B. García-Puente, A. Rodríguez-Hurtado, M. Santos, J. Sierra-García
Wind energy is one of the most promising renewable energies. But wind is a quite unstable resource due to its continuous variation and random nature. This uncertainty affects the production cost. Therefore, accurate forecasting of wind and energy is very interesting for energy markets. In this work, we test a recent and powerful intelligent technique, extreme gradient boosting (XGBoost), for wind prediction. The forecasting models of some wind features with XGBoost are compared with Support Vector Regression (SVR), Gaussian Process Regression (GPR) and Neural Networks (NN) models. Specifically, the three features predicted are the active power generated by the turbine, the wind speed, and the wind direction. The results conclude that these techniques are useful for wind and energy forecasting, with XGBoost being the most outstanding one, especially for short-term predictions.
{"title":"Evaluation of XGBoost vs. other Machine Learning models for wind parameters identification","authors":"B. García-Puente, A. Rodríguez-Hurtado, M. Santos, J. Sierra-García","doi":"10.24084/repqj21.334","DOIUrl":"https://doi.org/10.24084/repqj21.334","url":null,"abstract":"Wind energy is one of the most promising renewable energies. But wind is a quite unstable resource due to its continuous variation and random nature. This uncertainty affects the production cost. Therefore, accurate forecasting of wind and energy is very interesting for energy markets. In this work, we test a recent and powerful intelligent technique, extreme gradient boosting (XGBoost), for wind prediction. The forecasting models of some wind features with XGBoost are compared with Support Vector Regression (SVR), Gaussian Process Regression (GPR) and Neural Networks (NN) models. Specifically, the three features predicted are the active power generated by the turbine, the wind speed, and the wind direction. The results conclude that these techniques are useful for wind and energy forecasting, with XGBoost being the most outstanding one, especially for short-term predictions.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82922681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kévin Acadine, Augustin Mpanda Mabwe, A. El Hajjaji
This paper deals with performance of three and five level grid-connected T-type inverters. T-Type structure requires fewer power devices than Neutral-Point-Clamped and FlyingCapacitor inverters for the same power level. First, mathematical model of grid connected T-Type inverters is demonstrated. The PI controller is used to control the d-axis and q-axis currents, respectively. The sine Pulse Width Modulation (PWM) technique is used to control the MOSFET switches. The simulation of the complete system has been performed on MATLAB/Simulink.
{"title":"Performance Evaluation of Grid Connected T-Type Multilevel Inverters","authors":"Kévin Acadine, Augustin Mpanda Mabwe, A. El Hajjaji","doi":"10.24084/repqj21.404","DOIUrl":"https://doi.org/10.24084/repqj21.404","url":null,"abstract":"This paper deals with performance of three and five level grid-connected T-type inverters. T-Type structure requires fewer power devices than Neutral-Point-Clamped and FlyingCapacitor inverters for the same power level. First, mathematical model of grid connected T-Type inverters is demonstrated. The PI controller is used to control the d-axis and q-axis currents, respectively. The sine Pulse Width Modulation (PWM) technique is used to control the MOSFET switches. The simulation of the complete system has been performed on MATLAB/Simulink.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88174088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Á. Bayod-Rújula, R. Dufo-López, Amaya Martínez Gracia
This paper describes a technical-economical analysis to achieve the most appropriate sizing of grid-connected photovoltaic systems for water pumping in irrigation communities. The profitability of different tracking systems are analysed based on the price of the electrical energy consumed from the network. The case study of a real pumping system of an irrigation community located in Zaragoza (Spain) is presented, which supplies a geographical area of 2000 Ha, with six 630kW pumps and eight 110kW units.
{"title":"Sizing of on-grid photovoltaic systems for water pumping in irrigation communities","authors":"Á. Bayod-Rújula, R. Dufo-López, Amaya Martínez Gracia","doi":"10.24084/repqj21.228","DOIUrl":"https://doi.org/10.24084/repqj21.228","url":null,"abstract":"This paper describes a technical-economical analysis to achieve the most appropriate sizing of grid-connected photovoltaic systems for water pumping in irrigation communities. The profitability of different tracking systems are analysed based on the price of the electrical energy consumed from the network. The case study of a real pumping system of an irrigation community located in Zaragoza (Spain) is presented, which supplies a geographical area of 2000 Ha, with six 630kW pumps and eight 110kW units.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81493778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The importance and future prospects of offshore wind power generation invite great efforts and investments to make it an efficient technology. A crucial aspect is the development of efficient control strategies, which in many cases require models to identify the state of the turbine at a given time accurately. These models must be simple enough not to increase the computational complexity of the control algorithm while being able to capture the nonlinearity and coupling of wind systems. In this work we study the possibility of using neural networks to identify a wind turbine model to predict its power output. Two models, with different number of inputs, have been proposed. LSTM (Long-Short Term Memory) and RNN (Recurrent Neural Network) have been compared, with satisfactory results in terms of model accuracy on an offshore 5MW WT.
