Title :
A genetic algorithm-based approach to economic dispatch of power systems
Author :
Ma, H. ; El-Keib, A.A. ; Smith, R.E.
Author_Institution :
Dept. of Electr. Eng., Alabama Univ., Tuscaloosa, AL, USA
Abstract :
In view of the Clean Air Act (CAA) of 1990, the economic dispatch problem considering the compensating generation plan provided in the Act is nonlinear, ill-structured and multimodal. This paper presents a genetic algorithm (GA) based approach to solve this problem. Test results show that the genetic algorithm-based approach produces significantly better solutions compared against those obtained using the standard economic dispatch approach. It also proves the robustness of this algorithm in solving this type of optimization problem
Keywords :
air pollution detection and control; economics; genetic algorithms; load dispatching; power systems; thermal power stations; Clean Air Act; compensating generation plan; economic dispatch; genetic algorithm; optimization; power systems; robustness; Computer aided analysis; Cost function; Environmental economics; Fuel economy; Genetic algorithms; Power generation economics; Power system economics; Power systems; Production systems; Robustness;
Conference_Titel :
Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE
Conference_Location :
Miami, FL
Print_ISBN :
0-7803-1797-1
DOI :
10.1109/SECON.1994.324300
