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":"60 1","pages":""},"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":"20 1","pages":""},"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}
M. Lopes, G. Acevedo, B. Menezes, O.H.F. Rabelo, L. B. Brito, A. B. Dias, A. Filho, E. G. Domingues
This study aims to present the results of the application of a computational tool developed to perform a technical-economic feasibility analysis of large-scale Parabolic Trough Collectors (PTC) solar power plants in Brazil. The gross revenue from cash flow is obtained through an energy trading model for the Regulated Contracting Environment of the Brazilian Electricity Market. The economic viability analysis uses the Net Present Value, Modified Internal Rate of Return, Discounted Payback, and Levelized Cost of Energy indicators. The parametric structural optimization method is used to optimize the technical parameters of the plant. A case study was conducted to analyse the feasibility of implementing a 100 MW PTC in the five regions of Brazil. The results indicated that the best region in Brazil to receive this technology is the northeastern region. However, the project is economically unfeasible in all cities analysed. Therefore, a sensitivity analysis of the main parameters that affect the project's net present value is carried out to evaluate the impact of the economic parameters on the economic viability of an optimized PTC plant located in the city with the best technical performance. An optimistic scenario was evaluated considering the system's response to the parameters investigated in the sensitivity analysis. For this scenario, the results pointed to the project's economic viability.
{"title":"Technical-economic feasibility analysis of a large-scale parabolic trough collectors solar power plant in Brazil","authors":"M. Lopes, G. Acevedo, B. Menezes, O.H.F. Rabelo, L. B. Brito, A. B. Dias, A. Filho, E. G. Domingues","doi":"10.24084/repqj21.316","DOIUrl":"https://doi.org/10.24084/repqj21.316","url":null,"abstract":"This study aims to present the results of the application of a computational tool developed to perform a technical-economic feasibility analysis of large-scale Parabolic Trough Collectors (PTC) solar power plants in Brazil. The gross revenue from cash flow is obtained through an energy trading model for the Regulated Contracting Environment of the Brazilian Electricity Market. The economic viability analysis uses the Net Present Value, Modified Internal Rate of Return, Discounted Payback, and Levelized Cost of Energy indicators. The parametric structural optimization method is used to optimize the technical parameters of the plant. A case study was conducted to analyse the feasibility of implementing a 100 MW PTC in the five regions of Brazil. The results indicated that the best region in Brazil to receive this technology is the northeastern region. However, the project is economically unfeasible in all cities analysed. Therefore, a sensitivity analysis of the main parameters that affect the project's net present value is carried out to evaluate the impact of the economic parameters on the economic viability of an optimized PTC plant located in the city with the best technical performance. An optimistic scenario was evaluated considering the system's response to the parameters investigated in the sensitivity analysis. For this scenario, the results pointed to the project's economic viability.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91080109","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}
R. Dufo-López, J. Lujano-Rojas, J. Bernal-Agustín, J. S. Artal-Sevil, Á. Bayod-Rújula, Tomás Cortés-Arcos, Javier Carroquino Oñate, Cristina Escriche Martínez
In this paper, we use MHOGA software for the evaluation of a hydrogen generation system powered by wind turbines. We study the state of the art of the electrolyzers, obtaining the most important characteristics and costs of PEM electrolyzers. The optimization of a Wind-H2 system is performed, obtaining the best combination of components (wind turbines and electrolyzer) and control strategy for the hydrogen production. We will compare to the Wind-only system (wind farm which injects all the electricity produced to the gird). Two cases have been evaluated regarding the electricity price: Spanish SPOT price of 2019 and of 2021, with an expected increase of 1% annual. The Wind-H2 system can be competitive to the Wind-only system if the hydrogen sale price is 4.8 €/kg for the case of 2019 SPOT prices and 6.7 €/kg for the case of 2021 SPOT prices, considering 1% annual increase in the SPOT prices and 2% for the hydrogen price.
