Abstract:The smart-grid approach undergoes many difficulties regarding the strategy that will enable its actual implementation. In this paper, an overview of real-time simulation technologies and their applicability to the smart-grid approach are presented as enabling steps toward the smart-grid's actual implementation. The objective of this work is to contribute with an introductory text for interested readers of real-time systems in the context of modern electric needs and trends. In addition, a comprehensive review of current applications of real-time simulation in electric systems is provided, together with the basis to understand real-time simulation and the topologies and hardware used to implement it. Furthermore, an overview of the evolution of real-time simulators in the industrial and academic background and its current challenges are introduced.
Commonly, complex and uncertain plants cannot be faced through well-known linear approaches. Most of the time, complex controllers are needed to attain expected stability and robustness; however, they usually lack a simple design methodology and their actual implementation is difficult (if not impossible). Fuzzy logic control is an intelligent technique which, on its basis, allows the translation from logic statements to a nonlinear mapping. Although it has been proven to effectively deal with complex plants, many recent studies have moved away from the basic premise of linguistic interpretability. In this work, a simple fuzzy controller is designed in a clear way, privileging design easiness and logical consistency of linguistic operators. It is simulated together to a nonlinear model of a quadcopter with added actuators variability, so the robust operation of the controller is also proven. Uneven gain, bandwidth, and time-delay variations are applied among quadcopter's motors, so the simulations results enclose those characteristics which could be found in reality. As those variations can be related to actuators' performance, an analysis can be driven in terms of the features which are not commonly included in mathematical models like power electronics drives or electric machinery. These considerations may shorten the gap between simulation and actual implementation of the fuzzy controller. Briefly, this chapter presents a simple fuzzy controller which deals with a quadcopter plant as a first approach to intelligent control.
Educational systems are now focusing on skills enhancement, such as creative thinking skills (CTS), as a means of long-lasting, significant learning. To this end, some universities and higher education institutions incentivize active learning (AL) strategies as CTS developers. Indeed, a positive link among creative results, time availability, and the educational environment has been reported; however, it is mainly based on qualitative and perceptual results. For this reason, we present this comparative, quantitative study in the context of a Mexican high school, weighing the effectiveness of the flipped learning and gamification teaching strategies against a conventional approach. The study revealed no differences in the learning environment; instead, the type of activity and the teamwork interaction affected CTS the most. However, those who participated in the learning Strategies (LS) evaluated themselves higher than their peers in the traditional classes. These results highlight the independence of CTS toward the referred LS and set a departing point for further research addressing the course activities’ qualities seemingly related to CTS enhancement.
Phase-locked loop (PLL) systems play a crucial role in grid synchronization. Since variations on the grid voltage parameters are in general uncertain, the dynamics of PLLs are by nature nonlinear. This fact imposes a relevant challenge to guarantee their stability. Unfortunately, as argued in this paper, there is a remarkable lack of global stability tests even for the most common approaches, such as the synchronous reference frame (SRF). In this case, there is only available a small-signal-linearized-modelbased approach to stability. The main issue of resorting to local conclusions is that synchronization is forced to operate under conservative conditions, where large-signal variations are forbidden. Needless to say, this has a detrimental impact on applications, since performance is limited by small disturbance assumptions. Motivated by this problem, in the present work, we provide global asymptotic stability tests for two fundamental PLL algorithms. Namely, the conventional SRF-PLL and the enhanced SRF-EPLL. To do so, we use a Lyapunov approach acting directly on nonlinear trajectories. Consequently, the provided stability proofs do not rely on any linearization technique, frequency-domain conversion, or small-signal model representation. The main contribution in this paper is a set of stability conditions that are valid in a global sense. Moreover, it is shown that these results have direct practical implications in the form of new robust PLL gain tuning guidelines.
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