ANN based peak power tracking for PV supplied DC motors
This paper presents an application of an Artificial Neural Network (ANN) for the identification of the optimal operating point of a PV supplied separately excited dc motor driving two different load torques. A gradient descent algorithm is used to train the ANN controller for the identification of t...
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| Veröffentlicht in: | Solar energy 2000-01, Vol.69 (4), p.343-350 |
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| creator | Veerachary, Mummadi Yadaiah, Narri |
| description | This paper presents an application of an Artificial Neural Network (ANN) for the identification of the optimal operating point of a PV supplied separately excited dc motor driving two different load torques. A gradient descent algorithm is used to train the ANN controller for the identification of the maximum power point of the Solar Cell Array (SCA) and gross mechanical energy operation of the combined system. The algorithm is developed based on matching of the SCA to the motor load through a buck-boost power converter so that the combined system can operate at the optimum point. The input parameter to the neural network is solar insolation and the output parameter is the converter chopping ratio corresponding to the maximum power output of the SCA or gross mechanical energy output of the combined PV system. The converter chopping ratios at different solar insolations are obtained from the ANN controller for two different load torques and are compared with computed values. |
| doi_str_mv | 10.1016/S0038-092X(00)00085-2 |
| format | Article |
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A gradient descent algorithm is used to train the ANN controller for the identification of the maximum power point of the Solar Cell Array (SCA) and gross mechanical energy operation of the combined system. The algorithm is developed based on matching of the SCA to the motor load through a buck-boost power converter so that the combined system can operate at the optimum point. The input parameter to the neural network is solar insolation and the output parameter is the converter chopping ratio corresponding to the maximum power output of the SCA or gross mechanical energy output of the combined PV system. 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The converter chopping ratios at different solar insolations are obtained from the ANN controller for two different load torques and are compared with computed values.</description><subject>Applied sciences</subject><subject>DC motors</subject><subject>Energy</subject><subject>Equipments, installations and applications</subject><subject>Exact sciences and technology</subject><subject>Motors</subject><subject>Natural energy</subject><subject>Neural networks</subject><subject>Photovoltaic cells</subject><subject>Photovoltaic conversion</subject><subject>Power converters</subject><subject>Solar cell arrays</subject><subject>Solar energy</subject><subject>Solar power generation</subject><issn>0038-092X</issn><issn>1471-1257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNqF0E1LHEEQBuBGDLhu8hOEIYiaw5iqmemvk8hqVBAj-IG3pqe7J7TOTo_ds4r_PrOuGMhBT3V56i3qJWQLYR8B2c8rgFLkIIu7PYAfACBoXqyRCVYccywoXyeTd7JBNlO6B0COgk8IP7y4yGqdnM16px-yPjy7mA1Rmwff_cmaELPL2ywt-r71ozmaZfMwhJi-ki-NbpP79jan5ObX8fXsND__fXI2OzzPTVWwIWeUoaXaWMMKZ8CUTLKaV9LYxmpmdCkoWhTWAlaCy9rJoqbWVVLUIFGKckp2V7l9DI8LlwY198m4ttWdC4ukeMWQCeDlKHc-lFhRWkoBI_z-H7wPi9iNX6iiRA5FxdiI6AqZGFKKrlF99HMdXxSCWrauXltXy0oVgHptfdyfku23cJ2MbpuoO-PTv2VaLvNHdrBibuzuybuokvGuM8766MygbPCfHPoLcY2TfA</recordid><startdate>20000101</startdate><enddate>20000101</enddate><creator>Veerachary, Mummadi</creator><creator>Yadaiah, Narri</creator><general>Elsevier Ltd</general><general>Elsevier</general><general>Pergamon Press Inc</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope><scope>7TC</scope></search><sort><creationdate>20000101</creationdate><title>ANN based peak power tracking for PV supplied DC motors</title><author>Veerachary, Mummadi ; Yadaiah, Narri</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c426t-6561d5acdc62ec0c3696b749cdfda6ca3851d18dd014879be92b5de498b091983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Applied sciences</topic><topic>DC motors</topic><topic>Energy</topic><topic>Equipments, installations and applications</topic><topic>Exact sciences and technology</topic><topic>Motors</topic><topic>Natural energy</topic><topic>Neural networks</topic><topic>Photovoltaic cells</topic><topic>Photovoltaic conversion</topic><topic>Power converters</topic><topic>Solar cell arrays</topic><topic>Solar energy</topic><topic>Solar power generation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Veerachary, Mummadi</creatorcontrib><creatorcontrib>Yadaiah, Narri</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><collection>Mechanical Engineering Abstracts</collection><jtitle>Solar energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Veerachary, Mummadi</au><au>Yadaiah, Narri</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ANN based peak power tracking for PV supplied DC motors</atitle><jtitle>Solar energy</jtitle><date>2000-01-01</date><risdate>2000</risdate><volume>69</volume><issue>4</issue><spage>343</spage><epage>350</epage><pages>343-350</pages><issn>0038-092X</issn><eissn>1471-1257</eissn><coden>SRENA4</coden><abstract>This paper presents an application of an Artificial Neural Network (ANN) for the identification of the optimal operating point of a PV supplied separately excited dc motor driving two different load torques. 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| identifier | ISSN: 0038-092X |
| ispartof | Solar energy, 2000-01, Vol.69 (4), p.343-350 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Applied sciences DC motors Energy Equipments, installations and applications Exact sciences and technology Motors Natural energy Neural networks Photovoltaic cells Photovoltaic conversion Power converters Solar cell arrays Solar energy Solar power generation |
| title | ANN based peak power tracking for PV supplied DC motors |
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