Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems.
{"title":"Shaping future low-carbon energy and transportation systems: Digital technologies and applications","authors":"Jie Song;Guannan He;Jianxiao Wang;Pingwen Zhang","doi":"10.23919/IEN.2022.0040","DOIUrl":"https://doi.org/10.23919/IEN.2022.0040","url":null,"abstract":"Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"285-305"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954284.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209223","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}
Electrostatic capacitors store electric energy through the separation of opposite charges by a layer of dielectric material sandwiched between a pair of metal electrodes. Such energy storage devices feature fast charge/discharge rates and high power densities, rendering them indispensable components in modern electronics and power apparatus, such as electric drive vehicles and pulsed power systems. One of the remaining technical bottleneck issues of electrostatic capacitors lies in the limited energy storage density that is usually orders of magnitude lower than the electrochemical counterparts, falling short of the need for compact-size electronics and electrical apparatus. For instance, electrostatic capacitors occupy $sim 35$ vol% in the power control unit of electric drive vehicles, $sim 40$ vol% in medical defibrillators, and $sim 50$ vol% in power transmission converters.
{"title":"High-entropy strategy applied to dielectric energy storage","authors":"Qi Li","doi":"10.23919/IEN.2022.0023","DOIUrl":"https://doi.org/10.23919/IEN.2022.0023","url":null,"abstract":"Electrostatic capacitors store electric energy through the separation of opposite charges by a layer of dielectric material sandwiched between a pair of metal electrodes. Such energy storage devices feature fast charge/discharge rates and high power densities, rendering them indispensable components in modern electronics and power apparatus, such as electric drive vehicles and pulsed power systems. One of the remaining technical bottleneck issues of electrostatic capacitors lies in the limited energy storage density that is usually orders of magnitude lower than the electrochemical counterparts, falling short of the need for compact-size electronics and electrical apparatus. For instance, electrostatic capacitors occupy \u0000<tex>$sim 35$</tex>\u0000 vol% in the power control unit of electric drive vehicles, \u0000<tex>$sim 40$</tex>\u0000 vol% in medical defibrillators, and \u0000<tex>$sim 50$</tex>\u0000 vol% in power transmission converters.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"270-271"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954348.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209228","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}
With the increasing development of smart grid, multi-party cooperative computation between several entities has become a typical characteristic of modern energy systems. Traditionally, data exchange among parties is inevitable, rendering how to complete multiparty collaborative optimization without exposing any private information a critical issue. This paper proposes a fully privacy-preserving distributed optimization framework based on secure multi-party computation (SMPC) with secret sharing protocols. The framework decomposes the collaborative optimization problem into a master problem and several subproblems. The process of solving the master problem is executed in the SMPC framework via the secret sharing protocols among agents. The relationships of agents are completely equal, and there is no privileged agent or any third party. The process of solving subproblems is conducted by agents individually. Compared to the traditional distributed optimization framework, the proposed SMPC-based framework can fully preserve individual private information. Exchanged data among agents are encrypted and no private information disclosure is assured. Furthermore, the framework maintains a limited and acceptable increase in computational costs while guaranteeing optimality. Case studies are conducted on test systems of different scales to demonstrate the principle of secret sharing and verify the feasibility and scalability of the proposed methodology.
{"title":"Fully privacy-preserving distributed optimization in power systems based on secret sharing","authors":"Nianfeng Tian;Qinglai Guo;Hongbin Sun;Xin Zhou","doi":"10.23919/IEN.2022.0045","DOIUrl":"https://doi.org/10.23919/IEN.2022.0045","url":null,"abstract":"With the increasing development of smart grid, multi-party cooperative computation between several entities has become a typical characteristic of modern energy systems. Traditionally, data exchange among parties is inevitable, rendering how to complete multiparty collaborative optimization without exposing any private information a critical issue. This paper proposes a fully privacy-preserving distributed optimization framework based on secure multi-party computation (SMPC) with secret sharing protocols. The framework decomposes the collaborative optimization problem into a master problem and several subproblems. The process of solving the master problem is executed in the SMPC framework via the secret sharing protocols among agents. The relationships of agents are completely equal, and there is no privileged agent or any third party. The process of solving subproblems is conducted by agents individually. Compared to the traditional distributed optimization framework, the proposed SMPC-based framework can fully preserve individual private information. Exchanged data among agents are encrypted and no private information disclosure is assured. Furthermore, the framework maintains a limited and acceptable increase in computational costs while guaranteeing optimality. Case studies are conducted on test systems of different scales to demonstrate the principle of secret sharing and verify the feasibility and scalability of the proposed methodology.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"351-362"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954351.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209357","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}
With the global trend of pursuing clean energy and decarbonization, power systems have been evolving in a fast pace that we have never seen in the history of electrification. This evolution makes the power system more dynamic and more distributed, with higher uncertainty. These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period. The conventional computing approaches will not be sufficient for future power systems. This paper provides a historical review of computing for power system operation and planning, discusses technology advancements in high performance computing (HPC), and describes the drivers for employing HPC techniques. Some high performance computing application examples with different HPC techniques, including the latest quantum computing, are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future.
