{"id":18549,"date":"2015-05-06T12:44:21","date_gmt":"2015-05-06T09:14:21","guid":{"rendered":"http:\/\/www.irantahgig.ir\/?p=18549"},"modified":"2015-05-06T12:46:07","modified_gmt":"2015-05-06T09:16:07","slug":"%d8%b1%d9%88%d8%b4-%d8%a8%d9%87%db%8c%d9%86%d9%87-%d8%b3%d8%a7%d8%b2%db%8c-%d8%a8%d8%b9%d8%af-%d9%85%d8%aa%d8%ba%db%8c%d8%b1-%d8%a8%d8%b1%d8%a7%db%8c-%d8%ad%d9%84-%d9%85%d8%b3%d8%a3%d9%84%d9%87-%d8%af","status":"publish","type":"post","link":"http:\/\/www.irantahgig.ir\/?p=18549","title":{"rendered":"\u0631\u0648\u0634 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0628\u0639\u062f \u0645\u062a\u063a\u06cc\u0631 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0645\u0633\u0623\u0644\u0647 \u062f\u0631 \u0645\u062f\u0627\u0631 \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0646 \u0646\u06cc\u0631\u0648\u06af\u0627\u0647 \u0647\u0627"},"content":{"rendered":"

A variable-dimension optimization approach to unit commitment problem<\/span><\/p>\n

\u062a\u0627\u0631\u06cc\u062e:<\/strong> \u06f2\u06f0\u06f1\u06f0<\/span><\/p>\n

\u067e\u0627\u06cc\u06af\u0627\u0647:\u00a0<\/strong>IEEE Xplore<\/span><\/span><\/p>\n

\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0627\u0635\u0644 \u0645\u0642\u0627\u0644\u0647<\/a><\/span><\/p>\n

\"OK\"<\/span><\/p>\n

\t

\n\n\t\t\n\t\t
\n\t\t\t150,000 \u0631\u06cc\u0627\u0644 – \u067e\u0631\u062f\u0627\u062e\u062a \u0648 \u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 \u062a\u0631\u062c\u0645\u0647<\/span> <\/span><\/a>\u0646\u0647\u0627\u06cc\u06cc \u06a9\u0631\u062f\u0646 \u062e\u0631\u06cc\u062f<\/a>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t<\/svg>\n\t\t\t\t\t\t\u0645\u0648\u0631\u062f \u0628\u0647 \u0633\u0628\u062f \u062e\u0631\u06cc\u062f \u0627\u0636\u0627\u0641\u0647 \u0634\u062f\t\t\t\t\t<\/span>\n\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t

<\/span><\/p>\n

\u0646\u0627\u0645 \u0645\u062c\u0644\u0647:\u00a0<\/strong>Power Systems<\/span><\/span><\/p>\n

\u0642\u06cc\u0645\u062a:<\/strong> \u06f1\u06f5\u06f0,\u06f0\u06f0\u06f0 \u0631\u06cc\u0627\u0644<\/span><\/p>\n

\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc:<\/strong> \u06f9<\/span><\/p>\n

\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a \u0641\u0627\u0631\u0633\u06cc:<\/strong> \u06f1\u06f9<\/span><\/p>\n

\u06a9\u062f: <\/strong>\u06f3\u06f0\u06f3\u06f3\u06f4<\/span><\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0641\u0627\u0631\u0633\u06cc<\/span><\/h3>\n

