Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …

A decomposition-clustering-ensemble (DCE) learning approach is proposed for solar
radiation forecasting in this paper. In the proposed DCE learning approach,(1) ensemble …

Accurate estimation of solar radiation components of a specific location has been one of the
most important issues of solar energy applications. In this paper, a new approach, named …

In today's scenario the rate of growth of information is expanding exponentially in the World
Wide Web. As a result, extracting valid and useful information from a huge data has become …

Short-term wind speed forecasting has become an important technology to utilize
sustainable energy, reduce the impact of wind power grid and improve the control of wind …

Due to the existing large-scale grid-connected photovoltaic (PV) power generation
installations, accurate PV power forecasting is critical to the safe and economical operation …

Solar irradiation is influenced by many meteorological features, which results in a complex
structure meaning its prediction has low efficiency and accuracy. The existing prediction …

Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search
(CS) algorithm is affected by the step size, this paper proposes a K-Means clustering …

Solar radiation prediction is significant for solar energy utilization. This paper presents
hybrid methods following the decomposition-prediction-reconfiguration paradigm using only …

In the optimal and economic operation of the power system, generation scheduling is an
essential task. Conventional short-term generation scheduling does not regard the huge …