Visualizing the Doppler Effect

The development of Information and Communication Technologies suggests some spectacular changes in the methods used for teaching scientific subjects. Nowadays, the development of software and hardware makes it possible to simulate processes as close to reality as we want. However, when we are trying to explain some complex physical processes, it is better to simplify the problem under study using simplified pictures of the total process by eliminating some elements that make it difficult to understand this process. In this work we focus our attention on the Doppler effect which requires the space-time visualization that is very difficult to obtain using the traditional teaching resources. We have designed digital simulations as a complement of the theoretical explanation in order to help students understand this phenomenon.Comment: 16 pages, 8 figure

Causal aggregation: estimation and inference of causal effects by constraint-based data fusion

In causal inference, it is common to estimate the causal effect of a single treatment variable on an outcome. However, practitioners may also be interested in the effect of simultaneous interventions on multiple covariates of a fixed target variable. We propose a novel method that allows to estimate the effect of joint interventions using data from different experiments in which only very few variables are manipulated. If there is only little randomized data or no randomized data at all, one can use observational data sets if certain parental sets are known or instrumental variables are available. If the joint causal effect is linear, the proposed method can be used for estimation and inference of joint causal effects, and we characterize conditions for identifiability. In the overidentified case, we indicate how to leverage all the available causal information across multiple data sets to efficiently estimate the causal effects. If the dimension of the covariate vector is large, we may only have a few samples in each data set. Under a sparsity assumption, we derive an estimator of the causal effects in this high-dimensional scenario. In addition, we show how to deal with the case where a lack of experimental constraints prevents direct estimation of the causal effects. When the joint causal effects are non-linear, we characterize conditions under which identifiability holds, and propose a non-linear causal aggregation methodology for experimental data sets similar to the gradient boosting algorithm where in each iteration we combine weak learners trained on different datasets using only unconfounded samples. We demonstrate the effectiveness of the proposed method on simulated and semi-synthetic data

The use of decomposition methods to understand the economic growth gap between Latin America and east Asia

Understanding how growth factors contribute to explaining the large differences in growth rates across countries remains an important research agenda. The common approach to exploring this issue is based on the use of multiple linear regression analyses. This work contributes to growth literature by applying a new perspective based on the use of variance decomposition procedures: Shapley–Owen–Shorrocks and Oaxaca–Blinder. These methodologies have four main advantages with respect to traditional methodologies: they make possible the quantification of the relative contribution of each factor to economic growth, they allow us to estimate the efficiency in the use of the endowments of each factor, they can be used with any functional form and they can be used with estimation methods that are robust regarding endogeneity issues. We illustrate these advantages by analyzing the causes of the economic growth gap between Latin America and East Asia over the period 1980–2014. We find that the economic growth divergence between the two regions can be primarily explained by the differences in institutions and physical capital. In addition, the results indicate that the higher East Asian performance is not only due to its higher levels of endowments in these factors, but also to the higher efficiency in its use. We connect our results with the 2030 Agenda for Sustainable Development

The use of decomposition methods to understand the economic growth gap between latin america and east asia

[EN] Understanding how growth factors contribute to explaining the large differences in growth rates across countries remains an important research agenda. The common approach to exploring this issue is based on the use of multiple linear regression analyses. This work contributes to growth literature by applying a new perspective based on the use of variance decomposition procedures: Shapley–Owen–Shorrocks and Oaxaca–Blinder. These methodologies have four main advantages with respect to traditional methodologies: they make possible the quantification of the relative contribution of each factor to economic growth, they allow us to estimate the efficiency in the use of the endowments of each factor, they can be used with any functional form and they can be used with estimation methods that are robust regarding endogeneity issues. We illustrate these advantages by analyzing the causes of the economic growth gap between Latin America and East Asia over the period 1980–2014. We find that the economic growth divergence between the two regions can be primarily explained by the differences in institutions and physical capital. In addition, the results indicate that the higher East Asian performance is not only due to its higher levels of endowments in these factors, but also to the higher efficiency in its use. We connect our results with the 2030 Agenda for Sustainable Development.S

Grid forming H control for HVDC diode rectifier-connected wind power plants

[EN] Grid forming controllers need to operate with a large variation of grid parameters and grid structure, for instance, during black-start operation, connection to HVDC diode rectifiers, etc. This paper proposes a methodology for the synthesis of robust grid forming controllers for HVDC Diode Rectifier based Wind Power Plants using H ¿ control. The different operating modes of a HVDC Diode Rectifier based Wind Power Plant are be considered for the controller synthesis using the proposed H ¿ controller design methodology. The proposed methodology for grid forming controller design improves the performance and robustness of well tuned standard proportional-resonant based controllers. The results have been validated experimentally at the wind turbine level by means of a small power prototype. The validation at the system level has been carried out using a realistic simulation of a HVDC Diode Rectifier-connected Wind Power Plant.Authors would like to acknowledge the support of the Spanish Research Agency through grant PID2020-112943RB-I00 funded by MCIN/AEI/10.13039/501100011033 and grant PDC2021-121077-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR.Martínez-Turégano, J.; Sala, A.; Blasco-Gimenez, R. (2023). Grid forming H control for HVDC diode rectifier-connected wind power plants. CSEE Journal of Power and Energy Systems. 1-13. https://doi.org/10.17775/CSEEJPES.2023.0011011

Operation of DR-HVdc-Connected Grid-Forming Wind Turbine Converters Using Robust Loop-Shaping Controllers

[EN] Off-shore wind power plants can be connected to the on-shore grid using diode rectifier HVdc links. As diode rectifiers are passive converters, off-shore WPPs require grid-forming capability. This paper shows how to improve the WTG dynamic response and the voltage and current harmonic rejection by using H-infinity -based controllers. The paper explains how to synthesise three different H-infinity voltage controllers: the first is a single-loop H-infinity controller, the second is a cascaded H(infinity )controller and the third is a proportional-resonant controller that is optimised using H-infinity synthesis. The three H-infinity -based controllers improve the performance and the robustness obtained with a benchmark case PR controller tuned using the root locus technique. All the controllers are designed in continuous time and implemented in discrete time, applying bilinear discretisation with a sampling rate of 0.25 ms. Detailed PSCAD simulations validate the improvement of the performance and robustness, as well as an improvement in the harmonic rejection. The single H(infinity )controller shows the best combined characteristics of all tried controllers, at the expense of losing the separation between voltage and current control loops.Authors would like to acknowledge the support of the Spanish Research Agency through grant PID2020-112943RB-I00 funded by MCIN/AEI/10.13039/501100011033 and grant PDC2021-121077-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR.Martínez-Turégano, J.; Sala, A.; Blasco-Gimenez, R.; Blanes Campos, C. (2024). Operation of DR-HVdc-Connected Grid-Forming Wind Turbine Converters Using Robust Loop-Shaping Controllers. Applied Sciences. 14(2). https://doi.org/10.3390/app1402088114