An intelligent load shedding scheme using neural networks and neuro-fuzzy.
Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.
Haidar
Ahmed M A
AM
Faculty of Electrical & Electronics Engineering, University Malaysia Pahang (UMP), Lebuhraya Tun Razak 26300 Gambang, Kuantan, Pahang, Malaysia. ahaidar67@yahoo.com
Mohamed
Azah
A
Al-Dabbagh
Majid
M
Hussain
Aini
A
Masoum
Mohammad
M
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D004560:Electricity; D004581:Electronics / Q000379:methods; D017143:Fuzzy Logic; D055641:Mathematical Concepts; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D011210:Power Plants; D012815:Signal Processing, Computer-Assisted