{"title":"Computing for power system operation and planning: Then, now, and the future","authors":"Yousu Chen;Zhenyu Huang;Shuangshuang Jin;Ang Li","doi":"10.23919/IEN.2022.0037","DOIUrl":"https://doi.org/10.23919/IEN.2022.0037","url":null,"abstract":"With the global trend of pursuing clean energy and decarbonization, power systems have been evolving in a fast pace that we have never seen in the history of electrification. This evolution makes the power system more dynamic and more distributed, with higher uncertainty. These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period. The conventional computing approaches will not be sufficient for future power systems. This paper provides a historical review of computing for power system operation and planning, discusses technology advancements in high performance computing (HPC), and describes the drivers for employing HPC techniques. Some high performance computing application examples with different HPC techniques, including the latest quantum computing, are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"315-324"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954285.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50329297","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}
Conventional thermochemical syntheses by continuous heating under near equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways.
{"title":"Programmable heating and quenching for non-equilibrium thermochemical synthesis","authors":"Hao Zhao;Yangyang Fu","doi":"10.23919/IEN.2022.0020","DOIUrl":"https://doi.org/10.23919/IEN.2022.0020","url":null,"abstract":"Conventional thermochemical syntheses by continuous heating under near equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"277-277"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954352.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209220","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}
Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology.
{"title":"Resilient power grid for smart city","authors":"Yonghua Song;Can Wan;Xuejun Hu;Hongpei Qin;Kengweng Lao","doi":"10.23919/IEN.2022.0043","DOIUrl":"https://doi.org/10.23919/IEN.2022.0043","url":null,"abstract":"Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"325-340"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954283.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50329298","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}
Commercial biaxially oriented polypropylene (BOPP) film capacitors have been widely applied in the fields of electrical and electronic engineering. However, due to the sharp increase in electrical conduction loss as the temperature rises, the energy storage performance of BOPP films seriously degrades at elevated temperatures. In this study, the grafting modification method is facile and suitable for large-scale industrial manufacturing and has been proposed to increase the high-temperature energy storage performance of commercial BOPP films for the first time. Specifically, acrylic acid (AA) as a polar organic molecular is used to graft onto the surface of commercial BOPP films by using ultraviolet irradiation (abbreviated as BOPP-AA). The results demonstrate that the AA grafting modification not only slightly increases the dielectric constant, but also significantly reduces the leakage current density at high-temperature, greatly improving the high-temperature energy storage performance. The modified BOPP-AA films display a discharged energy density of 1.32 J/cm 3 with an efficiency of >90% at 370 kV/mm and 125 °C, which is 474% higher than that of the pristine BOPP films. This work manifests that utilizing ultraviolet grafting modification is a very efficient way to improve the high-temperature energy storage performance of commercial BOPP films as well as provides a hitherto unexplored opportunity for large-scalable production applications.
{"title":"Significantly improved high-temperature energy storage performance of commercial BOPP films by utilizing ultraviolet grafting modification","authors":"Qingguo Chi;Tianqi Wang;Changhai Zhang;Hainan Yu;Xindong Zhao;Xu Yang;Qingquan Lei;Hong Zhao;Tiandong Zhang","doi":"10.23919/IEN.2022.0046","DOIUrl":"https://doi.org/10.23919/IEN.2022.0046","url":null,"abstract":"Commercial biaxially oriented polypropylene (BOPP) film capacitors have been widely applied in the fields of electrical and electronic engineering. However, due to the sharp increase in electrical conduction loss as the temperature rises, the energy storage performance of BOPP films seriously degrades at elevated temperatures. In this study, the grafting modification method is facile and suitable for large-scale industrial manufacturing and has been proposed to increase the high-temperature energy storage performance of commercial BOPP films for the first time. Specifically, acrylic acid (AA) as a polar organic molecular is used to graft onto the surface of commercial BOPP films by using ultraviolet irradiation (abbreviated as BOPP-AA). The results demonstrate that the AA grafting modification not only slightly increases the dielectric constant, but also significantly reduces the leakage current density at high-temperature, greatly improving the high-temperature energy storage performance. The modified BOPP-AA films display a discharged energy density of 1.32 J/cm\u0000<sup>3</sup>\u0000 with an efficiency of >90% at 370 kV/mm and 125 °C, which is 474% higher than that of the pristine BOPP films. This work manifests that utilizing ultraviolet grafting modification is a very efficient way to improve the high-temperature energy storage performance of commercial BOPP films as well as provides a hitherto unexplored opportunity for large-scalable production applications.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"374-382"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954350.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50329296","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}
The equilibrium between dc bus voltage and ac bus frequency (Udc-f equilibrium) is the algorithm core of unified control strategies for ac-dc interlinking converters (ILCs), because the equilibrium implements certain mechanism. However, what the mechanism is has not been explicitly explored, which hinders further studies on unified control. This paper reveals that the state-space model of a Udc-f equilibrium controlled ILC is highly similar to that of a shaft-to-shaft machines system. Hence a detailed mechanism is discovered and named “virtual shaft-to-shaft machine (VSSM)” mechanism. A significant feature of VSSM mechanism is self-synchronization without current sampling or ac voltage sampling.
