Pub Date : 2024-12-01DOI: 10.1016/j.gloei.2024.11.011
Yanhong Ma , Feng Li , Hong Zhang , Guoli Fu , Min Yi
Accurate photovoltaic (PV) power forecasting ensures the stability and reliability of power systems. To address the complex characteristics of nonlinearity, volatility, and periodicity, a novel two-stage PV forecasting method based on an optimized transformer architecture is proposed. In the first stage, an inverted transformer backbone was utilized to consider the multivariate correlation of the PV power series and capture its non-linearity and volatility. ProbSparse attention was introduced to reduce high-memory occupation and solve computational overload issues. In the second stage, a weighted series decomposition module was proposed to extract the periodicity of the PV power series, and the final forecasting results were obtained through additive reconstruction. Experiments on two public datasets showed that the proposed forecasting method has high accuracy, robustness, and computational efficiency. Its RMSE improved by 31.23% compared with that of a traditional transformer, and its MSE improved by 12.57% compared with that of a baseline model.
{"title":"Two-stage photovoltaic power forecasting method with an optimized transformer","authors":"Yanhong Ma , Feng Li , Hong Zhang , Guoli Fu , Min Yi","doi":"10.1016/j.gloei.2024.11.011","DOIUrl":"10.1016/j.gloei.2024.11.011","url":null,"abstract":"<div><div>Accurate photovoltaic (PV) power forecasting ensures the stability and reliability of power systems. To address the complex characteristics of nonlinearity, volatility, and periodicity, a novel two-stage PV forecasting method based on an optimized transformer architecture is proposed. In the first stage, an inverted transformer backbone was utilized to consider the multivariate correlation of the PV power series and capture its non-linearity and volatility. ProbSparse attention was introduced to reduce high-memory occupation and solve computational overload issues. In the second stage, a weighted series decomposition module was proposed to extract the periodicity of the PV power series, and the final forecasting results were obtained through additive reconstruction. Experiments on two public datasets showed that the proposed forecasting method has high accuracy, robustness, and computational efficiency. Its RMSE improved by 31.23% compared with that of a traditional transformer, and its MSE improved by 12.57% compared with that of a baseline model.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 6","pages":"Pages 812-824"},"PeriodicalIF":1.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143153248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.gloei.2024.11.002
Zhiyu Yan , Lu Zhang , Fulong Song
In the capacity planning of hydro-wind-solar power systems (CPHPS), it is crucial to use flexible hydropower to complement the variable wind-solar power. Hydropower units must be operated such that they avoid specific restricted operation zones, that is, forbidden zones (FZs), to avoid the risks associated with hydropower unit vibration. FZs cause limitations in terms of both the hydropower generation and flexible regulation in the hydro-wind-solar power systems. Therefore, it is essential to consider FZs when determining the optimal wind-solar power capacity that can be compensated by the hydropower. This study presents a mathematical model that incorporates the FZ constraints into the CPHPS problem. Firstly, the FZs of the hydropower units are converted into those of the hydropower plants based on set theory. Secondly, a mathematical model was formulated for the CPHPS, which couples the FZ constraints of hydropower plants with other operational constraints (e.g., power balance constraints, new energy consumption limits, and hydropower generation functions). Thirdly, dynamic programming with successive approximations is employed to solve the proposed model. Lastly, case studies were conducted on the hydro-wind-solar system of the Qingshui River to demonstrate the effectiveness of the proposed model.
