Performance Simulation and Optimization of CCPP with Turbine Inlet Air Cooling

It is well established that the performance of combustion air turbines (gas turbines) is sensitive to ambient air temperature. As the ambient air temperature increases beyond standard design point  (ISASLS), the power output and exhaust gas flow rate reduces while the heat rate and exhaust gas temperature increases. While the trends are similar for heavy duty and aeroderivative gas turbines, due to the inherent nature of design the results are steeper for aeroderivatives.  Various types of turbine inlet cooling technologies such as evaporative cooling, refrigerated inlet cooling and thermal energy storage systems have been practiced with varying degree of success, each having its potential advantages and limitations.  Simplicity and cost advantage gained in evaporative cooling is offset by limitation of cooling along web bulb depression line (and is a function of site relative humidity). Refrigerated inlet cooling (direct and indirect) offer advantage of higher cooling and lesser sensitivity to site conditions, and result in greater power output with an impact on relative cost and complexity. Selection of optimum technology of turbine air inlet cooling is hence a tradeoff between competing factors.

Combined Cycle
Combined Cycle Power Plant

The complexity of combined cycles, without any turbine inlet air cooling, poses significant challenge in design of steam system and HRSG due to competing factors such as pinch point, heat and mass flows optimization etc. Knowledge of fluid viz properties of standard air (psychrometrics), standard gas for Joule Brayton cycle, steam for bottoming Rankine cycle and refrigerant for cooling system( for refrigerated inlet air cooling) as applied to complete cycle makes the process complete as well as complex. AxCYCLE™ is one such unique tool to simulate such combined cycle processes with multi fluid-multi phase flows including refrigeration. The standard HVAC features can easily be used for inlet air cooling refrigeration and integrated into the CCPP. Once a digital representation of the complex process is replicated and successfully ‘converged’ at design point, the challenge of optimization emerges. To facilitate optimization various tools namely AxCYCLE™ Map, Quest, Plan and Case are embedded integrally. As a first cut, users based on their experience apply AxCYCLE™ Map and vary one or two parameters to see the effect of operational parameters on cycle performance. AxCYCLE™ Quest opens the gates by allowing users to vary unlimited parameters, according to quasi-random Sobol sequences. mutli-Parameter optimization tasks are possible using AxCYCLE™ Plan – it uses design of experiments concepts. Once optimized the AxCYCLE™ Case tools allows off design simulation tasks. Exhibit below represents complexity of a combined cycle plant represented conveniently:

To learn more please check out the following demos:

Cost Estimation & Economic Analysis http://learn.softinway.com/Webinar/Watch/51

Vapor Compression Refrigeration System http://learn.softinway.com/Webinar/Watch/86

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