(384c) Modelling and Optimization Approaches to Enhance the Efficiency of Heat Recovery Steam Generators: A Case Study in Industrial Combined Cycle Power Plant | AIChE

# (384c) Modelling and Optimization Approaches to Enhance the Efficiency of Heat Recovery Steam Generators: A Case Study in Industrial Combined Cycle Power Plant

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Indian Institute of Technology Gandhinagar
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Indian Institute of Technology Gandhinagar
A combined cycle power plant (CCPP) is a complex system that uses gas turbineâ€™s hot exhaust to power the steam power plant for achieving higher thermal efficiency. Combined Cycle Power Plants (CCPPs) are popular in power generation industries as they have higher efficiencies as compared to Bryton Cycle and Rankine cycles [1]. In CCPP, gas turbine, Heat Recovery Steam Generator (HRSG) and steam turbine are arranged sequentially. CCPP has the advantage of extracting waste heat in the form of exhaust gases expelled from gas turbine through HRSG. HRSG utilizes this heat to evaporate water into steam and feed the steam generator. HRSG is a critical component of CCPP, as it ensures proper integration within combined cycle by transferring extracted exhaust heat from gas turbine to steam turbine. The overall efficiency of CCPP depends on the performance of HRSG [2].

Â An HRSG contains a maximum of three pressure sections (High, Intermediate and Low Pressure) with different types of heat exchangers (Economizer, Evaporator and Superheater) at various levels. In order to extract more heat from the exhaust gases coming from gas turbine, HRSG must be designed with optimal geometry (for maximum heat transfer) [3]. In the case of already installed HRSG, the operating conditions can be optimised to enhance the efficiency. The design of the HRSG is affected by the steam cycle parameters such as: pinch point (PP), which is defined as temperature difference between the saturation temperature of water and the gas temperature of the gas leaving the evaporator, and steam drum pressures. If the pinch point is minimized, energy losses are minimized. However it requires large heat transfer surface areas, an increase in the capital. Several studies are performed to optimize HRSG in combined cycle power plants. For instance, Behbahani-nia et al. [4] presented an exergy based thermo-economic method to find optimal values of the design parameters (pinch point and the gas-side velocity) for a single pressure HRSG. Bracco and Siri [5] analyzed different objective functions for exergetic optimization of single level combined gas-steam power plants. In all of these methods, the thermodynamic and/or thermo-economic analyses are investigated to achieve the optimum steam cycle parameters of HRSG [6]. These studies usually are performed using a steady state model of the HRSG and do not account for process dynamics/transients. However, dynamic models could provide better insights about the operation of the process and help evaluate control and alarm management strategies, key components for ensuring optimal operation of the plant.

In this work, we study the triple pressure HRSG associated with Dhuvaran CCPP in Gujarat, India. This HRSG has 13 heat exchangers at three different pressure levels. Thermal modelling of this HRSG at design point is carried out with pinch point and approach point method [3]. Further, the geometric details of heat exchangers are utilised to simulate it in Aspen Plus. The operating data obtained from the power plant is in good congruency with the simulated cases in terms of temperature profiles on both steam and exhaust gas sides. This steady state model of the HRSG is then extended to dynamic model using first principles approach which is then utilized to understand the behaviour of plant during transients. Alarm data with event log obtained for 6 days from this combined power plant indicates that 12186 alarms are flagged per day (compared to 144 alarms as per EEMUA-191 guidelines [7]) with approximately 8 alarms every minute. Therefore, we used the dynamic model of HRSG to evaluate the alarm management system in the plant. In this work, we will discuss the results of steady state model of HRSG, its extension to dynamic model and their usage in increasing the efficiency of overall system.

References:

[1] Abdolsaeid Ganjeh Kaviri, Mohammad Nazri Mohd Jaafar, and Tholudin Mat Lazim. Modeling and multi-objective exergy based optimization of a combined cycle power plant using a genetic algorithm. Energy Conversion and Management, 58:94â€“103, 2012.

[2] Ganapathy, V., 1996, â€œHeat-Recovery Steam Generators: Understand the Basics,â€ Chem. Eng. Prog., 92(8), pp. 32â€“45.

[3] Hajabdollahi, H., Ahmadi, P., and Dincer, I., 2011, â€œAn Exergy-Based Multi-Objective Optimization Of A Heat Recovery Steam Generator (HRSG) In A Combined Cycle Power Plant (CCPP) Using Evolutionary Algorithm,â€ Int. J. Green Energy, 8(1), pp. 44â€“64.

[4] Behbahani-nia, A., et al., Thermoeconomic Optimization of the Pinch Point and Gas-Side Velocity in Heat Recovery Steam Generators, Journal of Power and Energy, 224 (2010), 6, pp. 761-771

[5]Â Bracco, S., Siri, S., Exergetic Optimization of Single Level Combined Gas-Steam Power Plants Considering Different Objective Functions, Energy, 35 (2010), 12, pp. 5365-5373

[6] Mohammed, Mohammed S., and Milan V. Petrovi. "Thermoeconomic Optimization of Triple Pressure Heat Recover Steam Genreator Operating Parameters for Combined Cycle Plantsâ€ Thermal ScienceÂ 19.2 (2015): 447-460.

[7] EEMUA, (Engineering Equipment and Materials Usersâ€™ Association) , 2013,Alarm systems: a guide to design, management and procurement (3rd ed.)EEMUA Publication 191, London.