{"title":"Forecasting of wind turbine synthetic signals based on convolutional","authors":"C. Blanco, J. Sierra-García, M. Santos","doi":"10.24084/repqj21.365","DOIUrl":"https://doi.org/10.24084/repqj21.365","url":null,"abstract":"The importance and future prospects of offshore wind power generation invite great efforts and investments to make it an efficient technology. A crucial aspect is the development of efficient control strategies, which in many cases require models to identify the state of the turbine at a given time accurately. These models must be simple enough not to increase the computational complexity of the control algorithm while being able to capture the nonlinearity and coupling of wind systems. In this work we study the possibility of using neural networks to identify a wind turbine model to predict its power output. Two models, with different number of inputs, have been proposed. LSTM (Long-Short Term Memory) and RNN (Recurrent Neural Network) have been compared, with satisfactory results in terms of model accuracy on an offshore 5MW WT.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84877414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, the share of renewable sources in the energy mix of production units has been steadily increasing. The unpredictability of renewable sources leads to difficulties in planning, managing and controlling the electric energy system (EES). One of the ways to reduce the negative impact of unpredictable renewable sources is to predict the availability of these energy sources. Short-term forecasting of photovoltaic power plant production is one of the tools that enable greater integration of renewable energy sources into the EES. One way to gather information for the short-term forecast production model is to continuously photograph the hemisphere above the photovoltaic power plant. By processing the data contained within the images, parameters related to the current output power of the observed power plant are obtained. This paper presents a model that utilises a convolutional neural network to analyse images of the hemispherical sky above a power plant to predict the current output power of the power plant. Estimating current production is a crucial step in developing models for short-term solar forecasts. The model was specifically developed for photovoltaic power plants and is capable of achieving high accuracy in power prediction. The estimation of power production from photovoltaic power plants enables the use of next-frame prediction for short-term forecasting.
{"title":"Sky Image Analysis and Solar Power Forecasting: A Convolutional Neural Network Approach","authors":"A. Jakoplić, S. Vlahinić, B. Dobraš, D. Franković","doi":"10.24084/repqj21.355","DOIUrl":"https://doi.org/10.24084/repqj21.355","url":null,"abstract":"Recently, the share of renewable sources in the energy mix of production units has been steadily increasing. The unpredictability of renewable sources leads to difficulties in planning, managing and controlling the electric energy system (EES). One of the ways to reduce the negative impact of unpredictable renewable sources is to predict the availability of these energy sources. Short-term forecasting of photovoltaic power plant production is one of the tools that enable greater integration of renewable energy sources into the EES. One way to gather information for the short-term forecast production model is to continuously photograph the hemisphere above the photovoltaic power plant. By processing the data contained within the images, parameters related to the current output power of the observed power plant are obtained. This paper presents a model that utilises a convolutional neural network to analyse images of the hemispherical sky above a power plant to predict the current output power of the power plant. Estimating current production is a crucial step in developing models for short-term solar forecasts. The model was specifically developed for photovoltaic power plants and is capable of achieving high accuracy in power prediction. The estimation of power production from photovoltaic power plants enables the use of next-frame prediction for short-term forecasting.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90681632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Offshore wind turbines have become an increasingly attractive source of renewable energy because of their potential to access and utilize energy from deeper waters with more stable, stronger winds. The goal of this paper is to propose a mathematical model based on transfer functions to identify and study the behavior of the six degrees of freedom of floating turbines. For this purpose, the system has been simulated with OpenFAST for specific environmental conditions. A subset of data has been used to identify transfer functions to obtain a control-oriented model. The model has been progressively validated, extending the preliminary proposed model. The scope and limitations of this methodology have been assessed, as well as the possibilities of extending the present work to include a more functional methodology oriented to system co-design.
