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    FORECASTING OF SOLAR RADIATION FOR SOLAR SYSTEM UNDER DIFFERENT CLIMATIC CONDITION
    (International Organization on 'Technical and Physical Problems of Engineering', 2023) Al Musawi, Sura Saadi; Hamodat, Zaid Musaab; Basheer, Ayman Ghassan
    Sun oriented energy is a perfect, plentiful, and sustainable power source. The utilization of photovoltaic boards to produce power from sun-based energy is turning out to be more well known. Since sunlight-based energy is discontinuous, the produced power is variable. This vulnerability could be decreased by using energy stockpiling frameworks and exact sunlight-based power determining. The objective of this proposal is to carry out a sun-oriented figure module as a component of an improved Energy Management System (EMS). Measurable techniques, sky imagers, satellite imaging, and mathematical climate forecast are among the strategies examined (NWP). To meet EMS necessities, counterfeit brain organizations (ANNs), a subset of factual strategies, were picked as a forecast strategy. For the EMS to work appropriately, exact anticipating in the momentary expectation skyline is required. The expectation skyline is how much time coming down the line for which an expectation is required. Additionally, the paragraph mentions the Temporal Convolutional Network (TCN) architecture, which uses temporal convolutions to process sequential data and has shown promise for time-series analysis tasks. Albeit every one of the techniques referenced above give OK execution, TCN engineering gives additional promising outcomes. To enhance the accuracy of solar radiation predictions, the possibility of dividing the dataset into sub-datasets based on radiant and overcast weather conditions and implementing a dedicated prediction module for each sub-dataset is being investigated. The outcomes show that bunching the dataset further develops expectation exactness for all models. Besides, recreation results on datasets from various geological areas with fluctuating environment conditions show that forecast exactness is higher in regions with additional steady climate and bright days. © 2023, International Organization on 'Technical and Physical Problems of Engineering'. All rights reserved.