<![CDATA["Serving the energy market" - Articles - Valuation]]> http://www.erasmusenergy.com en-us N/A dejong@kyos.com Sun, 05 Feb 2012 14:58:33 CET 20 <![CDATA[The value of starting up the power plant]]> http://www.erasmusenergy.com/articles/192/1/The-value-of-starting-up-the-power-plant/Page1.html Keywords: power plant valuation, VPP, plant start, dynamic programming, Monte Carlo simulations, least squares Monte Carlo
Published in: World Power
Publication year: 2010
Co-author 1: Dirk van Abbema, ING Bank
Co-author 2: Henk Sjoerd Los, KYOS Energy Consulting
Co-author 3: Cyriel de Jong, KYOS Energy Consulting

Gas-fired power plants provide the primary source of production flexibility in many power markets. An economically optimal use of the start-stop flexibility of gas plants is paramount to retrieving the maximum value from the asset. With the increasing penetration of wind power, this flexibility will become essential to balance the system. While starts and stops allow the owner to choose the production hours with the largest margin, they are also associated with various explicit and implicit costs. In this article we demonstrate the impact of various start-stop constraints and costs. This impact analysis is possible by applying advanced techniques for generating realistic Monte Carlo price simulations in combination with techniques for optimizing the production pattern.

An important insight that we gain is that different ways to limit starts lead to subtle differences in the actual use of the power plant and the corresponding value. We also find that the common modeling assumption of having perfect foresight about the future spark spreads may lead to a significant overstatement of plant value. This latter result contrasts our previous belief [Los et al, 2009], and statements of some other researchers [cf Clewlow et al, 2009] who claim that perfect foresight is a reasonable assumption. In particular, when there is a fixed limit to the number of allowed starts, as is common in many VPP contracts, uncertainty about future margins is definitely reducing plant value. We are able to show this result using the concept of least-squares Monte Carlo as applied to energy assets in e.g. Deng (2006, power plants) and De Jong and Boogert (2008; gas storage).

]]> no@spam.com (Hans van Dijken) Mon, 23 Aug 2010 11:18:58 CEST http://www.erasmusenergy.com/articles/192/1/The-value-of-starting-up-the-power-plant/Page1.html <![CDATA[Realistic power plant valuations]]> http://www.erasmusenergy.com/articles/184/1/Realistic-power-plant-valuations/Page1.html

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

.]]> no@spam.com (Cyriel de Jong) Thu, 27 Aug 2009 22:20:32 CEST http://www.erasmusenergy.com/articles/184/1/Realistic-power-plant-valuations/Page1.html <![CDATA[A 'simple' hybrid model for power derivatives]]> http://www.erasmusenergy.com/articles/173/1/A-039simple039-hybrid-model-for-power-derivatives/Page1.html

Published in: Energy Economics

Publication year: 2009
Co-Author 1: Robert J. Elliot

This paper presents a method for valuing power derivatives using a supply–demand approach. Our method extends work in the

field by incorporating randomness into the base load portion of the supply stack function and equating it with a noisy demand process. We obtain closed form solutions for European option prices written on average spot prices considering two different supply models: a mean-reverting model and a Markov chain model. The results are extensions of the classic Black–Scholes equation. The model provides a relatively simple approach to describe the complicated price behaviour observed in electricity spot markets and also allows for computationally efficient derivatives pricing.

]]> no@spam.com (Matthew Lyle) Tue, 11 Aug 2009 15:18:20 CEST http://www.erasmusenergy.com/articles/173/1/A-039simple039-hybrid-model-for-power-derivatives/Page1.html <![CDATA[Pricing summer day options by good-deal bounds]]> http://www.erasmusenergy.com/articles/171/1/Pricing-summer-day-options-by-good-deal-bounds/Page1.html Published in: Energy Economics
Publication year: 2008
Co-author 1: Kazuhiko Ohashi

Despite the worldwide popularity of CDD- and HDD-type weather derivatives based on temperature, a different class of weather derivatives, so-called summer day options, is more popular in Japan; the payoffs are determined by the number of summer days (i.e., the days whose average temperature is above 25 °C) during the contract period.

In this paper, we price such summer day options by the good-deal bounds of Cochrane and Saa-Requejo [Cochrane, J.H., and J. Saa-Requejo, 2000, Beyond Arbitrage: Good-Deal Asset Price Bounds in Incomplete Markets, Journal of Political Economy 108, 79–119.], using temperature data for Tokyo

.

]]> no@spam.com (Takashi Kanamura) Fri, 07 Aug 2009 17:38:08 CEST http://www.erasmusenergy.com/articles/171/1/Pricing-summer-day-options-by-good-deal-bounds/Page1.html <![CDATA[Effective pricing of wind power]]> http://www.erasmusenergy.com/articles/165/1/Effective-pricing-of-wind-power/Page1.html Published in: WorldPower 2008
Publication year: 2008
Co-author 1: Hans van Dijken

Effective Pricing of Wind Power - Uncertainties in Wind Production Often Priced at Too Low Levels

This article describes the pricing and hedging of wind power contracts. It demonstrates that substantial discounts relative to baseload power prices are reasonable to cover the negative wind-price correlation and to cover the difficulty of hedging price risks.

In this article, we outline a sound approach to the assessment of wind power projects, based on a careful analysis of project returns. In particular, we describe a number of hedge mechanisms and highlight some common pitfalls in
structuring wind power purchase agreement (PPA) deals. Wind power is one of the most viable options to meet renewable energy targets. The attractiveness to investors depends on investment costs, expected future power price and (heavily) on the subsidy regime. But with the steady increase of wind
production, the ability to secure future cashflows and to manage the risks becomes a key issue as well.

