Abstract
This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.
Highlights
Electric power systems are large, interconnected, complex, and highly changeable systems that are always affected by a wide variety of perturbations [1]
The conventional linear controllers designed around an equilibrium point are useful, but their performance could be degraded if variations are presented in the system
The present contribution considers the non-linear power system nature and it defines an adaptive controllers’ behavior. This performance is obtained by the inclusion of some selected dynamic gains that are updated on each sample time to find the best values for every operating condition and system topology
Summary
Electric power systems are large, interconnected, complex, and highly changeable systems that are always affected by a wide variety of perturbations [1]. The present contribution considers the non-linear power system nature and it defines an adaptive controllers’ behavior This performance is obtained by the inclusion of some selected dynamic gains that are updated on each sample time to find the best values for every operating condition and system topology. The main contributions of our methodology are: (i) a new method for tuning multiple controllers in electrical grids is proposed; (ii) a time-domain analysis for damping low frequency oscillations considering different controllers when previous design stage was already performed is included; (iii) different controllers preserving good performance without imposing a particular requirement are considered; (iv) the introduced methodology offers a practical way to obtain adaptive behavior of controllers with simultaneously tuning, and positive interaction; (v) the proposed algorithm is learning online, which means no additional stages for training are required
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