Since its launch in March 2022, iEnergy has published 12 issues. iEnergy strives to promote innovation and development in the field of power and energy and to provide a high-quality academic exchange platform for global scholars. We know that the academic level of a journal is an important criterion for first-class influence; therefore, we have continued to optimize the review process and improve publication usage standards to ensure that every published paper has a high level of academic value and practical significance. In addition, we strictly control the quality of published papers and ensure that every published article, review and letter is peer-reviewed and recognized by experts.
{"title":"Toward Clean, Efficient, and Intelligent Power and Energy Systems","authors":"","doi":"10.23919/IEN.2024.0031","DOIUrl":"https://doi.org/10.23919/IEN.2024.0031","url":null,"abstract":"Since its launch in March 2022, iEnergy has published 12 issues. iEnergy strives to promote innovation and development in the field of power and energy and to provide a high-quality academic exchange platform for global scholars. We know that the academic level of a journal is an important criterion for first-class influence; therefore, we have continued to optimize the review process and improve publication usage standards to ensure that every published paper has a high level of academic value and practical significance. In addition, we strictly control the quality of published papers and ensure that every published article, review and letter is peer-reviewed and recognized by experts.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 4","pages":"185-186"},"PeriodicalIF":0.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818557","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905955","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}
Effective stability analysis is essential for the secure operation of modern power systems. As smart grids evolve with increased interconnection, renewable energy integration, and electrification, the large-scale deployment of ultra-high voltage AC/DC networks introduces various operational modes and potential fault points, posing significant challenges to maintaining stability. Traditional analysis and control methods fall short under these conditions. In contrast, emerging artificial intelligence (AI) techniques, combined with real-time data collection, provide powerful tools for enhancing stability analysis in smart grids. This paper comprehensively explores AI techniques in stability analysis, discussing the necessity and rationale for integrating AI into stability analysis through the lenses of knowledge fusion, discovery, and adaptation. It provides a thorough review of current studies on AI applications in stability analysis, addresses key challenges, and outlines future prospects for AI integration, highlighting its potential to improve analytical capabilities in complex power systems.
{"title":"Artificial Intelligence Techniques for Stability Analysis in Modern Power Systems","authors":"Jiashu Fang;Chongru Liu","doi":"10.23919/IEN.2024.0027","DOIUrl":"https://doi.org/10.23919/IEN.2024.0027","url":null,"abstract":"Effective stability analysis is essential for the secure operation of modern power systems. As smart grids evolve with increased interconnection, renewable energy integration, and electrification, the large-scale deployment of ultra-high voltage AC/DC networks introduces various operational modes and potential fault points, posing significant challenges to maintaining stability. Traditional analysis and control methods fall short under these conditions. In contrast, emerging artificial intelligence (AI) techniques, combined with real-time data collection, provide powerful tools for enhancing stability analysis in smart grids. This paper comprehensively explores AI techniques in stability analysis, discussing the necessity and rationale for integrating AI into stability analysis through the lenses of knowledge fusion, discovery, and adaptation. It provides a thorough review of current studies on AI applications in stability analysis, addresses key challenges, and outlines future prospects for AI integration, highlighting its potential to improve analytical capabilities in complex power systems.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 4","pages":"194-215"},"PeriodicalIF":0.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818563","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905802","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}
In this era of deep decarbonization, when the new mantra is green energy everywhere, can we find ourselves in a situation where we have too much green energy? Believe it or not, this is the energy paradox faced by Australia on October 3, 2024. The proliferation of photovoltaic panels on roofs is causing an over-production of electricity, threatening the grid's stability. On that day, the peak of solar energy reached a record level, far exceeding the expected consumption level. As a result, the electric load vanished, and the total demand seen by the dispatch center crossed the dangerous low limit set to ensure network stability. In Victoria, one of the wealthiest states in Australia, the electricity system is designed for demand ranging from 1,865 to 10,000 megawatts, with a typical average of 5,000 megawatts. But on Saturday, 3 October, the market fell to a record low of 1,352 megawatts. This unprecedented situation has put the electricity grid under immense pressure. While not resulting in a widespread blackout, it demonstrates the urgent need to adapt energy infrastructure and policies. Solutions such as cost-effective large-scale battery storage or virtual power plants improving the capacity to manage excess solar energy are urgently needed. Other countries, notably California, have experienced similar challenges, illustrated by the “Duck curve” (see Figure 1). The most straightforward mitigation means to “dump” the excess PV energy by capping their production, which amounts to increasing their total cost of ownership and lost opportunity for deeper decarbonization.
