{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99526"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99526","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Decision support system for reservoir operation using analytical modeling results","abstract":"This study applies an analytical approach to solving reservoir operation problems, in particular, developing an algorithm to search for the optimal solution for a system of reservoirs in parallel, establishing procedures to determine the effective forecast horizon, and demonstrating the practical applications of the derived rules. Based on these, a decision support system for reservoir operation is developed. More specifically, the analytical work of this thesis includes two parts. In the first part, a multi-stage optimization model is set up to derive the properties of optimal release decisions for a system of reservoirs in parallel with a single demand site; following that an algorithm is developed using the analytical results. In the second part, the properties of the optimal solution for a single water supply reservoir under uncertain forecast are derived, and these properties are then used to develop criteria and procedures to determine the effective forecast horizon, which can inform reservoir managers in the actual use of inflow forecast. Finally, a prototype reservoir operation decision support system is developed based on the analytical results. This system is to illustrate the applications of analytically derived reservoir operation rules to guide real-world reservoir operations. Through the system, users can use a graphical user interface (GUI) to upload data, execute model, and visualize the results. As a conclusion, being different from most existing studies using numerical models, this thesis shows the capabilities of the analytical approaches in providing information for real-world reservoir operation problems.","abstract_html":"This study applies an analytical approach to solving reservoir operation problems, in particular, developing an algorithm to search for the optimal solution for a system of reservoirs in parallel, establishing procedures to determine the effective forecast horizon, and demonstrating the practical applications of the derived rules. Based on these, a decision support system for reservoir operation is developed. More specifically, the analytical work of this thesis includes two parts. In the first part, a multi-stage optimization model is set up to derive the properties of optimal release decisions for a system of reservoirs in parallel with a single demand site; following that an algorithm is developed using the analytical results. In the second part, the properties of the optimal solution for a single water supply reservoir under uncertain forecast are derived, and these properties are then used to develop criteria and procedures to determine the effective forecast horizon, which can inform reservoir managers in the actual use of inflow forecast. Finally, a prototype reservoir operation decision support system is developed based on the analytical results. This system is to illustrate the applications of analytically derived reservoir operation rules to guide real-world reservoir operations. Through the system, users can use a graphical user interface (GUI) to upload data, execute model, and visualize the results. As a conclusion, being different from most existing studies using numerical models, this thesis shows the capabilities of the analytical approaches in providing information for real-world reservoir operation problems.","abstract_has_math":false,"creators":["Zhao, Qiankun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cai, Ximing"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T17:35:54Z","date_published":"2018-03-13T17:35:54Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Analytical reservoir operation rules","Decision support system","System of reservoirs in parallel","Effective forecast horizon"],"languages":["en"],"rights":["Copyright 2017 Qiankun Zhao"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99526","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cai, Ximing"]},{"key":"dc:creator","label":"Author","values":["Zhao, Qiankun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T17:35:54Z","2020-03-14T09:15:08Z","2017-12-11","2017-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Analytical reservoir operation rules","Decision support system","System of reservoirs in parallel","Effective forecast horizon"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Qiankun Zhao"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99526"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This study applies an analytical approach to solving reservoir operation problems, in particular, developing an algorithm to search for the optimal solution for a system of reservoirs in parallel, establishing procedures to determine the effective forecast horizon, and demonstrating the practical applications of the derived rules. Based on these, a decision support system for reservoir operation is developed. More specifically, the analytical work of this thesis includes two parts. In the