Wind power contracts typically contain discounts relative to the market forward prices. This derives from the difficulty in forecasting wind production and the variability in wind production, the correlation with market prices (imbalance and day-ahead). In the case presented, the correlation between day-ahead prices and wind production was already responsible for a discount of €6/MWh. A typical discount for imbalance costs has about the same magnitude, leading to an expected revenue shortfall of €12/MWh – without
even taking into account the effects of the continuous increase of wind production on spot power prices. The analysis also demonstrates that a
considerable proportion of the price risks, both short-term and long-term, are
unhedgeable and should be incorporated in additional discounts. It is our experience that these risks are easily overlooked and wind power priced too optimistically.
]]> no@spam.com (Cyriel de Jong) Mon, 24 Mar 2008 21:40:16 CET http://www.erasmusenergy.com/articles/165/1/Effective-pricing-of-wind-power/Page1.html <![CDATA[Spark Spread Options and the Valuation of Electricity Generation Assets]]> http://www.erasmusenergy.com/articles/142/1/Spark-Spread-Options-and-the-Valuation-of-Electricity-Generation-Assets/Page1.html Published in: Proceedings of the 32nd Hawaii International Conference on System Sciences Volume 3
Publication year: 1999
Co-author 1: Aram Sogomonian
Co-author 2: Blake Johnson

This paper presents and applies a methodology for valuing electricity derivatives by constructing replicating portfolios from electricity futures and the risk free asset. Futures based replication is argued to be made necessary by the non-storable nature of electricity, which rules out the traditional spot market, storage-based method of valuing commodity derivatives. Using the futures based approach, valuation formulae are derived for spark spread options for both geometric Brownian motion and mean reverting price processes. The valuation result is in turn used to construct real options based valuation formula for generation assets. Finally, the valuation formula derived for generation assets is used to value a sample of assets that have been recently sold, and the theoretical values calculated are compared to the observed sales prices of the assets.]]> no@spam.com (Shijie Deng) Mon, 07 Jan 2008 11:33:56 CET http://www.erasmusenergy.com/articles/142/1/Spark-Spread-Options-and-the-Valuation-of-Electricity-Generation-Assets/Page1.html <![CDATA[Valuation of the early-exercise price for options using simulation and nonparametric regression]]> http://www.erasmusenergy.com/articles/123/1/Valuation-of-the-early-exercise-price-for-options-using-simulation-and-nonparametric-regression/Page1.html Published in: Insurance mathematics & economics
Publication year: 1996

This article shows how to value the optimal stopping time for any Markovian process in finite discrete time. Specifically, the article focuses on the valuation of American options using simulations of stochastic processes. It also shows that the estimation of the decision rule to exercise early is equivalent to the estimation of a series of conditional expectations. For Markov processes, these conditional expectations can be estimated with nonparametric regression techniques. This article shows how to approximate the conditional expectations and the resulting early-exercise decision rule with spline and local regression.]]> no@spam.com (Jacques F. Carriere) Mon, 17 Dec 2007 15:22:52 CET http://www.erasmusenergy.com/articles/123/1/Valuation-of-the-early-exercise-price-for-options-using-simulation-and-nonparametric-regression/Page1.html <![CDATA[Valuation of Power Generation Assets: A Real Option Approach]]> http://www.erasmusenergy.com/articles/120/1/Valuation-of-Power-Generation-Assets-A-Real-Option-Approach/Page1.html Published in: Algo Research Quarterly
Publication year: 2000
Co-author 1: Yiping Zhuang

Real options theory is an increasingly popular tool for valuing physical assets such as power generation plants. In this paper, we describe a model for power plant valuation that accounts for such important operating characteristics as minimum on- and off-times, ramp time, nonconstant heat rates, response rate and minimum electricity dispatch level. The power plant values and optimal operating policies are obtained by employing stochastic dynamic programming. Sample numerical results, using electricity price data from the New England power pool, show that operating constraints can have a significant impact on power plant values and optimal operating policies.]]> no@spam.com (Doug Gardner) Thu, 13 Dec 2007 19:21:49 CET http://www.erasmusenergy.com/articles/120/1/Valuation-of-Power-Generation-Assets-A-Real-Option-Approach/Page1.html <![CDATA[Short-term generation asset valuation: a real option approach]]> http://www.erasmusenergy.com/articles/119/1/Short-term-generation-asset-valuation-a-real-option-approach/Page1.html Published in: Operations research
Publication year: 2002
Co-author 1: Graydon Barz

This paper discusses using real options to value power plants with unit commitment constraints over a short-term period. We formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit, that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit, and that these commitment decisions, once made, are subject to physical constraints such as minimum uptime and downtime. We also account for the costs associated with starting up and shutting down a unit. Last, we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow Ito processes. Using numerical simulation, we show that failure to consider physical constraints may significantly overvalue a power plant.]]> no@spam.com (Chung-Li Tseng) Thu, 13 Dec 2007 19:02:07 CET http://www.erasmusenergy.com/articles/119/1/Short-term-generation-asset-valuation-a-real-option-approach/Page1.html <![CDATA[Use of real options in asset valuation]]> http://www.erasmusenergy.com/articles/118/1/Use-of-real-options-in-asset-valuation/Page1.html Published in: The Electricity Journal
Publication year: 2002

An enhanced real option methodology and an alternative volatility measure, applied to the real option framework, allow a valuation to capture the holistic nature of real assets and the reality of the transaction involving them.]]> no@spam.com (Gary Gitelman) Thu, 13 Dec 2007 18:58:10 CET http://www.erasmusenergy.com/articles/118/1/Use-of-real-options-in-asset-valuation/Page1.html