A new solar radiation model for a power system reliability study

Abstract

The dwindling number of conventional power resources and its environmental impact has motivated a transition to renewable energy sources, such as solar power. Evaluating the reliability of solar power integration into power networks can help decision makers gauge the feasibility of their solar power projects. However, the stochastic and non-stationary nature of solar radiation is difficult to be modeled and can even hinder an accurate evaluation of reliability. A good solar model for accurately assessing solar-power-integrated systems should be able to retain the original statistical properties of the sampled solar radiation data. Therefore, this paper aims to develop a new robust and easy-to-use methodology for simulating solar radiation. The proposed model was compared with four other models, including the clearness index, auto-regressive moving average, and two probability-distribution-based models. Five statistical tests, namely, F-test, diurnal distributions, partial auto-correlation function (PACF), mean, and standard deviation, were performed for the comparison. The comparison results indicate that the proposed method effectively retains the statistical properties of the original data and outperforms all other models in the tests. Therefore, the proposed model can be used for assessing solar-power-integrated power systems.