{"title":"Utility-scale renewable hydrogen generation by wind turbines","authors":"R. Dufo-López, J. Lujano-Rojas, J. Bernal-Agustín, J. S. Artal-Sevil, Á. Bayod-Rújula, Tomás Cortés-Arcos, Javier Carroquino Oñate, Cristina Escriche Martínez","doi":"10.24084/repqj21.208","DOIUrl":"https://doi.org/10.24084/repqj21.208","url":null,"abstract":"In this paper, we use MHOGA software for the evaluation of a hydrogen generation system powered by wind turbines. We study the state of the art of the electrolyzers, obtaining the most important characteristics and costs of PEM electrolyzers. The optimization of a Wind-H2 system is performed, obtaining the best combination of components (wind turbines and electrolyzer) and control strategy for the hydrogen production. We will compare to the Wind-only system (wind farm which injects all the electricity produced to the gird). Two cases have been evaluated regarding the electricity price: Spanish SPOT price of 2019 and of 2021, with an expected increase of 1% annual. The Wind-H2 system can be competitive to the Wind-only system if the hydrogen sale price is 4.8 €/kg for the case of 2019 SPOT prices and 6.7 €/kg for the case of 2021 SPOT prices, considering 1% annual increase in the SPOT prices and 2% for the hydrogen price.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"1962 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91315964","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}
Nowadays, the promotion of renewable energy sources is a necessity. Technically, the increase of the renewable penetration in the power system (PS) is a challenge. One solution for this problem is the use of self-controlled microgrids (smartgrid, SG). In this work, the design of an algorithm to optimal manage the SG energy through the power inverter control in the SG is presented. In general, a SG consists of renewable energy sources, electrical loads and storage systems. In an isolated SG (no connected to the power system), a DC/AC (direct current / alternating current) converter (power inverter, PInv) is necessary to provide an alternating voltage to supply the loads. If the SG is connected to the PS, the PInv is used to inject the active power from the renewable energy sources.
{"title":"Inverter Control Design for the optimal management of electrical Microgrids","authors":"J. R. Vazquez, N. Magro, R. S. Herrera, A. Martin","doi":"10.24084/repqj21.310","DOIUrl":"https://doi.org/10.24084/repqj21.310","url":null,"abstract":"Nowadays, the promotion of renewable energy sources is a necessity. Technically, the increase of the renewable penetration in the power system (PS) is a challenge. One solution for this problem is the use of self-controlled microgrids (smartgrid, SG). In this work, the design of an algorithm to optimal manage the SG energy through the power inverter control in the SG is presented. In general, a SG consists of renewable energy sources, electrical loads and storage systems. In an isolated SG (no connected to the power system), a DC/AC (direct current / alternating current) converter (power inverter, PInv) is necessary to provide an alternating voltage to supply the loads. If the SG is connected to the PS, the PInv is used to inject the active power from the renewable energy sources.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82739602","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 paper presents an inverter based on the orthogonal space vectors theory (OVT inverter) and its performance. The OVT inverter consists of two constituent twolevel 3-phase inverters: the main inverter (MI) and the auxiliary one (AI). The MI is controlled in a simple way to generate the stepped output voltage and the AI works as an active filter limiting the higher harmonics in the OVT output voltage. The filtering process is formed by the use of the orthogonal space vector theory. The output voltage of the OVT inverter takes the shape of a stepped voltage comparable to the voltage generated by multilevel inverters. The AI operates as a very effective active power filter (APF) of the OVT inverter output voltage. The AI power is significantly lower in comparison to the MI power nevertheless its switching frequency affects the OVT performance. The article describes studies in which the impact of changes in the switching frequency filter inverter on the operation of the orthogonal inverter and the output voltage THD. Increasing the filter inverter switching frequency improved performance and reduced the transformer size, which acts as a summing node.
