Sergio Lopez
University of Deusto
5 Papers
46 Citations
Sergio Lopez is an academic researcher from University of Deusto. The author has contributed to research in topics: Wind power forecasting & Photovoltaic system. The author has an hindex of 4, co-authored 5 publications.
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Papers
Burnout, Resilience, and COVID-19 among Teachers: Predictive Capacity of an Artificial Neural Network
TL;DR: In this paper, the authors analyzed the relationship between resilience, burnout dimensions, and variables associated with COVID-19 through the design of an artificial neural network architecture and found that 30.8% suffered from burnout (high emotional exhaustion, high cynicism, and low professional efficacy) and 38.7% had a high level of resilience, with an inverse relationship between both constructs.
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Solar production forecasting based on irradiance forecasting using artificial neural networks
Christos S. Ioakimidis,Sergio Lopez,Konstantinos N. Genikomsakis,Pawel Rycerski,Dragan Simic +4 more
- 01 Nov 2013
TL;DR: This work presents the development of solar irradiance and PV power output forecasting models, based on artificial neural networks (ANNs), operating with a time horizon of 24 h in order to be integrated as part of home energy management systems (HEMS).
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Utilizing plug-in electric vehicles for peak shaving and valley filling in non-residential buildings with solar photovoltaic systems
Konstantinos N. Genikomsakis,Benjamin Bocquier,Sergio Lopez,Christos S. Ioakimidis +3 more
- 23 Apr 2016
TL;DR: A hybrid approach that combines an artificial neural network for solar irradiance forecasting with a MATLAB/Simulink model to simulate the power output of solar PV systems is described, as well as the development of a mathematical model to control the charging/discharging process of the PEVs.
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Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting
TL;DR: A short-term wind power forecasting model based on artificial neural network (ANN) clustering, which uses statistical feature parameters in the input vector, as well as an enhanced version of this approach that adjusts the ANN output with the probability of lower misclassification (PLM) method are described.
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Short-term wind speed forecasting model based on ANN with statistical feature parameters
Christos S. Ioakimidis,Konstantinos N. Genikomsakis,Panagiotis I. Dallas,Sergio Lopez +3 more
- 01 Nov 2015
TL;DR: This work proposes a novel short-term wind speed forecasting model based on an artificial neural network (ANN), with the key characteristic that statistical feature parameters of wind speed, wind direction and ambient temperature are employed in order to reduce the input vector and thus the complexity of the model.
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