NDLI: Load frequency control of a dynamic interconnected power system using generalised Hopfield neural network based self-adaptive PID controller

Content Provider	IET Digital Library
Author	Ramachandran, Rajeswari Madasamy, Balasubramonian Veerasamy, Veerapandiyan Saravanan, Loheswaran
Abstract	A novel generalised Hopfield neural network (GHNN) based self-adaptive proportional–integral–derivative (PID) controller for load frequency control (LFC) is designed for a two-area interconnected power system with nonlinearities of generator rate constraint and governor dead band. The control problem is conceptualised as an optimisation problem with an objective function as an area control error in terms of the PID controller parameters. The differential equations governing the behaviour of the GHNN were solved to obtain the controller parameters K p, K i and K d. To test the feasibility and robustness of the proposed controller, the system is tested in the presence of randomness in load demands, imprecisely modelled system dynamics, nonlinearities in the system model and uncertainties in the system parameter variations. The proposed method is simulated using Matlab R2014b/Simulink and the results obtained have shown that the propounded controller performance is superior to the integral, PID and fuzzy-based proportional–integral controllers. In addition, the Lyapunov stability analysis of the overall closed-loop system was carried out and the controller is implemented in real-time digital simulator run in hardware-in-the-loop to validate the effectiveness of the proposed method. Furthermore, the proposed controller is applied to the three-area power system to test its adaptability.
Starting Page	5713
Ending Page	5722
Page Count	10
ISSN	17518687
Volume Number	12
e-ISSN	17518695
Issue Number	Issue 21, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/12/21
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5622
Journal	IET Generation, Transmission & Distribution
Publisher Date	2018-10-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Control Area Control Error Closed-loop System Control of Electric Power System Differential Equation (numerical Analysis) Dynamic Interconnected Power System Frequency Control Fuzzy Control Fuzzy-based Proportional–integral Controllers Generalised Hopfield Neural Network-based Self-adaptive PID Controller Generator Rate Constraint GHNN Governor Dead Band Hardware-in-the-loop Hopfield Neural Network Imprecisely Modelled System Dynamics Load Demands Load Frequency Control Load Regulation Lyapunov Method Lyapunov Stability Analysis Neurocontrol Neurocontrollers Objective Function Optimisation Optimisation Problem Optimisation Technique PI Control PID Controller Parameter Power System Control Power System Economics Power System Interconnection Power System Managemen Power System Operation Proportional–integral–derivative Controller Propounded Controller Performance Real-time Digital Simulator Self Adjusting Control System Stability Stability in Control Theory System Model System Parameter Variations Three-area Power System Three-term Control Two-area Interconnected Power System Uncertain System Uncertainties
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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