\u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u06cc\u06a9 \u0631\u0648\u0634 \u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0628\u0639\u062f \u0645\u062a\u063a\u06cc\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u0633\u0627\u0626\u0644 dimensionality<\/span> \u0628\u0627\u0644\u0627 \u062f\u0631 \u062d\u0644 \u0645\u0633\u0623\u0644\u0647 \u062f\u0631 \u0645\u062f\u0627\u0631 \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0646 \u0646\u06cc\u0631\u0648\u06af\u0627\u0647\u200c\u0647\u0627 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f \u0645\u06cc\u200c\u06a9\u0646\u062f. \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0627\u0635\u0644 \u0628\u0639\u062f \u0641\u0636\u0627\u06cc \u062c\u0633\u062a\u062c\u0648\u06cc \u062a\u0637\u0628\u06cc\u0642\u06cc \u0631\u0627 \u0645\u0639\u0631\u0641\u06cc \u0645\u06cc\u200c\u06a9\u0646\u062f. \u0631\u0627\u0647\u200c\u06a9\u0627\u0631 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f\u06cc \u062f\u0631 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0627\u0632\u062f\u062d\u0627\u0645 \u0630\u0631\u0627\u062a \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0634\u062f\u0647 \u0627\u0633\u062a. \u0641\u0631\u0622\u06cc\u0646\u062f \u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0628\u0627 \u0628\u0639\u062f \u0645\u0633\u0623\u0644\u0647 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0622\u063a\u0627\u0632 \u0645\u06cc\u200c\u0634\u0648\u062f \u0648 \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u067e\u06cc\u0634\u0631\u0641\u062a \u0627\u0632\u062f\u062d\u0627\u0645 \u062a\u0637\u0628\u06cc\u0642 \u0645\u06cc\u200c\u06cc\u0627\u0628\u062f \u0648 \u062f\u0631 \u067e\u0627\u06cc\u0627\u0646\u060c \u0641\u0636\u0627\u06cc \u0628\u0639\u062f\u06cc \u0628\u0647\u06cc\u0646\u0647 \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc\u200c\u06a9\u0646\u062f. \u06a9\u0627\u0631\u0622\u06cc\u06cc \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0628\u0631 \u0631\u0648\u06cc \u06cc\u06a9 \u0633\u06cc\u0633\u062a\u0645 \u062a\u0633\u062a \u062f\u0647 \u0648\u0627\u062d\u062f\u06cc \u0622\u0632\u0645\u0627\u06cc\u0634 \u0645\u06cc\u200c\u0634\u0648\u062f. \u0646\u062a\u0627\u06cc\u062c \u0628\u0627 \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0631\u06cc\u0632\u06cc \u062f\u0648\u062f\u0648\u06cc\u06cc \u0648 \u0633\u06cc\u06a9\u0644 \u0648\u0638\u06cc\u0641\u0647 \u062b\u0627\u0628\u062a \u0645\u0642\u0627\u06cc\u0633\u0647 \u0645\u06cc\u200c\u0634\u0648\u0646\u062f. \u0646\u062a\u0627\u06cc\u062c \u0634\u0628\u06cc\u0647\u200c\u0633\u0627\u0632\u06cc \u0646\u0634\u0627\u0646 \u0645\u06cc\u200c\u062f\u0647\u0646\u062f \u06a9\u0647 \u0631\u0648\u0634 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f\u06cc \u0645\u0648\u062c\u0628 \u06a9\u0627\u0647\u0634 \u0642\u0627\u0628\u0644 \u0645\u0644\u0627\u062d\u0638\u0647 \u0628\u0639\u062f \u0645\u0633\u0623\u0644\u0647\u060c \u0647\u0645\u06af\u0631\u0627\u06cc\u06cc \u0633\u0631\u06cc\u0639\u200c\u062a\u0631 \u0648 \u06a9\u06cc\u0641\u06cc\u062a \u0628\u0647\u0628\u0648\u062f\u06cc\u0627\u0641\u062a\u0647 \u0631\u0627\u0647\u200c\u062d\u0644 \u0646\u0647\u0627\u06cc\u06cc \u0645\u06cc\u200c\u0634\u0648\u062f.<\/span><\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/span><\/h3>\n

This paper proposes a variable-dimension optimization approach to address the high dimensionality issues in solving the unit commitment problem. This method introduces the concept of adaptive search space dimension. The proposed approach is implemented in particle swarm optimization algorithm. The optimization process starts with an arbitrary problem dimension, adapts with respect to the swarm progress and finally selects the optimal dimensional space. The efficiency of this method is tested on a ten-unit test system. The results are compared with binary programming and fixed duty cycle approaches. The simulation results show that the proposed method results in considerable reduction of problem dimension, faster convergence and improved quality of the final solution<\/span><\/p>\n

\u0645\u0634\u062e\u0635\u0627\u062a \u0627\u0633\u062a\u0646\u0627\u062f\u06cc<\/strong><\/span><\/h3>\n