{"title":"Capacity planning of hydro-wind-solar hybrid power systems considering hydropower forbidden zones","authors":"Zhiyu Yan , Lu Zhang , Fulong Song","doi":"10.1016/j.gloei.2024.11.002","DOIUrl":"10.1016/j.gloei.2024.11.002","url":null,"abstract":"<div><div>In the capacity planning of hydro-wind-solar power systems (CPHPS), it is crucial to use flexible hydropower to complement the variable wind-solar power. Hydropower units must be operated such that they avoid specific restricted operation zones, that is, forbidden zones (FZs), to avoid the risks associated with hydropower unit vibration. FZs cause limitations in terms of both the hydropower generation and flexible regulation in the hydro-wind-solar power systems. Therefore, it is essential to consider FZs when determining the optimal wind-solar power capacity that can be compensated by the hydropower. This study presents a mathematical model that incorporates the FZ constraints into the CPHPS problem. Firstly, the FZs of the hydropower units are converted into those of the hydropower plants based on set theory. Secondly, a mathematical model was formulated for the CPHPS, which couples the FZ constraints of hydropower plants with other operational constraints (e.g., power balance constraints, new energy consumption limits, and hydropower generation functions). Thirdly, dynamic programming with successive approximations is employed to solve the proposed model. Lastly, case studies were conducted on the hydro-wind-solar system of the Qingshui River to demonstrate the effectiveness of the proposed model.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 6","pages":"Pages 798-811"},"PeriodicalIF":1.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143153158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.002
Penghui Ren , Jingwen Zheng , Liang Qin , Ruyin Sun , Shiqi Yang , Jiangjun Ruan , Kaipei Liu
The application of virtual synchronous generator (VSG) control in flywheel energy storage systems (FESS) is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids. Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches, this paper proposes an adaptive VSG control strategy for a flywheel energy storage array (FESA). First, by leveraging the FESA model, a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge (SOC) equalization across units. Furthermore, energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit. The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation. In addition, VSG technology is applied for the grid-connected control of the FESA, and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback. This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation. Subsequently, a parameter design method is developed through a small-signal stability analysis. Consequently, considering the SOC of the FESA, an adaptive control strategy for the inertia damping and the P/ω droop coefficient of the VSG control is proposed to optimize the grid support services of the FESA. Finally, the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.
{"title":"Adaptive VSG control of flywheel energy storage array for frequency support in microgrids","authors":"Penghui Ren , Jingwen Zheng , Liang Qin , Ruyin Sun , Shiqi Yang , Jiangjun Ruan , Kaipei Liu","doi":"10.1016/j.gloei.2024.10.002","DOIUrl":"10.1016/j.gloei.2024.10.002","url":null,"abstract":"<div><div>The application of virtual synchronous generator (VSG) control in flywheel energy storage systems (FESS) is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids. Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches, this paper proposes an adaptive VSG control strategy for a flywheel energy storage array (FESA). First, by leveraging the FESA model, a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge (SOC) equalization across units. Furthermore, energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit. The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation. In addition, VSG technology is applied for the grid-connected control of the FESA, and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback. This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation. Subsequently, a parameter design method is developed through a small-signal stability analysis. Consequently, considering the SOC of the FESA, an adaptive control strategy for the inertia damping and the <em>P</em>/<em>ω</em> droop coefficient of the VSG control is proposed to optimize the grid support services of the FESA. Finally, the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 563-576"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.003
Zehong Liu , Yu Sun , Chao Ma
To address the global climate crisis, achieving energy transitions is imperative. Establishing a new-type power system is a key measure to achieve CO2 emissions peaking and carbon neutrality. The core goal is to transform renewable energy resources into primary power sources. The large-scale integration of high proportions of renewable energy sources and power electronic devices will dramatically change the operational mechanisms and control strategies of power systems. Existing wind and solar converters mostly adopt the grid-following control mode, which leads to significant challenges in system security and stability as it is insufficient to support the frequency and voltage of the grid. On the other hand, grid- forming control technology (GFM) can provide voltage and frequency support for the system, and thus becomes an effective measure to improve the inertia and damping characteristics of power systems. This paper illustrates the principles, control strategies, equipment types, application scenarios, and project implementation of grid-forming technology. The simulation and analysis based on a renewable-dominated real new-type power system show that GFM can significantly enhance the frequency and voltage support capacity of the power system, improve renewable energy accommodation capacity and grid transmission capacity under weak grid conditions, and play an important role in enhancing the stability and power supply reliability of renewable-dominated new-type power systems.
