Robust frequency control in a renewable penetrated power system: an adaptive fractional order-fuzzy approach

• Main Authors: Anil Annamraju, Srikanth Nandiraju
• Format: Article
• Language: English
• Published: SpringerOpen 2019-08-01
• Series: Protection and Control of Modern Power Systems
• Subjects: Adaptive fractional order-fuzzy-PID controller; Renewable energy sources; Load frequency control; TLBO algorithm
• Online Access: http://link.springer.com/article/10.1186/s41601-019-0130-8

Abstract Purpose Load frequency control (LFC) in today’s modern power system is getting complex, due to intermittency in the output power of renewable energy sources along with substantial changes in the system parameters and loads. To address this problem, this paper proposes an adaptive fractional order (FO)-fuzzy-PID controller for LFC of a renewable penetrated power system. Design/methodology/approach To examine the performance of the proposed adaptive FO-fuzzy-PID controller, four different types of controllers that includes optimal proportional-integral-derivative (PID) controller, optimal fractional order (FO)-PID controller, optimal fuzzy PID controller, optimal FO-fuzzy PID controller are compared with the proposed approach. The dynamic response of the system relies upon the parameters of these controllers, which are optimized by using teaching-learning based optimization (TLBO) algorithm. The simulations are carried out using MATLAB/SIMULINK software. Findings The simulation outcomes reveal the supremacy of the proposed approach in dynamic performance improvement (in terms of settling time, overshoot and error reduction) over other controllers in the literature under different scenarios. Originality/value In this paper, an adaptive FO-fuzzy-PID controller is proposed for LFC of a renewable penetrated power system. The main contribution of this work is, a maiden application has been made to tune all the possible parameters of fuzzy controller and FO-PID controller simultaneously to handle the uncertainties caused by renewable sources, load and parametric variations.