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Power Plant Performance
Figure 1: Comparison Spark Spreads
monthly forward curves for the
peak and offpeak spark spreads
form the basis for the expected
operation and the intrinsic
valuation of a plant. Refining the
power and gas curves with daily
and hourly profiles improves the
valuation further. Ultimately, the
largest part of the power plant’s
capacity will be dispatched on an
hourly basis. Consequently, hourly
price curves are required to make
the dispatch decision.
Price Uncertainty & Real
Option Valuation
The hourly and daily forward
Source: KYOS Energy Consulting
curves may be treated as the best
forecast of future spot price levels (if we leave aside risk Correlated Returns: Unrealistic Spreads
premia). However, actual spot price levels will surely be To capture the dynamics between commodities over time,
different. On the one hand, this creates a risk, which may be analysts rely on Monte Carlo price simulations. This covers a
reflected in a high discount rate. On the other hand, price wide range of model implementations and we will
variations offer opportunities for extra margin if the plant’s demonstrate that the usual approaches exaggerate actual
dispatch and trading decisions can respond to them. To variations in spark spread levels.
capture this uncertainty, it is not sufficient to create The most common approach to combine multiple
high/medium/low price or spread scenarios. Actual market commodities in a Monte Carlo simulation model is applying
dynamicsarefarmorediversethanthat. acorrelationmatrixbetweenthedifferent
For example, a period of low margins
Models based on
commodities. This includes Principal
may be followed by a period of high
margins in the same day, week, month
correlated returns lead to
Component Analysis (PCA). A correlation
matrix captures the degree to which
or year. A plant operator will respond by
unrealistic spreads
prices move together from one day to the
reducing the production in the low next; it is derived from daily (or weekly)
spread period to minimise losses. At the same time, they will price returns. A correlation matrix, in combination with
maximise production in the high spread periods. In fact, a marketvolatilities,describesactualpricebehaviourquitewell
flexibleplantofferstheabilitytolimitthedownsideandtake for relatively short horizons, for example in Value-at-Risk
full advantage of the upside. This is the basis for any real models.However,extensiveresearchandpracticalexperience
option approach and is actually the way plant owners make lead to the insight that a correlation matrix is too weak to
a large part of their asset-backed trading profits in the maintain the fundamental relationships between
market place. commodities over a longer period. Consequently, very large
Still, to many in the power industry, this seems a non-real or negative spark spreads will be the result. These extreme
financialtrick.Indeed,suchanapproachissensitiveto‘model scenarios are not possible in reality though, as they would
error’ or ‘analyst bias’. It easily leads to an over-estimation of mean that either no power plant makes money or all power
true plant value. First, approaches which treat the plant as a plants make huge amounts of money. So, whereas an
strip of spark spread call options ignore the real-life intrinsic valuation disregards the value of plant flexibility,
restrictions on plant flexibility; restrictions may have either a the usual Monte Carlo simulation approach of correlated
technical or contractual nature. Second, approaches which returns results in an overestimation of plant flexibility.
are directly or indirectly based on unrealistic spark spread Another approach is not simulating the individual
levels suffer from the same overestimation bias. commodities, but simulating the spark spread directly. There
worldPower2009 49
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