{"title":"Performance of an OVT inverter reliant on the switching frequency of the filtering inverter","authors":"A. Muc, J. Iwaszkiewicz","doi":"10.24084/repqj21.450","DOIUrl":"https://doi.org/10.24084/repqj21.450","url":null,"abstract":"The paper presents an inverter based on the orthogonal space vectors theory (OVT inverter) and its performance. The OVT inverter consists of two constituent twolevel 3-phase inverters: the main inverter (MI) and the auxiliary one (AI). The MI is controlled in a simple way to generate the stepped output voltage and the AI works as an active filter limiting the higher harmonics in the OVT output voltage. The filtering process is formed by the use of the orthogonal space vector theory. The output voltage of the OVT inverter takes the shape of a stepped voltage comparable to the voltage generated by multilevel inverters. The AI operates as a very effective active power filter (APF) of the OVT inverter output voltage. The AI power is significantly lower in comparison to the MI power nevertheless its switching frequency affects the OVT performance. The article describes studies in which the impact of changes in the switching frequency filter inverter on the operation of the orthogonal inverter and the output voltage THD. Increasing the filter inverter switching frequency improved performance and reduced the transformer size, which acts as a summing node.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"153 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81726882","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}
M. Remiro-Cinca, L. Elorza-Uriarte, G. Fernández, L. Luengo-Baranguan, D. Martinez, N. Galán Hernández
Drastic reduction of greenhouse gases emissions depends, among other factors, on a quick and efficient integration of renewable sources in the energy generation pool. In this context, hydropower nowadays represents the biggest share of the world renewable energy generation. However, in the case of European Union, many hydropower plants are about to reach their end-of-life stage and environmental regulations on the recovery of natural water flows require these plants to be dismantled. In the controversial scenario where the need to recover natural waterflows and the loss of a key source of green energy clash with each other, the objective of this work is to provide an exhaustive review of the different auxiliary services that hydropower plants can provide in the current and especially future decarbonized electricity paradigm. To this end, services such as participation in secondary and tertiary regulation markets, power purchase agreements, local energy communities, reduction of curtailments, renewable energy storage or contribution to physical inertia to the grid are analyzed and final conclusions are drawn.
{"title":"Alternative Uses of Hydroelectric Power Plants in a Decarbonized Energy Scenario","authors":"M. Remiro-Cinca, L. Elorza-Uriarte, G. Fernández, L. Luengo-Baranguan, D. Martinez, N. Galán Hernández","doi":"10.24084/repqj21.368","DOIUrl":"https://doi.org/10.24084/repqj21.368","url":null,"abstract":"Drastic reduction of greenhouse gases emissions depends, among other factors, on a quick and efficient integration of renewable sources in the energy generation pool. In this context, hydropower nowadays represents the biggest share of the world renewable energy generation. However, in the case of European Union, many hydropower plants are about to reach their end-of-life stage and environmental regulations on the recovery of natural water flows require these plants to be dismantled. In the controversial scenario where the need to recover natural waterflows and the loss of a key source of green energy clash with each other, the objective of this work is to provide an exhaustive review of the different auxiliary services that hydropower plants can provide in the current and especially future decarbonized electricity paradigm. To this end, services such as participation in secondary and tertiary regulation markets, power purchase agreements, local energy communities, reduction of curtailments, renewable energy storage or contribution to physical inertia to the grid are analyzed and final conclusions are drawn.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83881167","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}
J. Cano-Martínez, E. Peñalvo-López, V. León-Martínez, I. Valencia-Salazar
New demand-side management models have emerged as a result of rising energy prices, the development of artificial intelligence, and the rise of prosumers. The purpose of this research is to use deep learning techniques to predict the energy production and demand of a prosumer network to determine dynamic prices for the local market. Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) were two methods that were taken into consideration for forecasting consumer demand and wind and solar energy generation. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) were used to compare the various approaches. The results demonstrated that GRU, with 0.0273, 0.0158, and 49.8 in RMSE, MAE, and MAPE respectively, is the best method for predicting energy generation and consumption in our datasets. Demand management system dynamic prices were calculated on an hourly basis using input from energy generation and demand forecasts. Finally, an optimization method was developed for establishing the energy planning.
