Renewable energy forecasting is a key for efficient resource use in terms of power generation and safe grid control. In this study, we investigated short-term statistical model with 1 to 3 h horizons using photovoltaic operation data from 215 plants throughout South Korea. A vector autoregression (VAR) model-based regional system proposed seven clusters This method showed better predictability ...

This study proposes a method to identify factor-augmented vector autoregression models without imposing uncorrelatedness or any timing restrictions among observed and unobserved factors in the system. To this end, we utilize changes unconditional shock variances following Rigobon (2003). The proposed can incorporate both structural system allows contemporaneous matrix be fully unrestricted. We ...

We provide an accessible introduction to graph-theoretic methods for causal analysis. Building on the work of Swanson and Granger (Journal of the American Statistical Association, Vol. 92, pp. 357–367, 1997), and generalizing to a larger class of models, we show how to apply graph-theoretic methods to selecting the causal order for a structural vector autoregression (SVAR). We evaluate the PC (...

This paper proposes a fully nonparametric test for cointegrating rank which does not require estimation of a vector autoregressive model. The test exploits the fact that the degeneracy in the moment matrix of the variables with mixed integration order corresponds to the notion of cointegration. With an appropriate standardization, the test statistics are shown to have a nuisance parameter free ...

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