Understanding relationships with the aggregate zonal imbalance using copulas

In the Italian electricity market, we analyze the Aggregate Zonal Imbalance, which is the algebraic sum, changed in sign, of the amount of energy procured by the Italian national Transmission and System Operator in the Dispatching Services Market at a given time in the northern Italian electricity macro-zone. Specifically, we determine possible relationships among the Aggregate Zonal Imbalances and other variables of interest in electricity markets, including renewable sources. From a methodological point of view, we use a multivariate model for time series that combines the marginal behavior with copula-type models. As a result, the flexibility of a copula approach will allow identifying the nature of non-linear linkages among the Aggregate Zonal Imbalance and other variables such as forecasted demand, forecasted wind and solar PV generation. In this respect, novel ways to measure dependence and association among random variates are adopted. Our results indicate a clear association between the Aggregate Zonal Imbalance and Forecasted Solar PV generation, and a weaker relationship with the other considered variables. We find this result both in terms of pairwise Spearman’s and Kendall’s correlations and in terms of upper and lower tail dependence. The analysis concludes with the proposal of new indicators to detect association among random vectors, which could identify the more important features driving imbalances.