(83c) Performance Simulation and Optimization of IGCC Power Plants

Performance simulation and optimization of Integrated Gasification and Combined Cycle (IGCC) power plants

Chengjun Qian and Nan Zhang

Centre for Process Integration

School of Chemical Engineering and Analytical Science

University of Manchester, UK

M13 9PL

chengjun.qian@postgrad.manchester.ac.uk 

Integrated Gasification and Combined Cycle (IGCC) has arisen as a promising technology in electricity production due to its higher efficiency, lower emitting level, capability for CO₂ capture and flexibility in feeds and products. However IGCC is yet to be competitive against conventional technologies due to its higher capital and operation costs, lower reliability and under-utilised CCS ability. Much research has been done to improve its thermal efficiency, economic and environmental performance. As IGCC is a combination of two well-developed technologies - gasification and combined cycles, some of the key potentials for improvement need to be exploited through their integration.

In this work, a general framework is proposed to incorporate property calculation, unit operation models, and flowsheet synthesis in an overall systematic model. Rigorous property methods and relevant parameters for gas streams, steam and electrolyte solutions come from well-developed methods and databases, such as PR-BM method for gas, IAPWS-IF97 for steam, and E-NRTL for sour gas treatment(Mathias 1983; Wagner and Kretzschmar 2007; Zhang and Chen 2010) . These rigorous methods are able to give more reliable results than approximate ones, which apply linear approximations for heat capacity, enthalpy or reaction constant calculation. Unit models are grouped according to operations involved and modelled based on physical laws and design specifications. Part load performance curves for key units, such as gasifiers and gas turbines, are included to facilitate flow sheet analysis. The units are linked to each other through connecting streams to form a structured flow sheet.

In general the synthesized flowsheet is formulated as an MINLP problem, which is difficult for most solvers. Therefore, the MINLP problem is degraded to NLP sub-problems combined with enumeration of discrete decision variables to remove integer variables. The resulted equation based model is optimised with the CONOPT solver in GAMS^TM software. Key decisions such as feed stock selection, product yields and operating parameters can be optimised simultaneously. However the NLP sub-problems are still difficult to solve and no global optimum is guaranteed. Several technologies, such as simulation-based initialization, random start points and shortcut models, are considered to help convergence and improve solution quality.

A case study is carried out, and results show that major performance improvement can be achieved towards affordable IGCC power plants.

Mathias, P. M. (1983). "A versatile phase equilibrium equation of state." Industrial & Engineering Chemistry Process Design and Development 22(3): 385-391.

Wagner, W. and H.-J. Kretzschmar (2007). International Steam Tables-Properties of Water and Steam based on the Industrial Formulation IAPWS-IF97: Tables, Algorithms, Diagrams, and CD-ROM Electronic Steam Tables-All of the equations of IAPWS-IF97 including a complete set of supplementary backward equations for fast calculations of heat cycles, boilers, and steam turbines, Springer.

Zhang, Y. and C.-C. Chen (2010). "Thermodynamic modeling for CO2 absorption in aqueous MDEA solution with electrolyte NRTL model." Industrial & Engineering Chemistry Research 50(1): 163-175.