With the passage of the Public Utilities Regulatory Policies Act (PURPA)
by the Federal Energy Regulatory Commission
(FERC) in 1978, cogeneration has steadily gained in popularity. Most
recently, the on-going process of deregulation in the
electric utility industry has changed the face of the energy market.
Changes in the nature of electrical rate structures and even
electrical providers have acted to greatly complicate the economic
analysis of cogeneration.
Several power cycles exist which can be used as the basis for a cogeneration
system. The Rankine, Brayton, Otto, and Diesel
cycles power cogeneration systems throughout the United States. Rankine
cycle power plants comprise the bulk of the base
loading power plants in the U.S. Brayton cycle gas turbines are generally
used in peaking power plant applications. Finally, the
Otto and Diesel cycle systems are used in smaller, packaged power systems
like back-up generators.
A Rankine based steam turbine cogeneration system is best suited for
high thermal vs. electrical load applications. The Otto and
Diesel cycle reciprocating engine systems have the highest fuel-to-electrical
efficiency, but are generally limited in size. Finally,
the Brayton cycle gas turbine falls between the reciprocating engine
and steam turbine systems in terms of fuel-to-electrical
efficiency. Gas turbines have now become available in sizes between
3 MW and 300 MW. The wide variety of turbine sizes
make them attractive when sizing a system.
Because of the nature and size of the Georgia Tech campus energy requirements,
a gas turbine was selected as the prime
mover for a campus cogeneration analysis. Using the half-hour campus
electrical data and the hourly campus gas data, an
economic analysis of differing sizes of gas turbine cogeneration systems
operated under differing operational strategies was
conducted. Four different turbines, a 10 MW, 7.5 MW, 5 MW, and 4 MW
were chosen for study. Each turbine was analyzed
based on a base load operating strategy, a peaking strategy, and a
thermal following strategy.
The 5 MW base loaded turbine returned the best simple payback of all
the systems studied. Its payback of 4 years is widely
considered acceptable for a project of this size. In general, the base
loading strategy returned the best economic results
regardless of the turbine size. The thermal following strategy was
slightly worse, and the peaking strategy returned poor
economic results.
The driving force behind the economic results was the campus electrical
rate structure. The base loading strategy benefited
most under the real-time-pricing (RTP) rate structure that serves the
campus. Conversely, the peaking strategy saw almost no
benefits from the RTP rate. It is important to realize that each of
these operational strategies can be beneficial and return
excellent economic results if the electrical rate that serves the facility
is naturally geared towards them. Therefore, a detailed
knowledge of how facility operation will affect the electrical rate
structure is an absolute requirement to perform an accurate
economic analysis.