{"title":"An overview of grid-forming technology and its application in new-type power system","authors":"Zehong Liu , Yu Sun , Chao Ma","doi":"10.1016/j.gloei.2024.10.003","DOIUrl":"10.1016/j.gloei.2024.10.003","url":null,"abstract":"<div><div>To address the global climate crisis, achieving energy transitions is imperative. Establishing a new-type power system is a key measure to achieve CO<sub>2</sub> emissions peaking and carbon neutrality. The core goal is to transform renewable energy resources into primary power sources. The large-scale integration of high proportions of renewable energy sources and power electronic devices will dramatically change the operational mechanisms and control strategies of power systems. Existing wind and solar converters mostly adopt the grid-following control mode, which leads to significant challenges in system security and stability as it is insufficient to support the frequency and voltage of the grid. On the other hand, grid- forming control technology (GFM) can provide voltage and frequency support for the system, and thus becomes an effective measure to improve the inertia and damping characteristics of power systems. This paper illustrates the principles, control strategies, equipment types, application scenarios, and project implementation of grid-forming technology. The simulation and analysis based on a renewable-dominated real new-type power system show that GFM can significantly enhance the frequency and voltage support capacity of the power system, improve renewable energy accommodation capacity and grid transmission capacity under weak grid conditions, and play an important role in enhancing the stability and power supply reliability of renewable-dominated new-type power systems.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 541-552"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.008
Hejun Yang , Zhaochen Yang , Siyang Liu , Dabo Zhang , Yun Yu
In renewable energy systems, energy storage systems can reduce the power fluctuation of renewable energy sources and compensate for the prediction deviation. However, if the renewable energy prediction deviation is small, the energy storage system may work in an underutilized state. To efficiently utilize a renewable-energy-sided energy storage system (RES), this study proposed an optimization dispatching strategy for an energy storage system considering its unused capacity sharing. First, this study proposed an unused capacity-sharing strategy for the RES to fully utilize the storage’s unused capacity and elevate the storage’s service efficiency. Second, RES was divided into “deviation-compensating energy storage (DES)” and “sharing energy storage (SES)” to clarify the function of RES in the operation process. Third, this study established an optimized dispatching model to achieve the lowest system operating cost wherein the unused capacity- sharing strategy could be integrated. Finally, a case study was investigated, and the results indicated that the proposed model and algorithm effectively improved the utilization of renewable-energy-side energy storage systems, thereby reducing the total operation cost and pressure on peak shaving.
{"title":"Optimization dispatching strategy for an energy storage system considering its unused capacity sharing","authors":"Hejun Yang , Zhaochen Yang , Siyang Liu , Dabo Zhang , Yun Yu","doi":"10.1016/j.gloei.2024.10.008","DOIUrl":"10.1016/j.gloei.2024.10.008","url":null,"abstract":"<div><div>In renewable energy systems, energy storage systems can reduce the power fluctuation of renewable energy sources and compensate for the prediction deviation. However, if the renewable energy prediction deviation is small, the energy storage system may work in an underutilized state. To efficiently utilize a renewable-energy-sided energy storage system (RES), this study proposed an optimization dispatching strategy for an energy storage system considering its unused capacity sharing. First, this study proposed an unused capacity-sharing strategy for the RES to fully utilize the storage’s unused capacity and elevate the storage’s service efficiency. Second, RES was divided into “deviation-compensating energy storage (DES)” and “sharing energy storage (SES)” to clarify the function of RES in the operation process. Third, this study established an optimized dispatching model to achieve the lowest system operating cost wherein the unused capacity- sharing strategy could be integrated. Finally, a case study was investigated, and the results indicated that the proposed model and algorithm effectively improved the utilization of renewable-energy-side energy storage systems, thereby reducing the total operation cost and pressure on peak shaving.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 590-602"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.004
Xiao Han , Jiangpeng Feng , Yunhao Zhao , Wenlei Bai
A novel model for measuring the economics of hydrogen generation via electrolytic water projects was constructed. The model overcomes the current problem of incomplete and inaccurate assessments of the price of producing hydrogen via water, which are caused by ignoring the indirect carbon costs of different power generation sources in the process of determining the cost of producing hydrogen via water. The model was used to analyze the price of producing hydrogen via water electrolysis and its sensitivity to the electricity costs of hydrogen production and carbon prices in various provinces of China. With the continuing increase in the penetration of novel energy in China’s power system and the gradual decline in electricity prices, the price of producing hydrogen via electrolytic water is expected to be close to or even lower than that of producing hydrogen via coal in the future. Geographical differences also have a significant impact on the price of producing hydrogen, which is typically higher in the southeastern coastal region than in the western region, because of the local price of electricity and the composition of the energy sources. Provinces that have been effective in developing novel energy sources, such as Qinghai, Sichuan, and others, have been effective in the hydrogen energy industry. Sichuan and other provinces with significant new energy development have a clear advantage in the hydrogen industry. Because provinces with low hydrogen production costs can transport hydrogen to provinces with high hydrogen production costs through pipelines, hydrogen pipelines are planned from Shaanxi to Henan and from Xinjiang to Nei Mongol. These study results reveal the relative economic advantages of producing hydrogen via water electrolysis under various energy and electricity price policies and provide new perspectives on China’s energy strategy and the growth of the hydrogen energy sector.
