TITLE:
Monte Carlo Simulation of a Combined-Cycle Power Plant Considering Ambient Temperature Fluctuations
AUTHORS:
Amir Hossein Jafari Yeganeh, Ali Behbahaninia, Parastoo Ghadamabadi
KEYWORDS:
Combined-Cycle Power Plant, Monte Carlo Method, Ambient Air Temper-ature, Maximum Likelihood Estimation, Stochastic Behavior
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.10 No.5,
May
31,
2022
ABSTRACT: A combined-cycle power plant (CCPP) is broadly utilized in many countries to cover
energy demand due to its higher efficiency than other conventional power
plants. The performance of a CCPP is highly sensitive to ambient air
temperature (AAT) and the generated power varies widely during the year with temperature
fluctuations. To have an accurate estimation of power generation, it is
necessary to develop a model to predict the average monthly power of a CCPP
considering ambient temperature changes. In the present work, the Monte Carlo
(MC) method was used to obtain the average generated power of a CCPP. The case
study was a combined-cycle power plant in Tehran, Iran. The region’s existing
meteorological data shows significant fluctuations in the annual ambient
temperature, which severely impact the performance of the mentioned plant,
causing a stochastic behavior of the output power.
To cope with this stochastic nature, the probability distribution of monthly
outdoor temperature for 2020 was determined using the maximum likelihood
estimation (MLE) method to specify the range of feasible inputs. Furthermore,
the plant was accurately simulated in THERMOFLEX to capture the generated power at different temperatures. The MC method was used to
couple the ambient temperature fluctuations to the output power of the plant,
modeled by THERMOFLEX. Finally, the mean value of net power for each month and
the average output power of the system were obtained. The results indicated
that each unit of the system generates 436.3 MW in full load operation. The
average deviation of the modeling results from the actual data provided by the
power plant was an estimated 3.02%. Thus, it can be concluded that this method
helps achieve an estimation of the monthly and annual power of a combined-cycle
power plant, which are effective indexes in the economic analysis of the
system.