Practical approach for sub-hourly and hourly prediction of PV power output
This paper proposes a practical and reliable approach for the prediction of photovoltaic power generation using solar irradiance as the input. Solar irradiance is modeled as the sum of a deterministic component and a Gaussian noise signal. The solar irradiance on a partly cloudy day is forecasted by...
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| creator | Hassanzadeh, M Etezadi-Amoli, M Fadali, M S |
| description | This paper proposes a practical and reliable approach for the prediction of photovoltaic power generation using solar irradiance as the input. Solar irradiance is modeled as the sum of a deterministic component and a Gaussian noise signal. The solar irradiance on a partly cloudy day is forecasted by Kalman filtering. The shaping filter for the Gaussian noise is calculated using spectral analysis and an autoregressive moving average (ARMA) model. The results of the two approaches are compared with the measured irradiance at a PV generating facility within an electric utility company. The results show that better estimates are obtained using spectral analysis than those obtained with the ARMA model, particularly for lower sampling rates. |
| doi_str_mv | 10.1109/NAPS.2010.5618944 |
| format | Conference Proceeding |
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The results show that better estimates are obtained using spectral analysis than those obtained with the ARMA model, particularly for lower sampling rates.</description><subject>Forecasting</subject><subject>Kalman filtering</subject><subject>Kalman filters</subject><subject>Mathematical model</subject><subject>Photovoltaic</subject><subject>power prediction</subject><subject>Predictive models</subject><subject>Radiation effects</subject><subject>shaping filter</subject><subject>Solar energy</subject><subject>Solar power generation</subject><subject>spectral analysis</subject><isbn>9781424480463</isbn><isbn>1424480469</isbn><isbn>9781424480456</isbn><isbn>9781424480470</isbn><isbn>1424480450</isbn><isbn>1424480477</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkE1LxDAYhCMiKGt_gHjJH-iaN3mTTY7L4sfKogU_rkvSJmylbkLaIvvvLdiLc5l5YJjDEHIDbAnAzN3LunpbcjahVKAN4hkpzEoDckTNUKrzf6zEJSn6_otNklJLba7Ic5VtPbS17ahNKUdbH2iImfajKw9xzN2J2mND55iyb9qpHo80Blp90hR_fKZxHNI4XJOLYLveF7MvyMfD_fvmqdy9Pm43611Zc4ZDCTUqAAgejGskKGeUVY4hMs0tyhWzGBovAYVwHgOwBkFrHhCNlEFzsSC3f7ut936fcvtt82k_PyB-AeZ8Te4</recordid><startdate>201009</startdate><enddate>201009</enddate><creator>Hassanzadeh, M</creator><creator>Etezadi-Amoli, M</creator><creator>Fadali, M S</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201009</creationdate><title>Practical approach for sub-hourly and hourly prediction of PV power output</title><author>Hassanzadeh, M ; Etezadi-Amoli, M ; Fadali, M S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c204t-1c46111fe19bd516b96a6b044082a4570a4fde51433be4f10d41882f44955f823</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Forecasting</topic><topic>Kalman filtering</topic><topic>Kalman filters</topic><topic>Mathematical model</topic><topic>Photovoltaic</topic><topic>power prediction</topic><topic>Predictive models</topic><topic>Radiation effects</topic><topic>shaping filter</topic><topic>Solar energy</topic><topic>Solar power generation</topic><topic>spectral analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Hassanzadeh, M</creatorcontrib><creatorcontrib>Etezadi-Amoli, M</creatorcontrib><creatorcontrib>Fadali, M S</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>Hassanzadeh, M</au><au>Etezadi-Amoli, M</au><au>Fadali, M S</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Practical approach for sub-hourly and hourly prediction of PV power output</atitle><btitle>North American Power Symposium 2010</btitle><stitle>NAPS</stitle><date>2010-09</date><risdate>2010</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><isbn>9781424480463</isbn><isbn>1424480469</isbn><eisbn>9781424480456</eisbn><eisbn>9781424480470</eisbn><eisbn>1424480450</eisbn><eisbn>1424480477</eisbn><abstract>This paper proposes a practical and reliable approach for the prediction of photovoltaic power generation using solar irradiance as the input. Solar irradiance is modeled as the sum of a deterministic component and a Gaussian noise signal. The solar irradiance on a partly cloudy day is forecasted by Kalman filtering. The shaping filter for the Gaussian noise is calculated using spectral analysis and an autoregressive moving average (ARMA) model. The results of the two approaches are compared with the measured irradiance at a PV generating facility within an electric utility company. The results show that better estimates are obtained using spectral analysis than those obtained with the ARMA model, particularly for lower sampling rates.</abstract><pub>IEEE</pub><doi>10.1109/NAPS.2010.5618944</doi><tpages>5</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Forecasting Kalman filtering Kalman filters Mathematical model Photovoltaic power prediction Predictive models Radiation effects shaping filter Solar energy Solar power generation spectral analysis |
| title | Practical approach for sub-hourly and hourly prediction of PV power output |
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