IoT based Solar Power Forecasting using AMA-ELM Technique

Forecasting solar energy is essential for efficient grid management and integrating renewable energy sources into the electrical system. With the use of an extreme learning machine (ELM) and an adaptive moving average filter, we suggest a unique method for predicting solar power. The solar power time series' dynamic properties are captured by the adaptive moving average filter, which is used to preprocess the data. The solar power production prediction is then made using the ELM, a quick and effective machine learning technique. The preprocessed data is used to train the ELM, which then uses this knowledge to discover the nonlinear correlations between the input characteristics and solar power production.