{"title":"Preliminary Identification of the Dynamics of a Floating Offshore Wind Turbine Barge","authors":"I. Galeote, S. Esteban, M. Santos","doi":"10.24084/repqj21.387","DOIUrl":"https://doi.org/10.24084/repqj21.387","url":null,"abstract":"Offshore wind turbines have become an increasingly attractive source of renewable energy because of their potential to access and utilize energy from deeper waters with more stable, stronger winds. The goal of this paper is to propose a mathematical model based on transfer functions to identify and study the behavior of the six degrees of freedom of floating turbines. For this purpose, the system has been simulated with OpenFAST for specific environmental conditions. A subset of data has been used to identify transfer functions to obtain a control-oriented model. The model has been progressively validated, extending the preliminary proposed model. The scope and limitations of this methodology have been assessed, as well as the possibilities of extending the present work to include a more functional methodology oriented to system co-design.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86744020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan D. Parra-Quintero, A. Rubio-Clemente, E. Chica
The utilization of marine power potential in Colombia holds a great promise, and the oscillating water column (OWC) is one option that deserves to be explored. The wave energy conversion process using an OWC typically involves two stages: the conversion of wave power to pneumatic power in an air chamber, and the conversion of pneumatic power to electricity using a selfrectifying air turbine coupled to an electric generator. In order to improve the efficiency of the primary stage, this study is aiming at determining the hydrodynamic performance of an OWC air chamber using a numerical model based on the Reynolds Averaged Navier-Stokes equations and the Volume of Fluid approach for free surface simulation. The chamber geometry was based on a U-shaped OWC. The maximum efficiency and the mean velocity of the chamber free surface were found to be 66.8% and 0.17 m/s, respectively. The numerical results for the wave height obtained through simulation were validated by comparing them to analytical expressions reported in the existing literature, and a significant level of agreement was observed. Optimizing the chamber shape parameters for the specific wave characteristics is concluded to be crucial to enhance the operating efficiency of the OWC.
{"title":"Performance of Resonant Chambers in Oscillating Water Column Devices","authors":"Juan D. Parra-Quintero, A. Rubio-Clemente, E. Chica","doi":"10.24084/repqj21.446","DOIUrl":"https://doi.org/10.24084/repqj21.446","url":null,"abstract":"The utilization of marine power potential in Colombia holds a great promise, and the oscillating water column (OWC) is one option that deserves to be explored. The wave energy conversion process using an OWC typically involves two stages: the conversion of wave power to pneumatic power in an air chamber, and the conversion of pneumatic power to electricity using a selfrectifying air turbine coupled to an electric generator. In order to improve the efficiency of the primary stage, this study is aiming at determining the hydrodynamic performance of an OWC air chamber using a numerical model based on the Reynolds Averaged Navier-Stokes equations and the Volume of Fluid approach for free surface simulation. The chamber geometry was based on a U-shaped OWC. The maximum efficiency and the mean velocity of the chamber free surface were found to be 66.8% and 0.17 m/s, respectively. The numerical results for the wave height obtained through simulation were validated by comparing them to analytical expressions reported in the existing literature, and a significant level of agreement was observed. Optimizing the chamber shape parameters for the specific wave characteristics is concluded to be crucial to enhance the operating efficiency of the OWC.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82940384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Remigio-Carmona, O. Florencias-Oliveros, J. González-de-la-Rosa
This paper presents a new qualitative method for assessing the power quality (PQ) of electrical systems using both time domain traditional indices and higher-order statistics. The method employs engineering data analysis (EDA) tools to analyse and interpret the PQ data coming from real datasets. Boxplot of each index are considered an essential tool that deserves to be included and studied when an external dataset it is analysed. But this research intends to go a step further, and for this reason a new tool for the spatial visualization of supply quality based on a radar chart is proposed. Each of its vertices constitutes an index, integrating from 3rd to 6 th order statistics with the traditional indicators SNR, SINAD and crest factor. The proposed methodology is applied to the analysis of real available signals and both, boxplot and radarchart, results are compared and commented. Finally, relationships are established between the altered indicators and the type(s) of event found in the signal.