first part, a multi-stage optimization model is set up to derive the properties of optimal release decisions for a system of reservoirs in parallel with a single demand site; following that an algorithm is developed using the analytical results. In the second part, the properties of the optimal solution for a single water supply reservoir under uncertain forecast are derived, and these properties are then used to develop criteria and procedures to determine the effective forecast horizon, which can inform reservoir managers in the actual use of inflow forecast. Finally, a prototype reservoir operation decision support system is developed based on the analytical results. This system is to illustrate the applications of analytically derived reservoir operation rules to guide real-world reservoir operations. Through the system, users can use a graphical user interface (GUI) to upload data, execute model, and visualize the results. As a conclusion, being different from most existing studies using numerical models, this thesis shows the capabilities of the analytical approaches in providing information for real-world reservoir operation problems.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-12-01","The student, Qiankun Zhao, accepted the attached license on 2017-12-08 at 23:46.","The student, Qiankun Zhao, submitted this Thesis for approval on 2017-12-08 at 23:47.","This Thesis was approved for publication on 2017-12-11 at 10:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11933 on 2018-03-13 at 10:38:07","Made available in DSpace on 2018-03-13T17:35:54Z (GMT). No. of bitstreams: 2 ZHAO-THESIS-2017.pdf: 2796563 bytes, checksum: 92b9e008df8b14e8108d9998ce36f63f (MD5) LICENSE.txt: 4209 bytes, checksum: d25db29455d18db3b9d0fc75aef2c79c (MD5) Previous issue date: 2017-12-11","Embargo set by: Seth Robbins for item 105495 Lift date: 2020-03-13T17:36:05Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 105495 on 2020-03-14T09:15:08Z."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Decision support system for reservoir operation using analytical modeling results"]}]}],"canonical_facts":{"dc:contributor":["Cai, Ximing"],"dc:creator":["Zhao, Qiankun"],"dc:date":["2018-03-13T17:35:54Z","2020-03-14T09:15:08Z","2017-12-11","2017-12"],"dc:description":["This study applies an analytical approach to solving reservoir operation problems, in particular, developing an algorithm to search for the optimal solution for a system of reservoirs in parallel, establishing procedures to determine the effective forecast horizon, and demonstrating the practical applications of the derived rules. Based on these, a decision support system for reservoir operation is developed. More specifically, the analytical work of this thesis includes two parts. In the first part, a multi-stage optimization model is set up to derive the properties of optimal release decisions for a system of reservoirs in parallel with a single demand site; following that an algorithm is developed using the analytical results. In the second part, the properties of the optimal solution for a single water supply reservoir under uncertain forecast are derived, and these properties are then used to develop criteria and procedures to determine the effective forecast horizon, which can inform reservoir managers in the actual use of inflow forecast. Finally, a prototype reservoir operation decision support system is developed based on the analytical results. This system is to illustrate the applications of analytically derived reservoir operation rules to guide real-world reservoir operations. Through the system, users can use a graphical user interface (GUI) to upload data, execute model, and visualize the results. As a conclusion, being different from most existing studies using numerical models, this thesis shows the capabilities of the analytical approaches in providing information for real-world reservoir operation problems.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-12-01","The student, Qiankun Zhao, accepted the attached license on 2017-12-08 at 23:46.","The student, Qiankun Zhao, submitted this Thesis for approval on 2017-12-08 at 23:47.","This Thesis was approved for publication on 2017-12-11 at 10:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11933 on 2018-03-13 at 10:38:07","Made available in DSpace on 2018-03-13T17:35:54Z (GMT). No. of bitstreams: 2 ZHAO-THESIS-2017.pdf: 2796563 bytes, checksum: 92b9e008df8b14e8108d9998ce36f63f (MD5) LICENSE.txt: 4209 bytes, checksum: d25db29455d18db3b9d0fc75aef2c79c (MD5) Previous issue date: 2017-12-11","Embargo set by: Seth Robbins for item 105495 Lift date: 2020-03-13T17:36:05Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 105495 on 2020-03-14T09:15:08Z."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/99526"],"dc:language":["en"],"dc:rights":["Copyright 2017 Qiankun Zhao"],"dc:subject":["Analytical reservoir operation rules","Decision support system","System of reservoirs in parallel","Effective forecast horizon"],"dc:title":["Decision support system for reservoir operation using analytical modeling results"],"dc:type":["text"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:37Z"}