A decision analysis model for reducing carbon emission from coal-fired power plants and its compensatory units.
J Environ Manage
; 301: 113829, 2022 Jan 01.
Article
en En
| MEDLINE
| ID: mdl-34592669
ABSTRACT
The increasing carbon dioxide level in the earth's atmosphere and continuously changing climate creates a significant challenge to sustainability in the world. It is not easy to control pollution due to carbon dioxide emissions from coal-fired power plants into the atmosphere. However, carbon capture technology provides an advantage for capturing carbon from power plants. Various researchers suggested the non-linear optimization model with post-combustion carbon capture technology in coal-fired power plants to reduce carbon emission. However, in their research articles, most researchers did not include loss of power due to retrofitting carbon capture technology in power plants and carbon emission from the compensatory power plant. This paper proposes a linear optimization model that minimizes the emission release from the power plant and its compensatory plant by appropriate selection of carbon capture technology. Our proposed model incorporates loss of power due to adopting carbon capture technology and emission release from the power plant and compensatory power plant in the problem formulation. We have also generated the Pareto curve that determines the trade-off solutions between emission release and the overall electricity cost. The applicability of our model is illustrated through power sector data from two Indian states. The net reduction of emissions in the two states are 27.17 % and 26.29 %, achieved by a mixed integer linear programming approach in coal-fired power plants. The model developed is generic and provides a sustainable environment for the generation of electricity.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Contaminantes Atmosféricos
/
Contaminación del Aire
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
Idioma:
En
Revista:
J Environ Manage
Año:
2022
Tipo del documento:
Article