Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9652072 | International Journal of Electrical Power & Energy Systems | 2005 | 8 Pages |
Abstract
A new method based on immune algorithm (IA) is presented to solve the scheduling of cogeneration plants in a deregulated market. The objective function includes fuel cost, population cost, and electricity wheeling cost, subjective to the use of mixed fuels, operational limits, emissions constraints, and transmission line flow constraints. Enhanced immune algorithm (EIA) is proposed by an improved crossover and mutation mechanism with a competition and auto-adjust scheme to avoid prematurity. Table lists with heuristic rules are also employed in the searching process to enhance the performance. EIA is also compared with the original IA. Test results verify that EIA can offer an efficient way for cogeneration plants to solve the problem of economic dispatch, environmental protection, and electricity wheeling.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Sung-Ling Chen, Ming-Tong Tsay, Hong-Jey Gow,