Daily integrated generation scheduling for thermal, pumped-storage, and cascaded hydro units and purchasing power considering network constraints
We have developed an innovative power generation scheduling method using quadratic programming (QP). The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to...
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Veröffentlicht in: | Electrical engineering in Japan 2011-04, Vol.175 (1), p.25-34 |
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creator | Sawa, Toshiyuki Sato, Yasuo Tsurugai, Mitsuo Onishi, Tsukasa |
description | We have developed an innovative power generation scheduling method using quadratic programming (QP). The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to this problem. We also add a penalty term to converge the value of those variables to 0 or 1 to the objective function: the sum of the fuel costs and the start‐up costs. This penalty term depends on the per‐unit fuel cost. The possibility of its variable converging to zero increases as the cost increases. This method was applied to a test system of daily generation scheduling that consisted of 29 thermal units, two pumped‐storage units, four cascaded hydro units, and one transmission. The schedule satisfied all constraints, that is, load‐power balance, operation reserve, power flow, minimum up/down‐times, and fuel consumption. This result shows that the proposed method is effective. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(1): 25–34, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21014 |
doi_str_mv | 10.1002/eej.21014 |
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The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to this problem. We also add a penalty term to converge the value of those variables to 0 or 1 to the objective function: the sum of the fuel costs and the start‐up costs. This penalty term depends on the per‐unit fuel cost. The possibility of its variable converging to zero increases as the cost increases. This method was applied to a test system of daily generation scheduling that consisted of 29 thermal units, two pumped‐storage units, four cascaded hydro units, and one transmission. The schedule satisfied all constraints, that is, load‐power balance, operation reserve, power flow, minimum up/down‐times, and fuel consumption. This result shows that the proposed method is effective. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(1): 25–34, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). 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Eng. Jpn</addtitle><description>We have developed an innovative power generation scheduling method using quadratic programming (QP). The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to this problem. We also add a penalty term to converge the value of those variables to 0 or 1 to the objective function: the sum of the fuel costs and the start‐up costs. This penalty term depends on the per‐unit fuel cost. The possibility of its variable converging to zero increases as the cost increases. This method was applied to a test system of daily generation scheduling that consisted of 29 thermal units, two pumped‐storage units, four cascaded hydro units, and one transmission. The schedule satisfied all constraints, that is, load‐power balance, operation reserve, power flow, minimum up/down‐times, and fuel consumption. This result shows that the proposed method is effective. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(1): 25–34, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21014</description><subject>Costs</subject><subject>Economics</subject><subject>Fuels</subject><subject>hydrothermal</subject><subject>interior point method</subject><subject>minimum up and down times</subject><subject>network constraints</subject><subject>On-line systems</subject><subject>Online</subject><subject>Purchasing</subject><subject>Quadratic programming</subject><subject>Scheduling</subject><subject>unit commitment</subject><issn>0424-7760</issn><issn>1520-6416</issn><issn>1520-6416</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp1kM9uEzEQxi0EEqFw4A18BKnbjr1ee_eISlr-RHAp6tFyvbOJ24292F6leQzeGCcBbpxmNPP7RvN9hLxlcMEA-CXiwwVnwMQzsmANh0oKJp-TBQguKqUkvCSvUnoAAMVUuyC_Pho37qnzGdfRZOzpGj2WzgVPk91gP4_Or-kQIs0bjFszntNp3k7YVymHaNZ4To3vqTXJmr7oN_s-Bjp7l9NxMc3Rbkw6HJnCDiO1wSfXYzxMPOZdiI_HWY6mvJFekxeDGRO--VPPyI_r5e3Vp2r1_ebz1YdVZQVIUeFQD1zVaFvZGugNZ6oxRnXFr-pqxQGYgXshWl5cM0A7yF6whinZYHtfy_qMvDvdnWL4OWPKeuuSxXE0HsOcNIOa8U4o1hX0_Qm1MaQUcdBTdFsT9wXSh9h1iV0fYy_s5YnduRH3_wf1cvnlr6I6KVzK-PRPYeKjlqpWjb77dqOvv3Z3K3kLuqt_Ays0lWA</recordid><startdate>20110415</startdate><enddate>20110415</enddate><creator>Sawa, Toshiyuki</creator><creator>Sato, Yasuo</creator><creator>Tsurugai, Mitsuo</creator><creator>Onishi, Tsukasa</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>L7M</scope></search><sort><creationdate>20110415</creationdate><title>Daily integrated generation scheduling for thermal, pumped-storage, and cascaded hydro units and purchasing power considering network constraints</title><author>Sawa, Toshiyuki ; Sato, Yasuo ; Tsurugai, Mitsuo ; Onishi, Tsukasa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4064-ef3f273ec868a0da2175aa7964179372001a0b448277610ecf6d4151765e8b363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Costs</topic><topic>Economics</topic><topic>Fuels</topic><topic>hydrothermal</topic><topic>interior point method</topic><topic>minimum up and down times</topic><topic>network constraints</topic><topic>On-line systems</topic><topic>Online</topic><topic>Purchasing</topic><topic>Quadratic programming</topic><topic>Scheduling</topic><topic>unit commitment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sawa, Toshiyuki</creatorcontrib><creatorcontrib>Sato, Yasuo</creatorcontrib><creatorcontrib>Tsurugai, Mitsuo</creatorcontrib><creatorcontrib>Onishi, Tsukasa</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Electrical engineering in Japan</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sawa, Toshiyuki</au><au>Sato, Yasuo</au><au>Tsurugai, Mitsuo</au><au>Onishi, Tsukasa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Daily integrated generation scheduling for thermal, pumped-storage, and cascaded hydro units and purchasing power considering network constraints</atitle><jtitle>Electrical engineering in Japan</jtitle><addtitle>Elect. Eng. Jpn</addtitle><date>2011-04-15</date><risdate>2011</risdate><volume>175</volume><issue>1</issue><spage>25</spage><epage>34</epage><pages>25-34</pages><issn>0424-7760</issn><issn>1520-6416</issn><eissn>1520-6416</eissn><abstract>We have developed an innovative power generation scheduling method using quadratic programming (QP). The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to this problem. We also add a penalty term to converge the value of those variables to 0 or 1 to the objective function: the sum of the fuel costs and the start‐up costs. This penalty term depends on the per‐unit fuel cost. The possibility of its variable converging to zero increases as the cost increases. 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subjects | Costs Economics Fuels hydrothermal interior point method minimum up and down times network constraints On-line systems Online Purchasing Quadratic programming Scheduling unit commitment |
title | Daily integrated generation scheduling for thermal, pumped-storage, and cascaded hydro units and purchasing power considering network constraints |
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