{"title":"Economic analysis of hydrogen production from electrolyzed water technology by provinces in China","authors":"Xiao Han , Jiangpeng Feng , Yunhao Zhao , Wenlei Bai","doi":"10.1016/j.gloei.2024.10.004","DOIUrl":"10.1016/j.gloei.2024.10.004","url":null,"abstract":"<div><div>A novel model for measuring the economics of hydrogen generation via electrolytic water projects was constructed. The model overcomes the current problem of incomplete and inaccurate assessments of the price of producing hydrogen via water, which are caused by ignoring the indirect carbon costs of different power generation sources in the process of determining the cost of producing hydrogen via water. The model was used to analyze the price of producing hydrogen via water electrolysis and its sensitivity to the electricity costs of hydrogen production and carbon prices in various provinces of China. With the continuing increase in the penetration of novel energy in China’s power system and the gradual decline in electricity prices, the price of producing hydrogen via electrolytic water is expected to be close to or even lower than that of producing hydrogen via coal in the future. Geographical differences also have a significant impact on the price of producing hydrogen, which is typically higher in the southeastern coastal region than in the western region, because of the local price of electricity and the composition of the energy sources. Provinces that have been effective in developing novel energy sources, such as Qinghai, Sichuan, and others, have been effective in the hydrogen energy industry. Sichuan and other provinces with significant new energy development have a clear advantage in the hydrogen industry. Because provinces with low hydrogen production costs can transport hydrogen to provinces with high hydrogen production costs through pipelines, hydrogen pipelines are planned from Shaanxi to Henan and from Xinjiang to Nei Mongol. These study results reveal the relative economic advantages of producing hydrogen via water electrolysis under various energy and electricity price policies and provide new perspectives on China’s energy strategy and the growth of the hydrogen energy sector.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 629-641"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.001
Jianhui Meng , Yaxin Sun , Zili Zhang
The merits of compressed air energy storage (CAES) include large power generation capacity, long service life, and environmental safety. When a CAES plant is switched to the grid-connected mode and participates in grid regulation, using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage. This occurs because the CAES output voltage does not match the frequency, amplitude, and phase of the power grid voltage. Therefore, an adaptive linear active disturbance-rejection control (A-LADRC) strategy was proposed. Based on the LADRC strategy, which is more accurate than the traditional proportional integral controller, the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters, resulting in improved accuracy and response speed. The problem of large impulse current when CAES is switched to the grid-connected mode is addressed, and the frequency fluctuation is reduced. Finally, the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform. The influence of the k value in the adaptive- adjustment formula on the A-LADRC was analyzed through simulation. The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.
{"title":"Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid","authors":"Jianhui Meng , Yaxin Sun , Zili Zhang","doi":"10.1016/j.gloei.2024.10.001","DOIUrl":"10.1016/j.gloei.2024.10.001","url":null,"abstract":"<div><div>The merits of compressed air energy storage (CAES) include large power generation capacity, long service life, and environmental safety. When a CAES plant is switched to the grid-connected mode and participates in grid regulation, using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage. This occurs because the CAES output voltage does not match the frequency, amplitude, and phase of the power grid voltage. Therefore, an adaptive linear active disturbance-rejection control (A-LADRC) strategy was proposed. Based on the LADRC strategy, which is more accurate than the traditional proportional integral controller, the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters, resulting in improved accuracy and response speed. The problem of large impulse current when CAES is switched to the grid-connected mode is addressed, and the frequency fluctuation is reduced. Finally, the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform. The influence of the <em>k</em> value in the adaptive- adjustment formula on the A-LADRC was analyzed through simulation. The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 577-589"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.007
Jun Yin , Heping Jia , Laijun Chen , Dunnan Liu , Shengwei Mei , Sheng Wang
Zero-carbon parks have broad prospects in carbon neutralization. As an energy hub, hydrogen energy storage plays an important role in zero-carbon parks. However, the nonlinear characteristics of hydrogen energy storage systems (HESSs) have a significant impact on the system economy. Therefore, considering the variable working condition characteristics of HESSs, a hybrid operation method is proposed for HESS, to support the efficient and economic operation of zero-carbon parks, by analyzing the operating principle of a zero-carbon park with HESS, the system structure framework and variable condition linearization model of the equipment in HESS are established. Moreover, considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions, a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells, effectively meeting the thermoelectric load demand of zero- carbon parks in different scenarios. Finally, the economy of the proposed hybrid operation strategy was verified in typical scenarios, using a zero-carbon park embedded with a HESS.
