|dc.description.abstract||With deregulation in the electric power industry, traditional
approaches for minimizing production costs have become unfit for
the present competitive environment. Owners of generation
assets must now consider price uncertainty in solving unit
commitment problems for scheduling and operating their power plants.
Operation flexibility of the generating assets, such as fuel switching
and overfire, becomes an important issue. Because in a competitive market with
volatile electricity prices, these flexibility may add significant values.
On the other hand, operational constraints, such as
ramp and minimum uptime/downtime constraints, present physical limits for
the generating assets to flexibly react to rapid price changes, which have
a negative effect on the asset value. Both of the operational flexibility
and operational constraints must be considered simultaneously so as to
achieve optimal operation under uncertainty. This dissertation devotes to
this very important subject.
Deregulation in the power industry allows new firms to freely enter
the generation markets. As a result, capacity expansion is no longer
the responsibility of local utility companies and has become a pure
investment problem. Overestimating the value of
a power may result in stranded capital for a long time period.
Therefore, to ensure a successful investment a fair
valuation method is essential. The generation asset valuation
must fully account for market uncertainty, which results in not only
risks but also opportunities. To minimize the risks, one must first have
sound models for market uncertainties. In this research, we consider
not only the uncertainties of electricity price and fuel price, but
also environment temperature because some characteristics of power plants
may be sensitive to the temperature. To fully capitalize on profitable
opportunities arising in the marketplace due to price spreads of different commodities,
such as fuel and electricity, a real options approach is considered, in which
different options are exercised at different but `optimal' timings.
Overall, this research is expected to contribute a new methodology for
fair generation valuation that accounts for multiple and interdependent
uncertainties and complex physical constraints. The proposed approach can
help operators achieving optimal operation
and investors making appropriate investment decisions.
In the long run, customers also benefit from the improved societal efficiency.||en_US
|dc.title||THERMAL GENERATION ASSET VALUATION PROBLEMS IN A COMPETITIVE MARKET||en_US
|dc.contributor.publisher||Digital Repository at the University of Maryland||en_US
|dc.contributor.publisher||University of Maryland (College Park, Md.)||en_US
|dc.subject.pquncontrolled||Least squares Monte Carlo method||en_US