{"title":"Equilibrium mechanism between dc voltage and ac frequency for ac-dc interlinking converters","authors":"Haixu Shi;Kai Sun;Xiaochao Hou;Yunwei Li;Haihao Jiang","doi":"10.23919/IEN.2022.0042","DOIUrl":"https://doi.org/10.23919/IEN.2022.0042","url":null,"abstract":"The equilibrium between dc bus voltage and ac bus frequency (Udc-f equilibrium) is the algorithm core of unified control strategies for ac-dc interlinking converters (ILCs), because the equilibrium implements certain mechanism. However, what the mechanism is has not been explicitly explored, which hinders further studies on unified control. This paper reveals that the state-space model of a Udc-f equilibrium controlled ILC is highly similar to that of a shaft-to-shaft machines system. Hence a detailed mechanism is discovered and named “virtual shaft-to-shaft machine (VSSM)” mechanism. A significant feature of VSSM mechanism is self-synchronization without current sampling or ac voltage sampling.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"279-284"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954356.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209222","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}
Chenxi Wang;Dalin Qin;Qingsong Wen;Tian Zhou;Liang Sun;Yi Wang
Building-level load forecasting has become essential with the support of fine-grained data collected by widely deployed smart meters. It acts as a basis for arranging distributed energy resources, implementing demand response, etc. Compared to aggregated-level load, the electric load of an individual building is more stochastic and thus spawns many probabilistic forecasting methods. Many of them resort to artificial neural networks (ANN) to build forecasting models. However, a well-designed forecasting model for one building may not be suitable for others, and manually designing and tuning optimal forecasting models for various buildings are tedious and time-consuming. This paper proposes an adaptive probabilistic load forecasting model to automatically generate high-performance NN structures for different buildings and produce quantile forecasts for future loads. Specifically, we cascade the long short term memory (LSTM) layer with the adjusted Differential ArchiTecture Search (DARTS) cell and use the pinball loss function to guide the model during the improved model fitting process. A case study on an open dataset shows that our proposed model has superior performance and adaptivity over the state-of-the-art static neural network model. Besides, the improved fitting process of DARTS is proved to be more time-efficient than the original one.
{"title":"Adaptive probabilistic load forecasting for individual buildings","authors":"Chenxi Wang;Dalin Qin;Qingsong Wen;Tian Zhou;Liang Sun;Yi Wang","doi":"10.23919/IEN.2022.0041","DOIUrl":"https://doi.org/10.23919/IEN.2022.0041","url":null,"abstract":"Building-level load forecasting has become essential with the support of fine-grained data collected by widely deployed smart meters. It acts as a basis for arranging distributed energy resources, implementing demand response, etc. Compared to aggregated-level load, the electric load of an individual building is more stochastic and thus spawns many probabilistic forecasting methods. Many of them resort to artificial neural networks (ANN) to build forecasting models. However, a well-designed forecasting model for one building may not be suitable for others, and manually designing and tuning optimal forecasting models for various buildings are tedious and time-consuming. This paper proposes an adaptive probabilistic load forecasting model to automatically generate high-performance NN structures for different buildings and produce quantile forecasts for future loads. Specifically, we cascade the long short term memory (LSTM) layer with the adjusted Differential ArchiTecture Search (DARTS) cell and use the pinball loss function to guide the model during the improved model fitting process. A case study on an open dataset shows that our proposed model has superior performance and adaptivity over the state-of-the-art static neural network model. Besides, the improved fitting process of DARTS is proved to be more time-efficient than the original one.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"1 3","pages":"341-350"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9732629/9954281/09954286.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50209358","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：