A Novel Technique for Load Frequency Control of Multi-Area Power Systems

In this paper, an adaptive type-2 fuzzy controller is proposed to control the load frequency of a two-area power system based on descending gradient training and error back-propagation. The dynamics of the system are completely uncertain. The multilayer perceptron (MLP) artificial neural network structure is used to extract Jacobian and estimate the system model, and then, the estimated model is applied to the controller, online. A proportional–derivative (PD) controller is added to the type-2 fuzzy controller, which increases the stability and robustness of the system against disturbances. The adaptation, being real-time and independency of the system parameters are new features of the proposed controller. Carrying out simulations on New England 39-bus power system, the performance of the proposed controller is compared with the conventional PI, PID and internal model control based on PID (IMC-PID) controllers. Simulation results indicate that our proposed controller method outperforms the conventional controllers in terms of transient response and stability.

[1]  Shuang Cong,et al.  A novel PID-like neural network controller , 2005 .

[2]  K. R. Sudha,et al.  An adaptive technique to control the load frequency of hybrid distributed generation systems , 2019, Soft Comput..

[3]  Min-Rong Chen,et al.  An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations , 2017 .

[4]  Jawad Talaq,et al.  Adaptive fuzzy gain scheduling for load frequency control , 1999 .

[5]  Bo Fu,et al.  Research on Automatic Generation Control with Wind Power Participation Based on Predictive Optimal 2-Degree-of-Freedom PID Strategy for Multi-area Interconnected Power System , 2018, Energies.

[6]  Ieee Report,et al.  Dynamic Models for Steam and Hydro Turbines in Power System Studies , 1973 .

[7]  K. S. Rajesh,et al.  Hybrid improved firefly-pattern search optimized fuzzy aided PID controller for automatic generation control of power systems with multi-type generations , 2019, Swarm Evol. Comput..

[8]  Hassan Bevrani,et al.  Intelligent Demand Response Contribution in Frequency Control of Multi-Area Power Systems , 2018, IEEE Transactions on Smart Grid.

[9]  Sidhartha Panda,et al.  Simulation study for automatic generation control of a multi-area power system by ANFIS approach , 2012, Appl. Soft Comput..

[10]  Mohammad Hassan Khooban,et al.  Teaching-learning-based optimal interval type-2 fuzzy PID controller design: a nonholonomic wheeled mobile robots , 2013, Robotica.

[11]  I. A. Chidambaram,et al.  Decentralized biased dual mode controllers for load frequency control of interconnected power systems considering GDB and GRC non-linearities , 2007 .

[12]  Yu He,et al.  Load-Frequency Control of Multi-Area Power System Based on the Improved Weighted Fruit Fly Optimization Algorithm , 2020, Energies.

[13]  Taher Niknam,et al.  Fuzzy sliding mode control scheme for a class of non-linear uncertain chaotic systems , 2013 .

[14]  Emmanuel Chibuikem Nnadozie,et al.  Adaptation of a Novel Fuzzy Logic Controller to a Hybrid Renewable Energy System , 2018 .

[15]  Vijay Kumar,et al.  A novel interval type-2 fractional order fuzzy PID controller: Design, performance evaluation, and its optimal time domain tuning. , 2017, ISA transactions.

[16]  Aysen Demiroren,et al.  The application of ANN technique to automatic generation control for multi-area power system , 2002 .

[17]  A. Peer Fathima,et al.  Load frequency control in deregulated power system integrated with SMES–TCPS combination using ANFIS controller , 2016 .

[18]  Sehraneh Ghaemi,et al.  Gain Scheduling Technique using MIMO Type-2 Fuzzy Logic System for LFC in Restructure Power System , 2017, Int. J. Fuzzy Syst..

[19]  G. Shusheng,et al.  PID-like controller using a modified neural network , 1997 .

[20]  Soroush Oshnoei,et al.  An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system , 2019, Appl. Soft Comput..

[21]  Wen Tan,et al.  Unified Tuning of PID Load Frequency Controller for Power Systems via IMC , 2010, IEEE Transactions on Power Systems.

[22]  Mohammad Hassan Khooban,et al.  Control of a class of non-linear uncertain chaotic systems via an optimal Type-2 fuzzy proportional integral derivative controller , 2013 .

[23]  Wen Tan,et al.  Tuning of PID load frequency controller for power systems , 2009 .

[24]  Nasser Hosseinzadeh,et al.  Load Frequency Control of a Multi-Area Power System: An Adaptive Fuzzy Logic Approach , 2014, IEEE Transactions on Power Systems.

[25]  Antonella Ferrara,et al.  Third Order Sliding Mode Observer-Based Approach for Distributed Optimal Load Frequency Control , 2017, IEEE Control Systems Letters.

[26]  Chia-Feng Juang,et al.  Load-frequency control by hybrid evolutionary fuzzy PI controller , 2006 .

[27]  Taher Niknam,et al.  A new intelligent online fuzzy tuning approach for multi-area load frequency control: Self Adaptive Modified Bat Algorithm , 2015 .

[28]  Sehraneh Ghaemi,et al.  Application of type-2 fuzzy logic system for load frequency control using feedback error learning approaches , 2014, Appl. Soft Comput..

[29]  Naebboon Hoonchareon,et al.  Implementation of an A~C~E~/sub 1/ decomposition method , 2002 .

[30]  Seyed Zeinolabedin Moussavi,et al.  Online adaptive type-2 fuzzy logic control for load frequency of multi-area power system , 2019, J. Intell. Fuzzy Syst..