A Multivariate Dependence Analysis for Electricity Prices, Demand and Renewable Energy Sources

TL;DR

This study uses a multivariate copula model to analyze the complex dependencies between electricity prices, demand, and renewable energy sources in Germany, emphasizing tail dependence and temporal dynamics.

Contribution

It introduces tailored tail dependence measures for multivariate extreme scenarios and applies them to study the dynamic interdependencies in the German electricity market.

Findings

Strong association between prices, renewable energy, and demand within a day

Dependencies vary over time and are significant in extreme scenarios

Provides insights for policy incentives promoting green energy

Abstract

This paper examines the dependence between electricity prices, demand, and renewable energy sources by means of a multivariate copula model {while studying Germany, the widest studied market in Europe}. The inter-dependencies are investigated in-depth and monitored over time, with particular emphasis on the tail behavior. To this end, suitable tail dependence measures are introduced to take into account a multivariate extreme scenario appropriately identified {through the} Kendall's distribution function. The empirical evidence demonstrates a strong association between electricity prices, renewable energy sources, and demand within a day and over the studied years. Hence, this analysis provides guidance for further and different incentives for promoting green energy generation while considering the time-varying dependencies of the involved variables