000 | 04488nam a22005895i 4500 | ||
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001 | 978-3-031-02505-1 | ||
003 | DE-He213 | ||
005 | 20240730163945.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2020 sz | s |||| 0|eng d | ||
020 |
_a9783031025051 _9978-3-031-02505-1 |
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024 | 7 |
_a10.1007/978-3-031-02505-1 _2doi |
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050 | 4 | _aTK1-9971 | |
072 | 7 |
_aTHR _2bicssc |
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072 | 7 |
_aTEC007000 _2bisacsh |
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072 | 7 |
_aTHR _2thema |
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082 | 0 | 4 |
_a621.3 _223 |
100 | 1 |
_aRao, Sunil. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981354 |
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245 | 1 | 0 |
_aMachine Learning for Solar Array Monitoring, Optimization, and Control _h[electronic resource] / _cby Sunil Rao, Sameeksha Katoch, Vivek Narayanaswamy, Gowtham Muniraju, Cihan Tepedelenlioglu, Andreas Spanias. |
250 | _a1st ed. 2020. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
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300 |
_aIX, 81 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSynthesis Lectures on Power Electronics, _x1931-9533 |
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505 | 0 | _aAcknowledgments -- Introduction -- Solar Array Research Testbed -- Fault Classification Using Machine Learning -- Shading Prediction for Power Optimization -- Topology Reconfiguration Using Neural Networks -- Summary -- Bibliography -- Authors' Biographies . | |
520 | _aThe efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance and help optimize the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading. | ||
650 | 0 |
_aElectrical engineering. _981355 |
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650 | 0 |
_aElectric power production. _927574 |
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650 | 0 |
_aElectronics. _93425 |
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650 | 1 | 4 |
_aElectrical and Electronic Engineering. _981356 |
650 | 2 | 4 |
_aElectrical Power Engineering. _931821 |
650 | 2 | 4 |
_aMechanical Power Engineering. _932122 |
650 | 2 | 4 |
_aElectronics and Microelectronics, Instrumentation. _932249 |
700 | 1 |
_aKatoch, Sameeksha. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981357 |
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700 | 1 |
_aNarayanaswamy, Vivek. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981358 |
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700 | 1 |
_aMuniraju, Gowtham. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981359 |
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700 | 1 |
_aTepedelenlioglu, Cihan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981360 |
|
700 | 1 |
_aSpanias, Andreas. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981361 |
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710 | 2 |
_aSpringerLink (Online service) _981362 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031003264 |
776 | 0 | 8 |
_iPrinted edition: _z9783031013775 |
776 | 0 | 8 |
_iPrinted edition: _z9783031036330 |
830 | 0 |
_aSynthesis Lectures on Power Electronics, _x1931-9533 _981363 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-02505-1 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c85162 _d85162 |