Energy and exergy co-optimization of IGCC with lower emissions based on fuzzy supervisory predictive control

Abstract

This paper presents an energy and exergy co-optimization method of integrated gasification combined cycle (IGCC) based on Fuzzy Supervisory Predictive Control (FSPC). Firstly, a green IGCC process is proposed which contains three principle couplings: air separation unit (ASU), heat recovery steam generator (HRSG) and CO2 capture/storage unit (CCS). From law of thermodynamics, using substance thermophysical parameters, the energy efficiency and exergy efficiency of IGCC are successively defined. The IGCC power station has features such as closed coupling, large time lag and non-linearity, however, faster response speed and lower overshoot are always the unremitting pursuits. Therefore, the Fuzzy Supervisory Predictive Control (FSPC) method is proposed to implement robust control under complex disturbances by pre-considering unmeasurable disturbance and measurable disturbance. The fuzzy rules extracted from historical bigdata are employed in supervisory layer to make the precise control decisions. Finally, the energy and exergy co-optimization model is built and solved for higher efficiency and economic effectiveness. Taking the large-scale (300MW) IGCC for example, after using FSPC, the efficiency of water recovery is increased from 40.7% to 62.1% with the ratio of 52.6% because of waste water recovery (WWR) system. The net efficiency of proposed IGCC system is increased from 37.6% to 41.7% with the ratio of 10.9%. The exergy efficiency of IGCC system is increased from 36.5% to 39.2% with the ratio of 7.4%. The proposed method has great significance for the energy-saving and Near-zero emissions (NZEC) IGCC with high safety and robust control under supercritical (SC) or ultra-super critical (USC) state.