Abstract
In this paper, Monte Carlo simulation models have been used to forecast the expected amount of energy production from photovoltaic panels. Two MC models have been proposed with traditional Monte Carlo method as their backbone. Model-1 combines the locally weighted scatterplot smoothing (LOESS) with simple Monte Carlo simulation. Model-2 is derived from the first model, and weather forecast data is used as an exogenous input. Also, the effect of weather is considered on traditional MC simulation and compared with Model-2. Using Model-2, the error between generated and predicted data is found to be the least. Results have been generated using Python and are discussed with inference in the manuscript.
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Seth, G., Prithvi, K.A., Paruthi, A., Jain, S., Soni, U. (2019). Prediction of PhotoVoltaic Power Generation Using Monte Carlo Simulation. In: Jain, L., E. Balas, V., Johri, P. (eds) Data and Communication Networks. Advances in Intelligent Systems and Computing, vol 847. Springer, Singapore. https://doi.org/10.1007/978-981-13-2254-9_25
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DOI: https://doi.org/10.1007/978-981-13-2254-9_25
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