Abstract
Solar energy is one of the most important renewable energies, with many advantages over other sources. Many parameters affect the electricity generation from solar plants. This paper aims to study the influence of these parameters on predicting solar radiation and electric energy produced in the Salt-Jordan region (Middle East) using long short-term memory (LSTM) and Adaptive Network-based Fuzzy Inference System (ANFIS) models. The data relating to 24 meteorological parameters for nearly the past five years were downloaded from the MeteoBleu database. The results show that the influence of parameters on solar radiation varies according to the season. The forecasting using ANFIS provides better results when the parameter correlation with solar radiation is high (i.e., Pearson Correlation Coefficient PCC between 0.95 and 1). In comparison, the LSTM neural network shows better results when correlation is low (PCC in the range 0.5–0.8). The obtained RMSE varies from 0.04 to 0.8 depending on the season and used parameters; new meteorological parameters influencing solar radiation are also investigated.
Highlights
Solar irradiation is the total quantity of electromagnetic irradiation emitted by the sun over a frequency range
Twenty-four meteorological parameters rameters are considered in the prediction process, for five different are considered in the prediction process, selected for selected five different scenarios
A Pearson correlation coefficient (PCC) algorithm is used to indicate the most influencing parameters correlated with solar radiation to facilitate the training process with Long Short-Term Memory (LSTM) and Adaptive Networkbased Fuzzy Inference System (ANFIS)
Summary
Solar irradiation is the total quantity of electromagnetic irradiation emitted by the sun over a frequency range. Solar energy is one of the most abundant and adaptable renewable energy sources; it can be used directly or indirectly. Among all the non-conventional energy sources, solar energy is the greatest option since it is both costeffective and ecologically friendly [1–4]. According to the Renewable Energy Policy Network for the Twenty-First Century, solar energy will reach a total production of 8000 GWatt in 2050 [8–11]. Solar irradiation is variable and intermittent, leading to significant output-power variability; this limit represents a serious challenge for the generated photovoltaic energy (PV) that must be continuously fed into the grid [4,12,13]. Solar and wind sources are suitable for mega-project investments in this field. Before starting the design of any renewable energy production plant, the factors that influence solar energy production must be studied
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
