Particle swarm optimization for solving combined economic and emission dispatch problems
Tosaphol Ratniyomchai, Anant Oonsivilai, Padej Pao-la-or, Thanatchai Kulworawanichpong
Abstract
Tosaphol Ratniyomchai, Anant Oonsivilai, Padej Pao-la-or, Thanatchai Kulworawanichpong
Abstract
This paper presents a demonstration of solving combined economic and emission dispatch problems. The objective of the combined problem can be expressed by taking both the fuel cost and total emission into account with required constraints. Among potential intelligent search methods, particle swarm optimization is well-known and widely-used in solving economic load dispatch. In this paper, the particle swarm optimization is exploited to demonstrate its use. A three-unit thermal power plant is situated for test. Sets of suitable dispatch with respect to economic or emission objectives can be efficiently found.
OpenAlex reports 25 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper presents a demonstration of solving combined economic and emission dispatch problems. The objective of the combined problem can be expressed by taking both the fuel cost and total emission into account with required constraints. Among potential intelligent search methods, particle swarm optimization is well-known and widely-used in solving economic load dispatch. In this paper, the particle swarm optimization is exploited to demonstrate its use. A three-unit thermal power plant is situated for test. Sets of suitable dispatch with respect to economic or emission objectives can be efficiently found.
Key concepts: Economic dispatch, Particle swarm optimization, Mathematical optimization, Multi-swarm optimization, Computer science, Swarm behaviour, Metaheuristic, Optimization problem