Modelling the joint behaviour of electricity prices in interconnected markets

Abstract

The liberalization of energy markets worldwide during recent decades has introduced severe implications on the price formation in these markets. Especially within the European day-ahead electricity markets, increased physical connections between different market areas and a joint effort on optimizing the aggregate social welfare have led to highly connected markets. Consequently, observing the exact same hourly day-ahead prices for two or more interconnected electricity markets in Europe happens frequently. This affects the modeling of such prices and in turn the valuation of derivatives written on prices from such market areas. In this paper, we propose a joint model for day-ahead electricity prices in interconnected markets composed of a combination of transformed Ornstein-Uhlenbeck processes. We discuss the properties of the model and propose an estimation procedure based on filtering techniques. Furthermore, the properties of the model reveal that analytical prices are attainable for e.g. forwards and spread options.

Intermittently Coupled Electricity Markets

“…They show that as his aversion to ambiguity increases, his trading activity, and consequently his inventory exposure, decreases in both locations. Christensen and Benth (2020) introduce regime-switching in their model for potentially coupled electricity prices using a latent uni-variate process that allows for seasonal behaviour. The parameters of this process are estimated from given market data via particle filtering.…”

A survey of electricity spot and futures price models for risk management applications

“…In 2020, Christensen and Benth [63] were interested in representing electricity prices in two interconnected countries. The authors sought to account for interconnectedness, that is, the non-zero probability event when prices are identical.…”

“…As interconnections between markets develop, models develop to depict previously ignored facts, such as the equality of prices in multiple countries over multiple time periods. The recent work of Gardini et al [102,101] and Christensen and Benth [63] are notable advances in incorporating the connected nature of markets into modeling. Along the same idea, the increase in the proportion of renewable energies in the production of electricity pushes us to develop the depiction of the dependence of electricity prices on exogenous uncertainties.…”

An Efficient Unified Approach for Spread Option Pricing in a Copula Market Model

“…[4] and [27] present new methodologies for the computation of the price of spread options, while [21] provides an assessment of spread option price sensitivities through Malliavin calculus. Further enrichments to the spread option framework are introduced by [26] and [25]. The former proposes a joint model for day-ahead electricity prices in interconnected markets and observes that the model yields analytical prices.…”