Adaptive control of a synchronous machine using the auto-searching method
TL;DR: In this paper, an adaptive proportional-integral (PI) controller with real-time gain adjustment was proposed for the design of a power system stabilizer and a static VAr (reactive volt-ampere) compensator.
Abstract: A novel adaptive control scheme is presented for the design of a power system stabilizer (PSS) and a static VAr (reactive volt-ampere) compensator (SVC). The developed adaptive proportional-integral (PI) controllers, whose gains are adjusted in real time using the online-measured system operating conditions and a look-up table stored in computer memory, can offer better damper effects for generator oscillations over a wide range of operating conditions than conventional PI controllers with fixed gain settings. The effects of the adaptive PSS and the adaptive SVC on generator damping and terminal voltage profile are examined by computer simulation of system dynamic responses to a major disturbance. >
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TL;DR: A new approach using an artificial neural network is proposed to adapt power system stabilizer (PSS) parameters in real time to demonstrate the effectiveness of the proposed neural network.
Abstract: A new approach using an artificial neural network is proposed to adapt power system stabilizer (PSS) parameters in real time. A pair of online measurements i.e., generator real-power output and power factor which are representative of the generator's operating condition, are chosen as the input signals to the neural net. The outputs of the neural net are the desired PSS parameters. The neural net, once trained by a set of input-output patterns in the training set, can yield proper PSS parameters under any generator loading condition. Digital simulations of a synchronous machine subject to a major disturbance of a three-phase fault under different operating conditions are performed to demonstrate the effectiveness of the proposed neural network. >
166 citations
01 May 1990
TL;DR: A new type of power system stabiliser based on fuzzy set theory is proposed to improve the dynamic performance of a multimachine power system and is of decentralised output feedback form and is easy for practical implementation.
Abstract: A new type of power system stabiliser based on fuzzy set theory is proposed to improve the dynamic performance of a multimachine power system. To have good damping character istic over a wide range of operating conditions, speed deviation (δω) and acceleration (δω) of a machine are chosen as the input signals to the fuzzy stabiliser on that particular machine. These input signals are first characterised by a set of linguistic variables using fuzzy set notations. The fuzzy relation matrix, which gives the relationship between stabiliser inputs and stabiliser output, allows a set of fuzzy logic operations that are per formed on stabiliser inputs to obtain the desired stabiliser output. Since only local measurements are required by the fuzzy stabiliser on each generating unit, the proposed stabiliser is of decentralised output feedback form and is easy for practical implementation. The effectiveness of the proposed fuzzy stabiliser is demonstrated by a multimachine system example.
110 citations
TL;DR: In this paper, the performance of an incremental Clarke-Gawthrop adaptive control scheme, suitable for a diesel-engine prime mover, is described, which uses a predictor that is derived from explicit estimates of the plant deadtime and time constants.
Abstract: The performance of an incremental Clarke-Gawthrop adaptive control scheme, suitable for a diesel-engine prime mover, is described. The controller uses a predictor that is derived from explicit estimates of the plant deadtime and time constants. Its performance under speed reference changes and load disturbances has been compared to that of a fixed, tuned proportional-integral (PI) controller. The algorithm is found to operate satisfactorily under different values of droop without any additional complexity of computation being incurred. However, the improvement in plant response due to the adaptive algorithm is somewhat reduced at high droops. The effective improvement due to adaptation is also seen to be reduced under 'cold oil' conditions. However, even under such conditions, it is possible to obtain improved response as compared to the PI controller. >
99 citations
Proceedings Article•
01 Jan 2007TL;DR: In this paper, an artificial neural network (ANN) based approach to tune the parameters of the SVC reactive power controller over a wide range of typical load model parameters is presented.
Abstract: This paper presents an artificial neural network (ANN) based approach to tune the parameters of the SVC reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based reactive power controller are optimised for typical values of the load voltage characteristics by conventional techniques. Using the generated data, the method of multilayer feed-forward ANN with the error back-propagation training is employed. An ANN tuned static var compensator (SVC) controller has been applied to control the reactive power of variable slip/speed model of isolated wind-diesel hybrid power system. Transient responses of sample hybrid power system have also been presented.
59 citations
01 Mar 1993
TL;DR: It is found that the fuzzy excitation controller can improve the dynamic performance of a power system over a wide range of operating conditions.
