Intelligent System Applications in Power Engineering: Evolutionary Programming and Neural Networks
Intelligent System Applications in Power Engineering: Evolutionary Programming and Neural Networks
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
| Hi-index | 0.00 |
Evolutionary Programming (EP) optimization technique is recently applied in solving electric power system optimization problems. It is a fraction in the Evolutionary Computation (EC) optimization techniques under the artificial intelligence hierarchy. Optimization is an important issue in power system operation and planning particularly in the area of voltage stability studies. This paper presents transmission loss minimisation using optimal reactive power planning techniques (RPP). The problem involved optimization process; utilizing the ideas of EP to identify the optimal solution for RPP. In this study, EP engine was initially developed to implement the optimisation process considering two RPP procedures, namely optimal reactive power dispatch (ORPD) and optimal transformer tap changer setting (OTTCS). Comparative studies performed in this study aimed to identify the most suitable RPP technique for minimising transmission loss in power system, while maintaining the voltage profiles at reasonable voltage levels and avoiding overcompensating to the system. Repetitive load flow program was implemented for the fitness computation of the EP. Simulation results on a bulk IEEE Reliability System (RTS) are included to demonstrate the effectiveness of the proposed technique. Results indicated that ORPD outperformed OTTCS in minimising the system transmission loss with voltage profiles maintained within the acceptable limit.