis investigates quantitative methods for portfolio optimization to produce a risk-minimum portfolio of FTR's to bid. A computer model based on Security-Constrained Unit Commitment Problem and Risk-Reward Analysis is developed to simulate various operating conditions of a power system and predict the variations of power flows and corresponding electricity prices. It offers guidelines about the bidding cost and the amount of megawatts to bid for each transmission path, in order to obtain a certain profit with the corresponding minimum risk. The method for calculating the risk and reward is Markowitz Mean-Variance Analysis. The computer model also includes the LMP determination for which a MATLAB code has been developed. The model is tested on a 6-bus power system."],"dc:identifier":["https://scholarworks.uno.edu/td/1334"],"dc:subject":["Electrical Engineering"],"dc:title":["Optimization of Financial Transmission Right Portfolios Using Risk-Reward Analysis of Deregulated Power Systems"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T05:29:24Z"}