Empirical Analysis of Inter-Zonal Congestion in the Italian Electricity Market Using Multinomial Logistic Regression

Abstract

The increasing integration of renewable energy sources (RESs) into the Italian electricity market has heightened inter-zonal congestion challenges as power flows vary across importing and exporting zones. Utilizing a Multinomial Logistic Regression model as an empirical approach, this study investigates the key factors driving inter-zonal congestion between zonal pairs from 2021 to 2023, focusing on how local and neighboring zones’ RES generation (wind, solar, and hydropower) and demand dynamics impact congestion probabilities. The findings reveal that increased local RES generation generally reduces the likelihood of congestion for importing regions but increases it for exporting zones. Specifically, higher wind and solar production in importing zones like CNOR and CSUD alleviates congestion by reducing the need for imports, while in exporting zones, such as NORD and CALA, increased RES generation can exacerbate congestion due to higher export volumes. Hydropower production shows similar trends, with local production mitigating congestion in importing zones but increasing it in exporting zones. In addition to the effects of local generation and demand within each zonal pair, the generation and demand from neighboring zones also have a notable and statistically significant impact. Although their marginal effects tend to be smaller, the contributions from neighboring zones are essential for comprehending the overall congestion dynamics. These insights underscore the need for strategic RES placement to enhance market efficiency and minimize congestion risks across the Italian zonal electricity market.