{"title":"Dynamic energy prices for residential users based on Deep Learning prediction models of consumption and renewable generation","authors":"J. Cano-Martínez, E. Peñalvo-López, V. León-Martínez, I. Valencia-Salazar","doi":"10.24084/repqj21.226","DOIUrl":"https://doi.org/10.24084/repqj21.226","url":null,"abstract":"New demand-side management models have emerged as a result of rising energy prices, the development of artificial intelligence, and the rise of prosumers. The purpose of this research is to use deep learning techniques to predict the energy production and demand of a prosumer network to determine dynamic prices for the local market. Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) were two methods that were taken into consideration for forecasting consumer demand and wind and solar energy generation. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) were used to compare the various approaches. The results demonstrated that GRU, with 0.0273, 0.0158, and 49.8 in RMSE, MAE, and MAPE respectively, is the best method for predicting energy generation and consumption in our datasets. Demand management system dynamic prices were calculated on an hourly basis using input from energy generation and demand forecasts. Finally, an optimization method was developed for establishing the energy planning.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88931908","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}
Various types of aqueous solutions are disposed of in residential, institutional, commercial, and industrial buildings. The wastewater must be treated to remove pathogens (bacteria, viruses), nutrients (nitrogen, phosphorus), and other compounds in order to maintain public health and the environment. Accumulation of untreated sewage can result in a wide range of nuisances. Most of Israel's wastewater is purified and used for irrigation every year, which amounts to 530 million cubic meters. Approximately 80 percent of wastewater recovered in Israel is recycled. By treating wastewater appropriately, agriculture, tourism, gardening, and industry can benefit. The presence of raw sewage in settlements with no sewage collection or transportation networks continues to pose a great threat even today. There is a significant energy consumption associated with wastewater treatment processes. In this study, solar energy was attempted to be integrated as a renewable energy source. With Renewable Energy Sources integrated into the process, costs will be reduced, and it will also be possible to establish decentralized facilities in areas without proper infrastructure for traditional treatment methods.
{"title":"Reducing Fossil Fuel Consumption by Incorporating Renewable Energy Sources in Wastewater Treatment Processes","authors":"H. Friman","doi":"10.24084/repqj21.360","DOIUrl":"https://doi.org/10.24084/repqj21.360","url":null,"abstract":"Various types of aqueous solutions are disposed of in residential, institutional, commercial, and industrial buildings. The wastewater must be treated to remove pathogens (bacteria, viruses), nutrients (nitrogen, phosphorus), and other compounds in order to maintain public health and the environment. Accumulation of untreated sewage can result in a wide range of nuisances. Most of Israel's wastewater is purified and used for irrigation every year, which amounts to 530 million cubic meters. Approximately 80 percent of wastewater recovered in Israel is recycled. By treating wastewater appropriately, agriculture, tourism, gardening, and industry can benefit. The presence of raw sewage in settlements with no sewage collection or transportation networks continues to pose a great threat even today. There is a significant energy consumption associated with wastewater treatment processes. In this study, solar energy was attempted to be integrated as a renewable energy source. With Renewable Energy Sources integrated into the process, costs will be reduced, and it will also be possible to establish decentralized facilities in areas without proper infrastructure for traditional treatment methods.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86494791","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}
D. M. Larruskain, P. Eguía, A. Iturregi, E. Torres, V. Valverde, A. Blázquez
Green hydrogen production from renewable energy sources has a big potential to reduce energy dependence on fossil fuel, contributing to the global goal set by the international community of net zero emissions by 2050. Electrolyzers are connected to grid with power stages that can be designed as active devices with high control capability and a remarkably fast operation. Nevertheless, in the present, they must overcome some challenges in order to ensure a reliable operation. This paper addresses the concept of protection of DC grids with electrolyzers fed from renewable energy sources. The topologies of the grid are discussed as well as protection features and fault clearing strategies. A new dynamic model for multi megawatt PEM electrolyzer is introduced. Finally, a case study with a PEM electrolyzer in a MVDC system is included.
{"title":"Protection of MVDC grids for the production of green hydrogen","authors":"D. M. Larruskain, P. Eguía, A. Iturregi, E. Torres, V. Valverde, A. Blázquez","doi":"10.24084/repqj21.260","DOIUrl":"https://doi.org/10.24084/repqj21.260","url":null,"abstract":"Green hydrogen production from renewable energy sources has a big potential to reduce energy dependence on fossil fuel, contributing to the global goal set by the international community of net zero emissions by 2050. Electrolyzers are connected to grid with power stages that can be designed as active devices with high control capability and a remarkably fast operation. Nevertheless, in the present, they must overcome some challenges in order to ensure a reliable operation. This paper addresses the concept of protection of DC grids with electrolyzers fed from renewable energy sources. The topologies of the grid are discussed as well as protection features and fault clearing strategies. A new dynamic model for multi megawatt PEM electrolyzer is introduced. Finally, a case study with a PEM electrolyzer in a MVDC system is included.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86118618","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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