CO2 mitigation for a network of power plants using mathematical programming

Abstract

This paper presents a case study focusing on the structural optimization of Ontario power generation, OPG’s fleet of power plants to meet a given CO2 reduction target by minimizing the cost of electricity (COE). The optimization takes into account the possible implementation of carbon capture and storage (CCS) and the possibility of constructing new power plants, with or without CCS, to maintain or increase electricity to the grid depending on the growth in electricity demand. The model is formulated as mixed integer non linear programme (MINLP) and implemented in GAMS (general algebraic modeling system). Exact linearization techniques were employed to facilitate solution development. Three mitigation options were considered in this study: fuel balancing (optimal adjustment of the operation of existing generating stations to reduce CO2 emissions without making structural changes to the fleet), fuel switching (switching from carbon intensive fuel to less carbon intensive fuel, e.g. Coal to natural gas) and retrofitting ccs on existing coal fired power plants. Both, fuel switching and retrofitting ccs involve structural changes on the existing fleet. The computer programme is capable of determining the best mix of fuel, annual capacity factor for existing power plants, location and size of CO2 capture process and finally, construction of new state-of-the-art power plants, such as supercritical pulverized coal (PC), integrated gas combined cycle (IGCC) or natural gas combined cycle (NGCC) with and without CCS.