Low carbon unit commitment (LCUC) with post carbon capture and storage (CCS) technology considering resource sensitivity. (1st November 2018)

• Record Type: Journal Article
• Authors: ReddyK, Srikanth; Panwar, Lokesh; Panigrahi, B.K.; Kumar, Rajesh
• Is Part Of: Journal of cleaner production. Volume 200(2018)
• Page Start: 161
• Page End: 173
• Publication Date: 2018-11-01
• Subjects: Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.07.195
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: This paper proposes a new methodology for scheduling of thermal generation plants equipped with Amine based post combustion carbon capture technology. The methodology develops a generic and simplified model for operational planning of thermal generators through unit commitment. The performance indices developed in this paper can accommodate the resource sensitivity of the fuel used for combustion. The proposed performance indices are coupled to unit commitment procedure through intelligent scheduling methodology considering both economic and environmental concerns of the system. The proposed models can be readily integrated into the unit commitment algorithm using the test system data and fuel composition. The same provides a simple and near appropriate model to consider resource sensitivity as compared to detailed (or) dedicated modeling carried out in Aspen, APEA, promax etc. The impact of resource sensitivity and scheduling strategy has been illustrated using a 10 unit thermal generation test system with amine based post combustion carbon capture technology. The resource sensitivity of the model has been demonstrated using three different compositions of fuel/coal viz. sub-bituminous, bituminous and lignite coals. The simulation results of resource sensitivity at various capture efficiencies are presented and discussed in detail with respect to various performance indices developed. The models developed in this paper can be integrated to wide range of thermal generation plants with wide range of coal type (or) fuel compositions across the globe.