In the context of the energy transition, the increasing penetration of renewable sources, the electrification process and the simultaneous decommissioning of obsolete thermoelectric plants focus increasingly on the security of energy supply, which must be analyzed considering the degree of uncertainty associated with the quantities involved.

Hence the need to carry out adequacy analyses adopting a probabilistic approach, in which the satisfaction of energy demand in a given electricity system is evaluated for a broad range of variation in exogenous variables. With the aim of addressing this need, a new methodology for evaluating generation adequacy indices was developed and implemented based on two tools previously developed at RSE: SPOPSI (Stochastic Power Profile SImulator), which is used to generate stochastic hourly profiles of photovoltaic and wind load and generation from weather and climate variables, and sMTSIM (stochastic Mid Term SIMulator), which solves hourly economic dispatch with zonal resolution over an annual horizon.

The additional features to be implemented in the new methodology were identified from an analysis of the needs and state of the art in adequacy assessments, based primarily on ENTSO-E’s European Resource Adequacy Assessment (ERAA) methodology and that used by the Italian TSO Terna. The resulting methodology is based on the Monte Carlo (MC) approach, which consists of performing the adequacy analysis for a very large number of case histories.

Each MC year is defined by the stochastic profiles generated by SPOPSI and by the the hourly profiles, also stochastic, of run-of-river hydropower production, water inputs to reservoir and reservoir plants, and unplanned failures. Adequacy is assessed using both classical indicators, such as Expected Energy Not Served (EENS) and Loss Of Load Expectation (LOLE), and innovative indicators, aimed at highlighting the impact of generation flexibility on adequacy. The analysis model was applied to a 2030 Italian energy scenario in order to exemplify the implemented methodology.