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Power generation forecasting model for photovoltaic array based on generic algorithm and BP neural network
High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the so...
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| creator | Zhengqiu Yang Yapei Cao Jiapeng Xiu |
| description | High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the solar power station. This paper focuses on the short-term forecasting method which aims at forecasting power generation in five minutes. This paper uses BP neural network(BP-NN) as the basic forecasting model and applies generic algorithm(GA) to optimize the weights and thresholds of BP-NN. The experimental results show that, the prediction effect of this method is ideal. |
| doi_str_mv | 10.1109/CCIS.2014.7175764 |
| format | conference_proceeding |
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The experimental results show that, the prediction effect of this method is ideal.</description><subject>BP Neural network</subject><subject>Forecasting</subject><subject>Genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Neural networks</subject><subject>Photovoltaic generation (PV)</subject><subject>Photovoltaic systems</subject><subject>Predictive models</subject><subject>Short-term forecasting</subject><issn>2376-5933</issn><issn>2376-595X</issn><isbn>1479947202</isbn><isbn>9781479947201</isbn><isbn>1479944394</isbn><isbn>9781479947195</isbn><isbn>1479947199</isbn><isbn>9781479944392</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9kNtKw0AYhNcTWGsfQLzZF0jd8-FSg4dCwYIK3pVN9k-bmmbLZrX07U21ejUwwzcMg9AVJWNKib3J88nLmBEqxppqqZU4QhdUaGuF4FYcowHjWmXSyveTv0Azwk7_A87P0ajrVoQQapVlhg3Qaha2EPECWogu1aHFVYhQui7V7QKvg4dm7-DNMqTwFZrk6hK7GN0OF64Dj3viB97bzSLEOi3X2LUe381wC5_RNb2kbYgfl-isck0Ho4MO0dvD_Wv-lE2fHyf57TSrmTYpqwznwitbGvCS8RIId_1cJgvliVSlolwWzjglClMoo31lS60LQaQFbTnlQ3T921sDwHwT67WLu_nhM_4NIjldUw</recordid><startdate>20141101</startdate><enddate>20141101</enddate><creator>Zhengqiu Yang</creator><creator>Yapei Cao</creator><creator>Jiapeng Xiu</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20141101</creationdate><title>Power generation forecasting model for photovoltaic array based on generic algorithm and BP neural network</title><author>Zhengqiu Yang ; Yapei Cao ; Jiapeng Xiu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i278t-f8334d69c8ed523ce03a19625b6d056c6135ba8a64b8b687df9c77b4059e79313</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>BP Neural network</topic><topic>Forecasting</topic><topic>Genetic algorithm</topic><topic>Genetic algorithms</topic><topic>Neural networks</topic><topic>Photovoltaic generation (PV)</topic><topic>Photovoltaic systems</topic><topic>Predictive models</topic><topic>Short-term forecasting</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhengqiu Yang</creatorcontrib><creatorcontrib>Yapei Cao</creatorcontrib><creatorcontrib>Jiapeng Xiu</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</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>Zhengqiu Yang</au><au>Yapei Cao</au><au>Jiapeng Xiu</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Power generation forecasting model for photovoltaic array based on generic algorithm and BP neural network</atitle><btitle>2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems</btitle><stitle>CCIS</stitle><date>2014-11-01</date><risdate>2014</risdate><spage>380</spage><epage>383</epage><pages>380-383</pages><issn>2376-5933</issn><eissn>2376-595X</eissn><isbn>1479947202</isbn><isbn>9781479947201</isbn><eisbn>1479944394</eisbn><eisbn>9781479947195</eisbn><eisbn>1479947199</eisbn><eisbn>9781479944392</eisbn><abstract>High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the solar power station. This paper focuses on the short-term forecasting method which aims at forecasting power generation in five minutes. This paper uses BP neural network(BP-NN) as the basic forecasting model and applies generic algorithm(GA) to optimize the weights and thresholds of BP-NN. The experimental results show that, the prediction effect of this method is ideal.</abstract><pub>IEEE</pub><doi>10.1109/CCIS.2014.7175764</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 2376-5933 |
| ispartof | 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, 2014, p.380-383 |
| issn | 2376-5933 2376-595X |
| language | eng |
| recordid | cdi_ieee_primary_7175764 |
| source | IEEE Xplore All Conference Series |
| subjects | BP Neural network Forecasting Genetic algorithm Genetic algorithms Neural networks Photovoltaic generation (PV) Photovoltaic systems Predictive models Short-term forecasting |
| title | Power generation forecasting model for photovoltaic array based on generic algorithm and BP neural network |
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