This website brings together articles about the financial aspects of energy markets. The main topics are risk-management, price modeling, valuation, optimization and energy market design.
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Published in WorldPower 2009
Authors: Henk Sjoerd Los, Hans van Dijken, Cyriel de Jong. KYOS Energy Consulting
The large investments in new power generation assets illustrate the need for proper financial plant evaluations. Traditional net present value (NPV) analysis disregards the flexibility to adjust production decisions to market developments, and thus underestimate true plant value. On the other hand, methods treating power plants as a series of spread options ignore technical and contractual restrictions, and thus overestimate true plant value. In this article we demonstrate the use of volatility and cointegration to incorporate market fundamentals and calculate dynamic, yet reasonable, spread levels and power plant values. A practical case study demonstrates how various technical and market constraints impact plant value. It also demonstrates that plant value may contain considerable option value, but 64% less than with the usual real option approaches. We conclude with an analysis of static and dynamic hedges affecting risk and return profiles
The thesis deals with fitting, modeling and forecasting of the retail consumer demand for natural gas. This is important and has a potential for numerous applications: gas portfolio risk management, keeping the storage system in balance, using it for valuation of swing contracts, gas consumption planning and other. Retail gas demand is weather sensitive and therefore can be better explained, compared to the demand from industries or power plants. A relationship between demand for the natural gas, weather and prices is of key focus. Such a relationship is studied by different tests and models for the demand of the natural gas, spot prices and weather are proposed. Econometric approaches are used to prove that spot or forward gas prices do not effect gas demand in a short-term horizon. Two models for residential natural gas demand are proposed. These are used to forecast demand for natural gas of residential consumers. Two weather models are considered and used to simulate gas demand. A comparison and discussion is provided. Data are obtained from three energy companies in the Netherlands and Belgium.