Title :
Corrective action planning for power system load frequency control
Author :
Sharma, Mukesh ; Shrivastava, L. ; Pandit, M.
Author_Institution :
Dept. of Electr. Eng., Madhav Inst. of Technol. & Sci., Gwalior, India
Abstract :
The main objective of Load Frequency Control (LFC) is to maintain reasonably uniform frequency, to divide the load between generators, and to control the tie-line interchange schedules. The LFC is one of the most important issues in power system operation and control for supplying sufficient power of good quality with certain reliability. The control strategies guarantee that the steady state error of frequencies maintained in a given tolerance limit. This paper presents an artificial neural network based on Levenberg-Marquardt algorithm (LMNN) for load frequency control of a power system. A comparison of the efficiency of the proposed ANN based corrective action planning with the conventional integral controller shows the superiority of proposed approach for different loading conditions in wide range.
Keywords :
electric generators; frequency control; load regulation; neural nets; power generation planning; power generation reliability; ANN based corrective action planning; LFC; LMNN; Levenberg-Marquardt algorithm; artificial neural network; corrective action planning; generator; integral controller; power system load frequency control; power system reliability; steady state error; tie-line interchange schedule; Algorithm design and analysis; Artificial neural networks; Frequency control; Load modeling; Power system stability; Training; Integral controller; Lebenberg-Marquardt Neural Network; Lebenberg-Marquardt algorithm; Load Frequency Control; reference power;
Conference_Titel :
Power, Energy and Control (ICPEC), 2013 International Conference on
Conference_Location :
Sri Rangalatchum Dindigul
Print_ISBN :
978-1-4673-6027-2
DOI :
10.1109/ICPEC.2013.6527694