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- W3010159544 abstract "The solar energy is a clean and renewable energy. Solar Photovoltaic renewable sources proving to be most beneficial with low-cost, so that number of PV plants is significantly growing. Today's solar plants are highly localized and unstructured. Around 14% of solar system face major fault every year therefore the management of photovoltaic systems is important for increase their efficiency. The system is implemented in two phases first one is monitoring followed by prediction which helps to reduce the energy loss. The solar monitoring phase collects and analyzes several constraints being evaluated by using sensors to calculate its panel level performance. Smart Monitoring system maintains track of electricity generation contents and regional temperature. The experimental results forecast the mistake finding as well as the panel's dead state with time parameters. Phase two deals with analyzing time-series of solar energy data for prediction using Hidden Markov Model (HMM). The model decides a prediction considering probabilistic relationship of the first value to next value in series. The predicted output is then compared with real-time output to increase accuracy of prediction." @default.
- W3010159544 created "2020-03-13" @default.
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- W3010159544 date "2018-05-01" @default.
- W3010159544 modified "2023-09-27" @default.
- W3010159544 title "Energy Prediction for Smart Solar Remote Monitoring System" @default.
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- W3010159544 doi "https://doi.org/10.1109/rteict42901.2018.9012503" @default.
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