Meteorological probabilistic models for power system adequacy and resiliency assessment

The consequence of increasing the use of large amount of renewable non programmable generation capability (wind and PV systems) as well as extreme weather events or, more in general, changing environmental conditions, will have significant impacts on future power systems, in particular on the power system adequacy and on the resiliency assessment. Climate change has changed and will continue to affect both the energy demand and the available generation capacity. For instance, high demand for extreme heat or cold phenomena can determine the presence of critical operating conditions from the point of view of power system adequacy. Meteorological variables, therefore, are essential inputs to study key dimensions that must be kept under close observation to correctly manage the power systems. In this context, the aim of this paper is to propose models to generate profiles of the main meteorological variables (irradiance, wind speed, ambient temperature) considering their interdependence, suitable for adequacy and resilience analysis. In this paper, two models are proposed for the generation of the hourly daily radiation profiles based on statistical data: one is based on data probability distributions and the other on the clear sky solar radiation. Moreover, since climatic variables are interdependent, to generate the hourly temperature profiles a model based on the irradiance profile and the monthly mean daily minimum and maximum hourly temperatures is developed. The temperature is generated starting from the measured data and from irradiance data generated using the two approaches here proposed. Then, the persistence of low and high temperature situations and number of consecutive clear and cloudy days considering measured and simulated data is analysed.