Power Plant Performance
Case Study
•
Monthly intrinsic valuation, no constraints
We consider a new gas-fired power plant in Germany. With A more detailed monthly curve shows that the winter periods
a 58.5% efficiency the plant produces a maximum of 420 MW; have the highest spark spreads, where the high power forward
at the minimum stable level it produces 170 MW (47% prices compensate for the also high gas prices. In the 36
efficiency). The plant has fixed annual operation and months, the plant produces only peakload, with an average
maintenance (O&M) costs of €6.3 million. We disregard spark spread of €31.70/MWh. This generates an annual value
discounting for simplicity. of €35.2 million. If the company could trade all monthly
If a plant is dispatched economically, it produces when its periods individually, this would ensure a minimum value the
spark spread – the gross marginal revenue – is positive and company can lock in on the forward market.
does not produce when the spark spread is negative. Simple as
•
Hourly intrinsic valuation, no constraints
it seems, technical, contractual and market restrictions hinder In most of the months, the expected hourly spark spread is
plant owners aiming to exactly dispatch along this principle. negative in some hours, but positive in other hours. Assuming
Actual dispatching is an optimization challenge, involving the plant has maximum ramping flexibility and is fully traded
issues such as ramp rates, minimum run-times, plant trips, on the spot market, the average expected value totals €43.0
maintenance and production-dependent heat rates. Optimal million. This is more than the monthly intrinsic value, because
dispatch decisions can be derived with various mathematical of the larger expected variations in the spot than in the
techniques. KYOS generally works with dynamic programming forward market. However, prices will not follow the current
techniques. curve for sure. This creates risk, part of which can be hedged on
the forward market, but also additional profit opportunities.
Case Study Results
•
Simulations with cointegrations, no constraints
We evaluate the plant over the period 2010-2012 based on Based on our price simulation model we calculate an
forward prices at the end of March 2009. optimal dispatch schedule per simulation path. This yields a
•
Traditional approach, no constraints value per simulation, with an average of €53.8 million, but
With the traditional approach, power is constantly produced with a large standard deviation of €8.0 million. As we will
during 2,500 peak and 2,500 offpeak hours. Taking fixed cost analyse later, the uncertainty in outcomes may be partially
components of €6.3 million/year into consideration, this leads hedged on the forward market, but some risk certainly
to an average annual value of €20.4 million. remains. The €10.7 million difference with the hourly intrinsic
Table 1: Breakdown of Power Plant Value
Total Intrinsic Flexibility
Value Value Value Power Gas Carbon Starts OH
[m€/yr] [m€/yr] [m€/yr] [GWh/yr] [GWh/yr] [kton/yr] [#/yr] [#/yr]
Fixed Price Curves
2500 peak + 2500 offpeak 20.4 20.4 0.0 2,100 3,621 740 N/A 5,000
Monthly forward curve 35.2 35.2 0.0 1,379 2,377 486 250 3,283
Hourly forward curve 43.0 43.0 0.0 2,059 3,520 720 417 4,902
Price Simulations,
With Cointegration 53.8 43.0 10.7 2,003 3,423 700 343 4,769
Variable O&M 50.8 40.0 10.8 1,919 3,280 671 345 4,569
Minimum runtimes 44.3 32.6 11.8 2,008 3,488 713 52 5,232
Start costs 42.3 30.2 12.1 2,025 3,545 725 44 5,294
Maintenance 39.6 28.1 11.5 1,907 3,339 683 42 4,987
Plant trips 36.9 25.8 11.0 1,800 3,153 645 44 4,706
Seasonality 37.1 26.0 11.1 1,803 3,159 646 44 4,703
Degradation 36.5 25.2 11.4 1,782 3,148 644 44 4,661
ALL, incl Take-or-Pay 35.9 25.9 10.0 1,894 3,341 683 43 4,935
Source: KYOS Energy Consulting. Note: the values exclude investment or financing costs; total value = intrinsic + flexibility value
worldPower 2009 51
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