PREEM Workshop – Valuing Power Plants with Spark Spread Options
This workshop is offered by the Program for Research in Energy and Emissions Markets (PREEM) at the University of Technology, Sydney.
The workshop will be presented by distinguished Professor Gordon Sick, Professor of Finance at the Haskayne School of Business, University of Calgary, Canada. Professor Gordon Sick has a solid experience in consulting. His recent projects have included valuation of union merger gains and losses, real options analysis and valuation of spark spreads, real options analysis and valuation of mine development strategies, and valuation of liquidated damages on a long-term gas purchase contract including Kalman filter analysis of forward curves.
Details of the workshop are as follows:
Title: Valuing Power Plants with Spark Spread Options
Time: 2:00pm – 5:10pm, Friday 8th April
Location: Access Grid Room 01.16.11. Room 11, Level 16, UTS Tower Building, 15 Broadway, Sydney
Registration fee: $450 (a discount of $70 applies to registrations taken by Monday 4th April)
Non-UTS academics are entitled to receive a 50% discount
Non-UTS students are entitled to receive a 75% discount
For UTS academics and UTS PG-students there will be a special arrangement
NEW!! For registered participants who will not be able attend the workshop at UTS, remote access from any PC/laptop to our Access Grid login facility will be available.
Additional information regarding the method of payment will be provided on registration.
Registration: Click here to register or contact Alex Radchik (Alex.Radchik@uts.edu.au) for all other inquiries. Immediately before payment select your discount type (early bird, academic or student). Note when entering organisation name, click the New Organisation Name button if the form rejects your entry.
As the number of places is limited, please register as soon as possible. The FCFS policy (First-Come, First-Served) will be applied.
It is common to refer to a gas-fired power plant as generating a spark spread: converting natural gas to electricity by burning. A spark spread has two correlated stochastic variables: electricity price and natural gas price. To lower the number of variables in a problem, we worked with heat rates. The market heat rate is the ratio of the electricity price to the natural gas price and the plant heat rate is the number of gigajoules (GJ) of gas needed to generate one MWh of electric power.
We estimate a stochastic model for market heat rates that incorporates time of day, day of week, month and the incidence or otherwise of a spike in heat rates. We use the model and its residuals in a bootstrap process simulating future market heat rates, and use a Least Squares Monte Carlo approach to determine the optimal operating policy.
We applied our model to existing power plant in Alberta, Canada. This plant is powered by two General Electric gas turbines combined with a steam generator that allows combined cycle operations. This power plant is popular in various power jurisdictions around the world as a turnkey power plant that can offer peaking capacity, and some baseload power delivery. 4 operating modes for the plant are considered: cold metal (off), 15 MW idle in combined cycle, full simple-cycle power (95 MW) and combined cycle full power (120 MW). The plant is valued in each of four modes and the whole approach is summarized in a simple, easy-to-use example in a spreadsheet model using historical data.
Note that TTA is currently hosting PREEM web postings and email notifications on a temporary basis until University resources are set up to do this. For the latest PREEM news including presentations of past events, please visit the PREEM index page.