Improved fuzzy load models by clustering techniques in optimal planning of distribution networks
The notion of modeling is essential to modern techniques of control and operation process. Developing a control process in fact means developing a model that allows us to predict the action and reduce the amount of feedback required. Recently the fuzzy modeling has become driving force that today is...
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| creator | Cartina, G. Grigoras, G. Bobric, E.C. Comanescu, D. |
| description | The notion of modeling is essential to modern techniques of control and operation process. Developing a control process in fact means developing a model that allows us to predict the action and reduce the amount of feedback required. Recently the fuzzy modeling has become driving force that today is reflected in many different software and hardware products. The paper presents improvements of the fuzzy load models by clustering techniques in distribution networks planning. The hierarchic clustering techniques, conjunctively with fuzzy modeling, are proposed in this paper for determination of the typical load profiles, customers' categories, and so on. Obtained results demonstrate the ability of the fuzzy load models to overcome difficult aspects encountered in process control and operation problems. |
| doi_str_mv | 10.1109/PTC.2009.5282025 |
| format | Conference Proceeding |
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Developing a control process in fact means developing a model that allows us to predict the action and reduce the amount of feedback required. Recently the fuzzy modeling has become driving force that today is reflected in many different software and hardware products. The paper presents improvements of the fuzzy load models by clustering techniques in distribution networks planning. The hierarchic clustering techniques, conjunctively with fuzzy modeling, are proposed in this paper for determination of the typical load profiles, customers' categories, and so on. Obtained results demonstrate the ability of the fuzzy load models to overcome difficult aspects encountered in process control and operation problems.</description><subject>Clustering techniques</subject><subject>Decision making</subject><subject>distribution networks</subject><subject>Feedback</subject><subject>Fuzzy control</subject><subject>fuzzy load models</subject><subject>Hardware</subject><subject>Investments</subject><subject>Load modeling</subject><subject>load profiles</subject><subject>optimal planning</subject><subject>Pattern analysis</subject><subject>Power systems</subject><subject>Predictive models</subject><subject>Process control</subject><isbn>9781424422340</isbn><isbn>1424422345</isbn><isbn>9781424422357</isbn><isbn>1424422353</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkE1LxDAYhCMiKGvvgpf8gV2TN4ltjrL4sbCgh_W8Ns0bjXaT2qRK99dbcS_O5WEYGIYh5IKzBedMXz1tlgtgTC8UVMBAHZFClxWXICWAUOXxPy_ZKSlSemeTpBL8Wp-Rl9Wu6-MXWuqG_X6kbawt3UWLbaJmpE07pIy9D680Y_MW_OeAifpAY5f9rm5p19Yh_MbRUetT7r0Zso-BBszfsf9I5-TE1W3C4sAZeb673Swf5uvH-9XyZj33vFR57pQwwKUyQuE0T9uGg6i05tzVWigGzhrH7QRlwAjUojIMQdSVLSWUTMzI5V-vR8Rt10_r-nF7-EX8AJewV1o</recordid><startdate>200906</startdate><enddate>200906</enddate><creator>Cartina, G.</creator><creator>Grigoras, G.</creator><creator>Bobric, E.C.</creator><creator>Comanescu, D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200906</creationdate><title>Improved fuzzy load models by clustering techniques in optimal planning of distribution networks</title><author>Cartina, G. ; Grigoras, G. ; Bobric, E.C. ; Comanescu, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-f53b2145b35e0009dc12389911fa93502fdbf1d2fd5b2b3e938b0e23a8d742703</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Clustering techniques</topic><topic>Decision making</topic><topic>distribution networks</topic><topic>Feedback</topic><topic>Fuzzy control</topic><topic>fuzzy load models</topic><topic>Hardware</topic><topic>Investments</topic><topic>Load modeling</topic><topic>load profiles</topic><topic>optimal planning</topic><topic>Pattern analysis</topic><topic>Power systems</topic><topic>Predictive models</topic><topic>Process control</topic><toplevel>online_resources</toplevel><creatorcontrib>Cartina, G.</creatorcontrib><creatorcontrib>Grigoras, G.</creatorcontrib><creatorcontrib>Bobric, E.C.</creatorcontrib><creatorcontrib>Comanescu, D.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cartina, G.</au><au>Grigoras, G.</au><au>Bobric, E.C.</au><au>Comanescu, D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Improved fuzzy load models by clustering techniques in optimal planning of distribution networks</atitle><btitle>2009 IEEE Bucharest PowerTech</btitle><stitle>PTC</stitle><date>2009-06</date><risdate>2009</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><isbn>9781424422340</isbn><isbn>1424422345</isbn><eisbn>9781424422357</eisbn><eisbn>1424422353</eisbn><abstract>The notion of modeling is essential to modern techniques of control and operation process. Developing a control process in fact means developing a model that allows us to predict the action and reduce the amount of feedback required. Recently the fuzzy modeling has become driving force that today is reflected in many different software and hardware products. The paper presents improvements of the fuzzy load models by clustering techniques in distribution networks planning. The hierarchic clustering techniques, conjunctively with fuzzy modeling, are proposed in this paper for determination of the typical load profiles, customers' categories, and so on. Obtained results demonstrate the ability of the fuzzy load models to overcome difficult aspects encountered in process control and operation problems.</abstract><pub>IEEE</pub><doi>10.1109/PTC.2009.5282025</doi><tpages>6</tpages></addata></record> |
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| ispartof | 2009 IEEE Bucharest PowerTech, 2009, p.1-6 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Clustering techniques Decision making distribution networks Feedback Fuzzy control fuzzy load models Hardware Investments Load modeling load profiles optimal planning Pattern analysis Power systems Predictive models Process control |
| title | Improved fuzzy load models by clustering techniques in optimal planning of distribution networks |
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