This issue of The Journal of Energy Markets demonstrates not only the complex challenges of modeling energy prices but also the close association of technology and operational performance in price formation and valuation. This interaction of technology, operations and prices is a feature distinctive to energy, which promotes a rich set of research topics.
In “Stochastic modeling of photovoltaic power generation and electricity prices”, the first paper in this issue, Fred Espen Benth and Noor ’Adilah Ibrahim propose a new stochastic model for the daily peak production of photovoltaic (PV) power in Germany. They apply sun intensity as a seasonal function and model the deseasonalized data using an autoregressive process with skewed normally distributed noise and seasonal variance to explain the dynamics. As expected, power spot prices are negatively related to PV production. To extend these results, the authors analyze some virtual power plant derivatives and energy quanto options for PV output and electricity price dynamics.
Electricity transmission infrastructure features strongly in our second paper. “Risk and abnormal returns in markets for congestion revenue rights” by Rimvydas Baltaduonis, Samuel Bonar, John Carnes and Erin Mastrangelo looks at the locational pricing of congestion by means of financial transmission rights (FTRs). Both hedging and speculation on these FTRs are considered. The paper develops a novel methodology for estimating the systematic risk of individual FTRs and detecting the presence of abnormal returns among these financial instruments. This paper applies the proposed methodology to all auctioned transmission rights in California from 2009 to 2015.
Storage facilities are considered in the issue’s third paper, “A forward dynamic optimization strategy under contango storage arbitrage with frictions” by Behzad Ghafouri and Matt Davison. The authors seek to explain and improve the offshore oil storage trade observed in a contango market using a forward dynamic optimization strategy. The strategy formulation is developed in terms of trades in forward contracts and contrasted with the published research. The impact of the forward curve dynamics is studied by examining trading decisions based on the realized slope and mean level of the forward curve. The effects of initial conditions, the frequency with which the position is readjusted, and the storage costs are also examined.
Our fourth and final paper in this issue, “A three-factor model on the natural gas forward curve including temperature forecasts” by Christoph Jablonowski and Markus Schicks, is also on the topic of forward curve modeling, but this time in the context of gas and weather forecasting. The emphasis here is on the use of temperature forecasts in a three-factor model that jointly describes both natural gas forward prices and temperature forecast dynamics. The factors are determined by principal component analysis on the forward curve of the Dutch natural gas trading hub title transfer facility, together with Amsterdam temperature forecasts. The model is significant and reflects a useful formulation of the evident value of temperature forecasts in forward gas pricing.
We are pleased to present this collection of papers, all of which contain innovative modeling and practical applications. The relationships between the main energy commodities – oil, gas and power – and multiple fundamental factors and physical infrastructures are clearly demonstrated here.
Derek W. Bunn
London Business School
This paper proposes a stochastic model for the maximal production of PV power on a daily basis, based on data from three transmission system operators in Germany.
This paper develops a novel methodology for estimating the systematic risk of individual financial transmission rights and detecting the presence of abnormal returns among these financial instruments.
The goal of this paper is to explain and improve the offshore oil storage trade observed in a contango market using a forward dynamic optimization strategy. The strategy is developed using trades in forward contracts and contrasted with the literature.
This paper introduces a three-factor model that jointly describes both natural gas forward prices and temperature forecast dynamics.