ABSTRACT
ABST R AC T Coal-red power plants are widely recognized as major water consumers whose operability has started to be affected by drought conditions across some regions of the country. Water availability also restricts the construction of new plants to satisfy the increasing power demand since these new facilities must include water-expensive carbon sequestration technologies. Therefore, national efforts to reduce water withdrawal and consumption have been intensied. Water consumption in thermoelectric generation is strongly associated to losses on cooling systems and to gas purication operations. These processes are affected by uncertain variables like atmospheric conditions. Thus, minimization of water consumption requires optimal operating conditions and parameters, while fullling the environmental constraints. Particulate Carbon (PC) power plants are studied in this work. Optimization under uncertainty for these large-scale complex processes with black-box models cannot be solved with conventional
CONTENTS
Introduction .........................................................................................................650 Particulate Carbon (PC) Model ....................................................................... 651 Uncertainties in PC Process .............................................................................. 651 Novel Stochastic Optimization Algorithm ..................................................... 652 Implementation of BONUS in Aspen Plus Models .....................................654 Results and Discussion ......................................................................................654
