{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/46937"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/46937","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Fast optimal power flow analysis for large-scale smart grid","abstract":"Optimal power flow OPF plays an important role in power system operation. The emerging smart grid aims to create an automated energy delivery system that enables two-way flows of electricity and information. As a result, it will be desirable if OPF can be solved in real time in order to allow the implementation of time-sensitive applications, such as real-time pricing. We develop a novel algorithm to accelerate the computation of alternating current optimal power flow (ACOPF) through power system network reduction (NR). We formulate the OPF problem based on an equivalent reduced system and then compute its solution. The detailed optimal dispatch for the original power system is obtained afterwards using a distributed algorithm. Our results are compared with two widely used methods: full ACOPF and the linearized OPF with DC power flow and lossless network assumption, the so-called DCOPF. Experimental results show that for a large power system, our method achieves 7.01× speedup over ACOPF with only 1.72% error, and is 75.7% more accurate than the DCOPF solution. Our method is even 10% faster than DCOPF. Our experimental results demonstrate the unique strength of the proposed technique for fast, scalable, and accurate OPF computation. We also show that the proposed method is effective for smaller benchmarks.","abstract_html":"Optimal power flow OPF plays an important role in power system operation. The emerging smart grid aims to create an automated energy delivery system that enables two-way flows of electricity and information. As a result, it will be desirable if OPF can be solved in real time in order to allow the implementation of time-sensitive applications, such as real-time pricing. We develop a novel algorithm to accelerate the computation of alternating current optimal power flow (ACOPF) through power system network reduction (NR). We formulate the OPF problem based on an equivalent reduced system and then compute its solution. The detailed optimal dispatch for the original power system is obtained afterwards using a distributed algorithm. Our results are compared with two widely used methods: full ACOPF and the linearized OPF with DC power flow and lossless network assumption, the so-called DCOPF. Experimental results show that for a large power system, our method achieves 7.01× speedup over ACOPF with only 1.72% error, and is 75.7% more accurate than the DCOPF solution. Our method is even 10% faster than DCOPF. Our experimental results demonstrate the unique strength of the proposed technique for fast, scalable, and accurate OPF computation. We also show that the proposed method is effective for smaller benchmarks.","abstract_has_math":false,"creators":["Liang, Yi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Chen, Deming"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-16T18:26:58Z","date_published":"2014-01-16T18:26:58Z","updated_at":"2026-07-22T22:25:38Z","subjects":["Smart Grid","Power System","Network Reduction","Optimal Power Flow"],"languages":["en"],"rights":["Copyright 2013 Yi Liang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/46937","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chen, Deming"]},{"key":"dc:creator","label":"Author","values":["Liang, Yi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-01-16T18:26:58Z","2016-01-16T11:01:38Z","2013-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"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":["Smart Grid","Power System","Network Reduction","Optimal Power Flow"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2013 Yi Liang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/46937"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Optimal power flow OPF plays an important role in power system operation. The emerging smart grid aims to create an automated energy delivery system that enables two-way flows of electricity and information. As a result, it will be desirable if OPF can be solved in real time in order to allow the implementation of time-sensitive applications, such as real-time pricing. We develop a novel algorithm to accelerate the computation of alternating current optimal power flow (ACOPF) through power system network reduction (NR). We formulate the OPF problem based on an equivalent reduced system and then compute its solution. The detailed optimal dispatch for the original power system is obtained afterwards using a distributed algorithm. Our results are compared with two widely used methods: full ACOPF and the linearized OPF with DC power flow and lossless network assumption, the so-called DCOPF. Experimental results show that for a large power system, our method achieves 7.01× speedup over ACOPF with only 1.72% error, and is 75.7% more accurate than the DCOPF solution. Our method is even 10% faster than DCOPF. Our experimental results demonstrate the unique strength of the proposed technique for fast, scalable, and accurate OPF computation. We also show that the proposed method is effective for smaller benchmarks.","Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2013-12-12T22:49:51Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Liang_Yi.pdf: 3568754 bytes, checksum: 549adb03e80b96cdf26f17706523d259 (MD5) Liang_Yi.pdf: 3568758 bytes, checksum: 2b65b6612148bb7eec53553424e832ff (MD5)","Made available in DSpace on 2014-01-16T18:26:58Z (GMT). No. of bitstreams: 2 Yi_Liang.pdf: 3568758 bytes, checksum: 2b65b6612148bb7eec53553424e832ff (MD5) license.txt: 4058 bytes, checksum: 4ef900c3c2eed55b0324d771b3ca936c (MD5)","Restriction data tranferred 2014-07-01T11:36:53-05:00 Original Data Group with Access Administrator Release Date: 2016-01-16 12:27:27 UTC Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Item marked as restricted to the 'Administrator' Group (id=1) by Seth Robbins (robbins.sd@gmail.com) on 2014-01-16T18:27:41Z Item is restricted until 2016-01-16T18:27:27Z","Limited Restriction Lifted for Item 46956 on 2016-01-16T11:01:38Z."]},{"key":"dc:title","label":"Title","values":["Fast optimal power flow analysis for large-scale smart grid"]}]}],"canonical_facts":{"dc:contributor":["Chen, Deming"],"dc:creator":["Liang, Yi"],"dc:date":["2014-01-16T18:26:58Z","2016-01-16T11:01:38Z","2013-12"],"dc:description":["Optimal power flow OPF plays an important role in power system operation. The emerging smart grid aims to create an automated energy delivery system that enables two-way flows of electricity and information. As a result, it will be desirable if OPF can be solved in real time in order to allow the implementation of time-sensitive applications, such as real-time pricing. We develop a novel algorithm to accelerate the computation of alternating current optimal power flow (ACOPF) through power system network reduction (NR). We formulate the OPF problem based on an equivalent reduced system and then compute its solution. The detailed optimal dispatch for the original power system is obtained afterwards using a distributed algorithm. Our results are compared with two widely used methods: full ACOPF and the linearized OPF with DC power flow and lossless network assumption, the so-called DCOPF. Experimental results show that for a large power system, our method achieves 7.01× speedup over ACOPF with only 1.72% error, and is 75.7% more accurate than the DCOPF solution. Our method is even 10% faster than DCOPF. Our experimental results demonstrate the unique strength of the proposed technique for fast, scalable, and accurate OPF computation. We also show that the proposed method is effective for smaller benchmarks.","Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2013-12-12T22:49:51Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Liang_Yi.pdf: 3568754 bytes, checksum: 549adb03e80b96cdf26f17706523d259 (MD5) Liang_Yi.pdf: 3568758 bytes, checksum: 2b65b6612148bb7eec53553424e832ff (MD5)","Made available in DSpace on 2014-01-16T18:26:58Z (GMT). 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