{"title":"A Graphical method for PQ assessment: EDA tools using traditional indices and Higher-order Statistics","authors":"P. Remigio-Carmona, O. Florencias-Oliveros, J. González-de-la-Rosa","doi":"10.24084/repqj21.390","DOIUrl":"https://doi.org/10.24084/repqj21.390","url":null,"abstract":"This paper presents a new qualitative method for assessing the power quality (PQ) of electrical systems using both time domain traditional indices and higher-order statistics. The method employs engineering data analysis (EDA) tools to analyse and interpret the PQ data coming from real datasets. Boxplot of each index are considered an essential tool that deserves to be included and studied when an external dataset it is analysed. But this research intends to go a step further, and for this reason a new tool for the spatial visualization of supply quality based on a radar chart is proposed. Each of its vertices constitutes an index, integrating from 3rd to 6 th order statistics with the traditional indicators SNR, SINAD and crest factor. The proposed methodology is applied to the analysis of real available signals and both, boxplot and radarchart, results are compared and commented. Finally, relationships are established between the altered indicators and the type(s) of event found in the signal.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85053187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Djamila Rekioua, K. Kakouche, T. Rekioua, Z. Mokrani
Wind/Photovoltaic energy systems are among the most used configurations in multi-sources energy systems because their reliability, robustness and power sources complementarily. For heavy loads, it is more convenient to add backup systems (diesel generator) for an enhanced power availability. In order to protect power sources and increase their lifespan, several power management strategies are such as fuzzy logic control, artificial neural networks and metaheuristic algorithms are proposed and used in literature. This paper presents a power supervisory control (PMC) based on fuzzy logic control dedicated for photovoltaic/wind turbine/ diesel generator/battery systems. The application of the aforementioned technique makes it possible to predict how the hybrid system various operating processes would change in response to solar irradiation and wind speed variations. The study was implemented under Matlab/Simulink. To obtain more realistic results, measured weather values have been incorporated in the simulation. The application is made in a coastal town which has a good potential values of solar irradiance and wind speeds. The obtained results show that the load have been supplied while the batteries were protected due to the PMC.
{"title":"Control a Photovoltaic/Wind Turbine/Diesel generator with storage battery","authors":"Djamila Rekioua, K. Kakouche, T. Rekioua, Z. Mokrani","doi":"10.24084/repqj21.342","DOIUrl":"https://doi.org/10.24084/repqj21.342","url":null,"abstract":"Wind/Photovoltaic energy systems are among the most used configurations in multi-sources energy systems because their reliability, robustness and power sources complementarily. For heavy loads, it is more convenient to add backup systems (diesel generator) for an enhanced power availability. In order to protect power sources and increase their lifespan, several power management strategies are such as fuzzy logic control, artificial neural networks and metaheuristic algorithms are proposed and used in literature. This paper presents a power supervisory control (PMC) based on fuzzy logic control dedicated for photovoltaic/wind turbine/ diesel generator/battery systems. The application of the aforementioned technique makes it possible to predict how the hybrid system various operating processes would change in response to solar irradiation and wind speed variations. The study was implemented under Matlab/Simulink. To obtain more realistic results, measured weather values have been incorporated in the simulation. The application is made in a coastal town which has a good potential values of solar irradiance and wind speeds. The obtained results show that the load have been supplied while the batteries were protected due to the PMC.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75729241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Ballestín-Bernad, J. S. Artal-Sevil, J. A. Domínguez-Navarro
In this paper a novel analytical design methodology for wind power permanent magnet synchronous generators is presented. This kind of electric generator plays a major role in small-scale wind energy conversion systems up to 10 kW. The proposed diameter-cubed sizing equation is based both on the generator requirements, imposed by the application, and the design parameters that rely on the designer criteria. The magnetic field waveforms of both the permanent magnets field and the armature field are considered from the first moment through the winding factors, as well as the slots effects given by the Carter factor. The analytical model of the permanent magnet synchronous generator is validated with the finite element method, showing good agreement, both with no load and under load. As the generator is unsaturated, the main source of divergence between the analytical and the finite element model are the iron losses, due to the nonuniform magnetic field distribution.
{"title":"Analytical Design Methodology for Wind Power Permanent Magnet Synchronous Generators","authors":"V. Ballestín-Bernad, J. S. Artal-Sevil, J. A. Domínguez-Navarro","doi":"10.24084/repqj21.418","DOIUrl":"https://doi.org/10.24084/repqj21.418","url":null,"abstract":"In this paper a novel analytical design methodology for wind power permanent magnet synchronous generators is presented. This kind of electric generator plays a major role in small-scale wind energy conversion systems up to 10 kW. The proposed diameter-cubed sizing equation is based both on the generator requirements, imposed by the application, and the design parameters that rely on the designer criteria. The magnetic field waveforms of both the permanent magnets field and the armature field are considered from the first moment through the winding factors, as well as the slots effects given by the Carter factor. The analytical model of the permanent magnet synchronous generator is validated with the finite element method, showing good agreement, both with no load and under load. As the generator is unsaturated, the main source of divergence between the analytical and the finite element model are the iron losses, due to the nonuniform magnetic field distribution.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74239864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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