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Advanced forecasting methods for renewable generation and loads in modern power systems

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Table 1.1 associates forecasting methods, classified in terms of lead times, to corresponding needs [28]
Figure 2.3 - Cross-correlation coefficients between solar irradiance (a), clearness index (b) and the available weather variables
Figure 2.4 - Next day PV power forecasts obtained through the Bayesian approaches, the PM method (solid lines), and actual PV power (dash line) on (a) 21
Figure 2.5 - Next day PV power forecasts obtained through the Bayesian approaches, the PM method (solid lines), and actual PV power (dash line) on (a) 29
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Hybrid approaches P ROBABILISTIC METHODS FOR SHORT TERM PHOTOVOLTAIC POWER Assessment of the quality of forecasts S HORT TERM INDUSTRIAL LOAD FORECASTING METHODS : STATE OF Assessment of the quality of reactive power forecasts Assessment of mixture Inverse Burr Inverse Weibull G OODNESS OF FITTING INDICES

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