20.500.12556/DKUM-66955 Intra-minute cloud passing forecasting based on a low cost iot sensor - a solution for smoothing the output power of PV power plants Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be reduced effectively by proper short-term cloud passing forecasting and suitable PV power plant output power control. This paper proposes a low-cost Internet of Things (IoT)-based solution for intra-minute cloud passing forecasting. The hardware consists of a Raspberry PI Model B 3 with a WiFi connection and an OmniVision OV5647 sensor with a mounted wide-angle lens, a circular polarizing (CPL) filter and a natural density (ND) filter. The completely new algorithm for cloud passing forecasting uses the green and blue colors in the photo to determine the position of the Sun, to recognize the clouds, and to predict their movement. The image processing is performed in several stages, considering selectively only a small part of the photo relevant to the movement of the clouds in the vicinity of the Sun in the next minute. The proposed algorithm is compact, fast and suitable for implementation on low cost processors with low computation power. The speed of the cloud parts closest to the Sun is used to predict when the clouds will cover the Sun. WiFi communication is used to transmit this data to the PV power plant control system in order to decrease the output power slowly and smoothly. photovoltaic power plant cloud passing forecasting algorithm sensor Raspberry Pi camera wide-angle lens optical filters internet of things fotovoltaična elektrarna napovedovanje premikanja oblakov algoritmi senzorji Raspberry Pi kamera širokokotni objektiv optični filtri internet stvari true true true Angleški jezik Slovenski jezik Znanstveno delo 2017-07-20 12:35:48 2017-07-20 12:36:55 2022-08-01 13:23:13 2019-07-11 15:08:26 2017 0 0 str. 1-20 št. 5 Letn. 17 2017 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 621.31 10176278 20570134 10.3390/s17051116 URN:SI:UM:DK:NARQE8IH Sensors_2017_Sukic,_Gtumberger_Intra-Minute_Cloud_Passing_Forecasting_Based_on_a_Low_Cost_IoT_Sensor—A_Solution_for_Smoothing_the_Output.pdf Sensors_2017_Sukic,_Gtumberger_Intra-Minute_Cloud_Passing_Forecasting_Based_on_a_Low_Cost_IoT_Sensor—A_Solution_for_Smoothing_the_Output.pdf 1 8D737428561C4987FC7A1BDE4876068A 6ea83c996df79c5bed9cf20dee9b135e0201ac4dbfeb879f99ffe63a59ee0bef 6fb8ee64-7c0e-11eb-bb7a-00155d0001ca 20.500.12556/dkum/8544501c-1c7a-4606-8601-0789c2321860 https://dk.um.si/Dokument.php?lang=slv&id=114400 http://www.mdpi.com/1424-8220/17/5/1116 1 https://dk.um.si/Dokument.php?lang=slv&id=114399 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0