{"title":"Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems","authors":"Jun Yin , Heping Jia , Laijun Chen , Dunnan Liu , Shengwei Mei , Sheng Wang","doi":"10.1016/j.gloei.2024.10.007","DOIUrl":"10.1016/j.gloei.2024.10.007","url":null,"abstract":"<div><div>Zero-carbon parks have broad prospects in carbon neutralization. As an energy hub, hydrogen energy storage plays an important role in zero-carbon parks. However, the nonlinear characteristics of hydrogen energy storage systems (HESSs) have a significant impact on the system economy. Therefore, considering the variable working condition characteristics of HESSs, a hybrid operation method is proposed for HESS, to support the efficient and economic operation of zero-carbon parks, by analyzing the operating principle of a zero-carbon park with HESS, the system structure framework and variable condition linearization model of the equipment in HESS are established. Moreover, considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions, a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells, effectively meeting the thermoelectric load demand of zero- carbon parks in different scenarios. Finally, the economy of the proposed hybrid operation strategy was verified in typical scenarios, using a zero-carbon park embedded with a HESS.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 603-615"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.006
Huayi Wu , Zhao Xu , Youwei Jia
To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources, energy storage systems are being deployed in microgrids. Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day. To mitigate this challenge, an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system (HBESS) operating within a microgrid is proposed, with a focus on efficient state-of-charge (SoC) planning to minimize microgrid expenses. The SoC ranges of the battery energy storage (BES) are determined in the day- ahead stage. Concurrently, the power generated by fuel cells and consumed by electrolysis device are optimized. This is followed by the intraday stage, where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized. To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage, we proposed an outer-inner column-and-constraint generation algorithm (outer-inner-CCG). Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.
{"title":"Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission","authors":"Huayi Wu , Zhao Xu , Youwei Jia","doi":"10.1016/j.gloei.2024.10.006","DOIUrl":"10.1016/j.gloei.2024.10.006","url":null,"abstract":"<div><div>To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources, energy storage systems are being deployed in microgrids. Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day. To mitigate this challenge, an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system (HBESS) operating within a microgrid is proposed, with a focus on efficient state-of-charge (SoC) planning to minimize microgrid expenses. The SoC ranges of the battery energy storage (BES) are determined in the day- ahead stage. Concurrently, the power generated by fuel cells and consumed by electrolysis device are optimized. This is followed by the intraday stage, where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized. To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage, we proposed an outer-inner column-and-constraint generation algorithm (outer-inner-CCG). Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 5","pages":"Pages 616-628"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.gloei.2024.10.005
Ning Zhou , Bowen Shang , Mingming Xu , Lei Peng , Guang Feng
Improving the accuracy of solar power forecasting is crucial to ensure grid stability, optimize solar power plant operations, and enhance grid dispatch efficiency. Although hybrid neural network models can effectively address the complexities of environmental data and power prediction uncertainties, challenges such as labor-intensive parameter adjustments and complex optimization processes persist. Thus, this study proposed a novel approach for solar power prediction using a hybrid model (CNN-LSTM-attention) that combines a convolutional neural network (CNN), long short- term memory (LSTM), and attention mechanisms. The model incorporates Bayesian optimization to refine the parameters and enhance the prediction accuracy. To prepare high-quality training data, the solar power data were first preprocessed, including feature selection, data cleaning, imputation, and smoothing. The processed data were then used to train a hybrid model based on the CNN-LSTM-attention architecture, followed by hyperparameter optimization employing Bayesian methods. The experimental results indicated that within acceptable model training times, the CNN-LSTM-attention model outperformed the LSTM, GRU, CNN-LSTM, CNN-LSTM with autoencoders, and parallel CNN-LSTM attention models. Furthermore, following Bayesian optimization, the optimized model demonstrated significantly reduced prediction errors during periods of data volatility compared to the original model, as evidenced by MRE evaluations. This highlights the clear advantage of the optimized model in forecasting fluctuating data.
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