Implementation of Adaptive Critic-Based Neurocontrollers for Turbogenerators in a Multimachine Power System

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontroller\u27s training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability

A Neural Network Based Optimal Wide Area Control Scheme for a Power System

With deregulation of the power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. This paper presents the design and the DSP implementation of a nonlinear optimal wide area controller based on adaptive critic designs and neural networks for a power system on the real-time digital simulator (RTDS©). The performance of the WACS as a power system stability agent is studied using the Kundur\u27\u27s two area power system example. The WACS provides better damping of power system oscillations under small and large disturbances even with the inclusion of local power system stabilizers

Application of differential evolution to power system stabilizer design

Includes synopsis.Includes bibliographical references.In recent years, many Evolutionary Algorithms (EAs) such as Genetic Algorithms (GAs) have been proposed to optimally tune the parameters of the PSS. GAs are population based search methods inspired by the mechanism of evolution and natural genetic. Despite the fact that GAs are robust and have given promising results in many applications, they still have some drawbacks. Some of these drawbacks are related to the problem of genetic drift in GA which restricts the diversity in the population. ... To cope with the above mentioned drawbacks, many variants of GAs have been proposed often tailored to a particular problem. Recently, several simpler and yet effective heuristic algorithms such as Population Based Incremental Learning (PBIL) and Differential Evolution (DE), etc., have received increasing attention

IMPACT OF GENERIC AND MULTIBAND POWER SYSTEM STABLIZER (PSS) ON ELECTRIC POWER SYSTEM STABILITY

Sustained power system oscillation has become a serious problem for power system operation and control nowadays. Oscillations cause safety problems in electric power equipment and limit the transmission capacity of long-distance power transmission. Oscillations can reach an amount that can compromise the stable operation of the synchronous generator and the power system in general. One way to suppress oscillations is to use a stabilizer of the power system as an integral part of the excitation systems of generators. The task of the power oscillation stabilizer is to produce a torque damping component of the electromagnetic torque through the excitation systems. This paper reveals the impacts of Generic and Multiband power system stabilizers (PSS) to enhance the damping of low frequency oscillations in a two machine power system. The impact of the Multiband PSS was seen to be better that of Generic PSS on the two machine power system in Matlab Simulink. KEY WORD: Power, Stability, Simulation, Oscillations, Faults. DOI: 10.7176/CEIS/12-2-04 Publication date: April 30th 202