Chapters authored
Optimization of the ANNs Models Performance in the Short-Term Forecasting of the Wind Power of Wind Farms
Due to the low dispatchability of wind power, the massive integration of this energy source in electrical systems requires short-term and very short-term wind farm power output forecasting models to be as efficient and stable as possible. A study is conducted in the present paper of potential improvements to the performance of artificial neural network (ANN) models in terms of efficiency and stability. Generally, current ANN models have been developed by considering exclusively the meteorological information of the wind farm reference station, in addition to selecting a fixed number of time periods prior to the forecasting. In this respect, new ANN models are proposed in this paper, which are developed by: varying the number of prior 1-h periods (periods prior to the prediction hour) chosen for the input layer parameters; and/or incorporating in the input layers data from a second weather station in addition to the wind farm reference station. It has been found that the model performance is always improved when data from a second weather station are incorporated. The mean absolute relative error (MARE) of the new models is reduced by up to 7.5%. Furthermore, the longer the forecast horizon, the greater the degree of improvement.
Part of the book: Theory of Complexity
A Method to Improve Comprehension and Learning in Science Education – A Case Study in Systems Engineering and Automation
Difficulties are commonly detected in students with respect to the acquisition of certain specific competencies in a particular topic. One strategy to optimize the assimilation of knowledge and improve the learning results of students in a specific topic is through the use of the active learning process. Active learning can serve to facilitate autonomous and collaborative learning in specific topics as a complement to in-person classes. In this chapter, a method to improve comprehension and learning is developed and applied, using for this purpose both autonomous and collaborative works. The case study presented is undertaken for one of the subjects in the area of systems engineering and automation in one of the public universities of Canary islands (Spain). Different specific topics of the subject were selected. To check the effect of the application of the proposed method, a statistical analysis was performed. For this objective, t-test and the p-value statistical were used. As results, it was found that 100% of the students who presented some difficulty in relation to the general subject obtained higher relative results in the specific topics that they worked on when employing the proposed method, compared with their global result in the subject.
Part of the book: Active Learning