Solar energy prediction for communicating sensors

What is it about?

The prediction of the solar radiation and energy availability is a critical issue, as the amount of the harvested energy may vary over time. In this study, a novel solar radiation and energy predictor (Solar Energy Predictor for Communicating Sensors: SEPCS) is proposed. This prediction model uses past energy observations to forecast future energy availability in short term. To assess the performance of the proposed algorithm, authors used database providing the solar radiation evolution for one year. Then, a comparative performance evaluation shows that the SEPCS predictor significantly outperforms the state-of-the-art energy predictors, by decreasing the average prediction error from 28 to 6.5%.

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Why is it important?

We propose a Solar Energy Predictor for Communicating Sensors (SEPCS), a novel real-time solar energy prediction algorithm based on the EWMA method. SEPCS predictor considers the current weather conditions to accurately estimate solar power.

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