Pappala, V. S., & Erlich, I. (2010). A variable-dimension optimization approach to unit commitment problem. Power Systems, IEEE Transactions on, 25(3), 1696-1704<\/span><\/p>\n

\u062f\u0627\u0646\u0644\u0648\u062f \u0627\u0635\u0644 \u0645\u0642\u0627\u0644\u0647<\/span><\/h3>\n

\"10002icon\"<\/a>\u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627\u06cc \u0645\u0642\u0627\u0644\u0647 \u0631\u0648\u0634 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0628\u0639\u062f \u0645\u062a\u063a\u06cc\u0631 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0645\u0633\u0623\u0644\u0647 \u062f\u0631 \u0645\u062f\u0627\u0631 \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0646 \u0646\u06cc\u0631\u0648\u06af\u0627\u0647 \u0647\u0627<\/span><\/h1>\n

\u0645\u0642\u0627\u0644\u0647 “\u0631\u0648\u0634 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0628\u0639\u062f \u0645\u062a\u063a\u06cc\u0631 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0645\u0633\u0623\u0644\u0647 \u062f\u0631 \u0645\u062f\u0627\u0631 \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0646 \u0646\u06cc\u0631\u0648\u06af\u0627\u0647 \u0647\u0627” \u062f\u0631 \u0633\u0627\u0644 \u06f2\u06f0\u06f1\u06f0 \u062f\u0631 \u0645\u062c\u0644\u0647\u00a0Power Systems<\/span> \u0686\u0627\u067e \u0634\u062f\u0647 \u0648 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0627\u0637\u0644\u0627\u0639\u0627\u062a\u06cc\u00a0IEEE<\/span> \u0646\u0645\u0627\u06cc\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0628\u0631\u0631\u0633\u06cc\u00a0\u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0627\u0632\u062f\u062d\u0627\u0645 \u0630\u0631\u0627\u062a \u0648\u00a0\u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0628\u0639\u062f \u0645\u062a\u063a\u06cc\u0631 \u0645\u0633\u0627\u0626\u0644 dimensionality<\/span> \u0628\u0627\u0644\u0627 \u067e\u0631\u062f\u0627\u062e\u062a\u0647 \u0627\u0633\u062a. \u0647\u0645\u0686\u0646\u06cc\u0646 \u0628\u0631\u0627\u0633\u0627\u0633 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u067e\u0627\u06cc\u06af\u0627\u0647 \u0627\u0637\u0644\u0627\u0639\u0627\u062a\u06cc \u06af\u0648\u06af\u0644 \u0627\u0633\u06a9\u0648\u0644\u0627\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u06f1\u06f4 \u0628\u0627\u0631 \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0646\u0627\u062f \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0647 \u0627\u0633\u062a.<\/span><\/p>\n

\t\n\n\t\t\n\t\t

\n\t\t\t150,000 \u0631\u06cc\u0627\u0644 – \u067e\u0631\u062f\u0627\u062e\u062a \u0648 \u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 \u062a\u0631\u062c\u0645\u0647<\/span> <\/span><\/a>\u0646\u0647\u0627\u06cc\u06cc \u06a9\u0631\u062f\u0646 \u062e\u0631\u06cc\u062f<\/a>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t<\/svg>\n\t\t\t\t\t\t\u0645\u0648\u0631\u062f \u0628\u0647 \u0633\u0628\u062f \u062e\u0631\u06cc\u062f \u0627\u0636\u0627\u0641\u0647 \u0634\u062f\t\t\t\t\t<\/span>\n\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t

A variable-dimension optimization approach to unit commitment problem \u062a\u0627\u0631\u06cc\u062e: \u06f2\u06f0\u06f1\u06f0 \u067e\u0627\u06cc\u06af\u0627\u0647:\u00a0IEEE Xplore \u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0627\u0635\u0644 \u0645\u0642\u0627\u0644\u0647<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[84,127,292,314,316],"tags":[],"_links":{"self":[{"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/posts\/18549"}],"collection":[{"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=18549"}],"version-history":[{"count":2,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/posts\/18549\/revisions"}],"predecessor-version":[{"id":19440,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=\/wp\/v2\/posts\/18549\/revisions\/19440"}],"wp:attachment":[{"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=18549"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=18549"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.irantahgig.ir\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=18549"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}