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Artificial Intelligence Based solar Radiation Predictive Model Using Weather Forecasts

Computers, Materials & Continua 2022年第4期71卷 109-124页

作者： Sathish Babu Pandu A.Sagai Francis Britto Pudi Sekhar P.Vijayarajan Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Mesfer Al Duhayyim Department of Electrical and Electronics Engineering University College of EngineeringPanruti607106India Department of Mechanical Engineering Rohini College of Engineering&TechnologyPalkulam629401India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyAndra Pradesh530046India Department of Electrical and Electronics Engineering University College of EngineeringBIT CampusTiruchirappalli620024India Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

solar energy has gained attention in the past two decades,since it is an effective renewable energy source that causes no harm to the *** irradiation prediction(SIP)is essential to plan,schedule,and manage photovoltaic power plants and grid-based power generation *** models have been proposed for SIP in the literature while such studies demand huge volumes of weather data about the target location for a lengthy period of *** this scenario,commonly available Artificial Intelligence(AI)technique can be trained over past values of irradiance as well as weatherrelated parameters such as temperature,humidity,wind speed,pressure,and ***,in current study,the authors aimed at developing a solar irradiance prediction model by integrating big data analytics with AI models(BDAAI-SIP)using weather forecasting *** order to perform long-term collection of weather data,Hadoop MapReduce tool is *** proposed solar irradiance prediction model operates on different ***,data preprocessing take place using various sub processes such as data conversion,missing value replacement,and data ***,Elman Neural Network(ENN),a type of feedforward neural network is also applied for predictive *** is divided into input layer,hidden layer,loadbearing layer,and output *** overcome the insufficiency of ENN in choosing the value of weights and hidden layer neuron count,Mayfly Optimization(MFO)algorithm is *** order to validate the performance of the proposed model,a series of experiments was *** experimental values infer that the proposed model outperformed other methods used for comparison.

关键词： solar irradiation prediction weather forecast artificial intelligence Elman neural network mayfly optimization

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