A coordinated design of power system stabilizer and power oscillation damping controller for generator and STATCOM voltage regulators is presented. Because fuzzy logic has the potential to overcome the inherent limitations of conventional and analytical model-based design approaches, simple fuzzy logic controllers operating as power system stabilizer and power oscillation damping controller are used in this work to enhance power system stability. The coordinated design of these fuzzy supplementary controllers (FSCs) is formulated as a constrained optimization problem with a time-domain based cost function. The optimal set of controller parameters is determined by applying a simultaneous tuning approach based on bat algorithm optimization. Simulations of a two-area power system under several operating conditions and perturbations are carried out to validate the effectiveness of the proposed alternative in damping system oscillations. Performance of the proposed coordinated FSCs is compared with other coordinated and uncoordinated design approaches, including coordinated FSCs using genetic algorithm and particle swarm optimization. Traditionally, power system stabilizers (PSSs) providing a supplementary signal through the generator voltage regulators have been extensively used by electric power utilities around the world to resolve oscillatory instability problems [4]. However, the operation and control requirements of today's power systems frequently make the damping contribution from PSSs alone insufficient [5]. Despite the fact that FACTS devices offer new opportunities for improving the damping of electromechanical oscillations through supplementary controllers, it is generally recognized that installing them for the sole purpose of power system stability enhancement is not a cost-effective solution [6]. However, when installed to satisfy their primary purpose, a power oscillation damping controller (PODC) can be incorporated into the existing devices.With the deployment of an increasing number of FACTS controllers in the systems, the potential for adverse interaction with one another and other controllers such as PSSs increases. Therefore, in order to provide maximum system benefit, it is important to coordinate the controllers of the various dynamic devices installed in a power system [1]. In this regard, various approaches have been reported in the literature to design PSSs and PODCs [7][8][9][10][11][12][13][14][15]. Because of the nonlinear nature of power system dynamics, any design based on linear analysis is often questionable and has to be extensively checked by nonlinear simulation [9,16,17]. On the other hand, despite that nonlinear design methods offer attractive features for the controller synthesis, a more complicated design procedure is also involved in this case [8,14,18]. In general, it is important to highlight that any analytical model-based approach presents some inherent shortcomings in the design and performance of the controller [17,18]. As for this, alternative synthesis techniques like ...
A neurofuzzy controller (NFC) with adaptive input link weights (ILWs) and working as an adaptive power system stabilizer is presented. The control structure of the proposed adaptive neurofuzzy power system stabilizers (ANFPSSs) consists of a neuroidentifier to track the dynamic behavior of the plant and an NFC to damp the low-frequency power system oscillations. Usually, the input membership functions (IMFs) and consequent parameters (CPs) are adapted in order to enhance the performance of the NFC. However, the adjustment of IMFs can be realized indirectly by the tuning of ILWs introduced here, which is simpler due to the small number of parameters involved. Therefore, in this paper, ILWs and CPs are updated online by the gradient descent method. Simulation studies over a range of operating conditions and disturbances in a single machine-infinite bus system and a multimachine power system demonstrate the improvement in the dynamic performance of the system with the proposed ANFPSS.Index Terms-Adaptive control, fuzzy logic controller (FLC), neural networks, power system stabilizer (PSS).
Contribution to the damping of inter-area and torsional oscillation modes, in doubly fed induction generators (DFIG) based wind farms, by power oscillation damping controllers (PODCs) based on two conventional structures and a fuzzy control strategy is investigated in this study. In this regard, a PODC with no lead/lag compensation is designed first and then a PODC with one lead/lag block is developed using eigenvalue techniques and the application of an iterative process based on the bat optimisation algorithm (BOA). Moreover, a fuzzy PODC, based on a simple fuzzy controller and tuned with the BOA according to the system transient response under a critical perturbation, is also designed. Comparative performance of the three PODCs is evaluated on a multi-machine power system. It is observed that all three PODCs can contribute to improving the damping of inter-area oscillations. However, eigenvalue analysis and non-linear time domain simulations reveal that each of them may also impact to a lesser or greater extent the shaft torsional oscillation mode damping. Their relative impact in this regard is also investigated.
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