This paper proposes a new and a novel technique based on Artificial Neural Networks (ANNs) for nonlinear model of turbogenerators in a multi-machine power system. Only local measurements are required by each ANN in this new method, and hence it is called decentralized neuro-identificiation. Each turbogenerator in the power system is quipped with an ANN which is able to identify (or model) its particular turbogenerator from moment to moment This information can then be used by a second ANN at each generator to enable effective control of the nonlinear non-stationary process under all operating conditions. Simulation results are presented in this paper to show the potential of this new technique for designing fkture nonlinear ANN controllers
The electric power system is a complex nonlinear time varying system that needs advanced intelligent...
A neural network based identifier is designed for effective control of a small power system. The pow...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The increasing complexity of a modern power grid highlights the need for advanced system identificat...
This paper provides a novel method for nonlinear identification of multiple turbogenerators in a fiv...
This paper provides a new technique for nonlinear identification of multiple turbogenerators in a fi...
The increasing complexity of modern power systems highlights the need for effective system identific...
This paper reports on the simulation and practical studies carried out on a single turbogenerator co...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
This paper presents the design of a continually online trained (COT) artificial neural network (ANN)...
This paper describes an on-line identification technique for modelling a turbogenerator system. The ...
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multipl...
Power systems are nonlinear with fast changing dynamics. In order to design a nonlinear adaptive con...
A novel method for nonlinear identification of a static compensator connected to a power system usin...
The electric power system is a complex nonlinear time varying system that needs advanced intelligent...
A neural network based identifier is designed for effective control of a small power system. The pow...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The increasing complexity of a modern power grid highlights the need for advanced system identificat...
This paper provides a novel method for nonlinear identification of multiple turbogenerators in a fiv...
This paper provides a new technique for nonlinear identification of multiple turbogenerators in a fi...
The increasing complexity of modern power systems highlights the need for effective system identific...
This paper reports on the simulation and practical studies carried out on a single turbogenerator co...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
This paper presents the design of a continually online trained (COT) artificial neural network (ANN)...
This paper describes an on-line identification technique for modelling a turbogenerator system. The ...
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multipl...
Power systems are nonlinear with fast changing dynamics. In order to design a nonlinear adaptive con...
A novel method for nonlinear identification of a static compensator connected to a power system usin...
The electric power system is a complex nonlinear time varying system that needs advanced intelligent...
A neural network based identifier is designed for effective control of a small power system. The pow...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...