Abstract: An approach based on fuzzy set theory is proposed for the design of an excitation controller for a synchronous generator. In the proposed fuzzy expert system, generator speed deviation and acceleration are taken as controller inputs. These input signals are first characterized by linguistic variables using fuzzy set notations. A fuzzy relation matrix is built to give the relationship between controller input and controller output. A set of fuzzy logic operations are performed by the fuzzy excitation controller using controller inputs and fuzzy relation matrix to get the desired controller output. To demonstrate the effectiveness of the fuzzy excitation controller, digital simulations of a power system subject to a three-phase fault under different operating conditions are performed. It is found that the fuzzy excitation controller can improve the dynamic performance of a power system over a wide range of operating conditions. Since the fuzzy excitation controller does not require model identification, it can be easily implemented on a microcomputer. >
50 citations
References
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TL;DR: In this article, the stability of synchronous machines under small perturbations is explored by examining the case of a single machine connected to an infinite bus through external reactance, and the results are shown to be similar to ours.
Abstract: The phenomena of stability of synchronous machines under small perturbations is explored by examining the case of a single machine connected to an infinite bus through external reactance.
1,939 citations
TL;DR: In this paper, the general concepts associated with applying power system stabilizers utilizing shaft speed, ac bus frequency, and electrical power inputs are developed in the first part of a three-part paper.
Abstract: The general concepts associated with applying power system stabilizers utilizing shaft speed, ac bus frequency, and electrical power inputs are developed in this first part of a three-part paper. This lays the foundation for discussion of the tuning concepts and practical aspects of stabilizer application in Parts II and III. The characteristics of the "plant" through which the power system stabilizer must operate are discussed and the implications upon stabilizer tuning and performance are noted. A general approach for analyzing stabilizers utilizing an arbitrary input signal is described and applied to the frequency and electrical power input signals.
940 citations
TL;DR: In this paper, a modified form of one of the more promising adaptive control algorithms for power systems is developed and described, and compared results of studies with adaptive stabilizer based on two alternate adaptive control algorithm and a conventional fixed parameter stabilizer show the improvement in response obtained with the adaptive algorithm.
Abstract: Characteristics of certain adaptive control techniques are discussed in this paper with particular emphasis on their application to power systems. A modified form of one of the more promising algorithms that makes it more suitable. for power systems is developed and described. Comparative results of studies with adaptive stabilizer based on two alternate adaptive control algorithms and a conventional fixed parameter stabilizer show the improvement in response obtained with the adaptive algorithm.
210 citations
TL;DR: In this article, an adaptive synchronous machine stabilizer utilizing the least squares identification with varying forgetting factor and a self-searching control strategy is proposed, which provides excellent damping under varying operating conditions and with different types of disturbances.
Abstract: An adaptive synchronous machine stabilizer utilizing the least-squares identification with varying forgetting factor and a self-searching control strategy is proposed in this paper. The use of varying forgetting factor in the identification algorithm improves parameter tracking under both transient and dynamic conditions, and the use of a self-searching pole shifting control technique increases the flexibility when applied to varying operating conditions encountered in power systems. These features make this stabilizer very robust. Studies given in the paper show that the proposed self-tuning stabilizer provides excellent damping under varying operating conditions and with different types of disturbances.
169 citations
TL;DR: In this article, a proportional-integral (PI) power system stabilizer is proposed for stabilization of power systems and two approaches for determining the optimal stabilizer gains of the proposed PI stabilizer are presented.
Abstract: Stabilization of power systems is investigated using a proportional-integral (PI) power system stabilizer. Digital (sampled-data) PI stabilizers as well as analog (continuous-time) PI stabilizers are examined in this paper. Two approaches, viz., the root-locus method and the suboptimal regulator method, are presented for determining the optimal stabilizer gains of the proposed PI stabilizer. The dynamic responses following a step disturbance by digital simulation are obtained by means of three types of stabilizers: the conventional power system stabilizer, the optimal stabilizer and the PI stabilizer. Simulation results show that the proposed PI stabilizer yields better system dynamic performance than the others in the sense of having greater damping in response to a step disturbance. A characteristic feature of the proposed PI stabilizer is that it is very simple for practical implementation, especially in the digital case, as commercial PI controllers have been widely employed by the industry for years.
119 citations