{"title":"EV and PV are Booming, but is the Grid Ready to Coordinate them?","authors":"Innocent Kamwa;Hajar Abdolahinia","doi":"10.23919/IEN.2024.0023","DOIUrl":"https://doi.org/10.23919/IEN.2024.0023","url":null,"abstract":"In this era of deep decarbonization, when the new mantra is green energy everywhere, can we find ourselves in a situation where we have too much green energy? Believe it or not, this is the energy paradox faced by Australia on October 3, 2024. The proliferation of photovoltaic panels on roofs is causing an over-production of electricity, threatening the grid's stability. On that day, the peak of solar energy reached a record level, far exceeding the expected consumption level. As a result, the electric load vanished, and the total demand seen by the dispatch center crossed the dangerous low limit set to ensure network stability. In Victoria, one of the wealthiest states in Australia, the electricity system is designed for demand ranging from 1,865 to 10,000 megawatts, with a typical average of 5,000 megawatts. But on Saturday, 3 October, the market fell to a record low of 1,352 megawatts. This unprecedented situation has put the electricity grid under immense pressure. While not resulting in a widespread blackout, it demonstrates the urgent need to adapt energy infrastructure and policies. Solutions such as cost-effective large-scale battery storage or virtual power plants improving the capacity to manage excess solar energy are urgently needed. Other countries, notably California, have experienced similar challenges, illustrated by the “Duck curve” (see Figure 1). The most straightforward mitigation means to “dump” the excess PV energy by capping their production, which amounts to increasing their total cost of ownership and lost opportunity for deeper decarbonization.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 4","pages":"187-188"},"PeriodicalIF":0.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10787156","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905804","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}
Effective perovskite crystallization control strategies for flexible substrates with scalable processing techniques have rarely been reported and remain an important challenge. In this study, 3-mercaptobenzoic acid (3-MBA) was introduced into the perovskite precursor to modulate the crystallization dynamics, facilitating rapid nucleation while slowing down crystal growth. This approach enabled the formation of uniform, dense large-area perovskite films on flexible substrates. Consequently, a $12 text{cm}^{2}$ flexible perovskite solar module achieved a power conversion efficiency (PCE) of 16.43%. Additionally, the module exhibited enhanced mechanical stability under various bending radii and improved light stability, marking a substantial advance toward the practical application of flexible perovskite solar modules.
{"title":"Crystallization Regulation for Stable Blade-Coated Flexible Perovskite Solar Modules","authors":"Hua Zhong;Fei Zhang","doi":"10.23919/IEN.2024.0024","DOIUrl":"https://doi.org/10.23919/IEN.2024.0024","url":null,"abstract":"Effective perovskite crystallization control strategies for flexible substrates with scalable processing techniques have rarely been reported and remain an important challenge. In this study, 3-mercaptobenzoic acid (3-MBA) was introduced into the perovskite precursor to modulate the crystallization dynamics, facilitating rapid nucleation while slowing down crystal growth. This approach enabled the formation of uniform, dense large-area perovskite films on flexible substrates. Consequently, a \u0000<tex>$12 text{cm}^{2}$</tex>\u0000 flexible perovskite solar module achieved a power conversion efficiency (PCE) of 16.43%. Additionally, the module exhibited enhanced mechanical stability under various bending radii and improved light stability, marking a substantial advance toward the practical application of flexible perovskite solar modules.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 4","pages":"189-193"},"PeriodicalIF":0.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10787155","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905931","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 accurate state-of-charge (SOC) estimation of sodium-ion batteries is the basis for their efficient application. In this paper, a new SOC estimation method suitable for sodium-ion batteries and their application conditions is proposed, which considers the combination of open circuit voltage (OCV) and internal resistance correction. First, the optimal order of equivalent circuit model is analyzed and selected, and the monotonic and stable mapping relationships between OCV and SOC, as well as between ohmic internal resistance and SOC are determined. Then, a joint estimation algorithm for battery model parameters and SOC is established, and a joint SOC correction strategy based on OCV and ohmic internal resistance is established. The test results show that OCV correction is reliable when polarization is small, that the ohmic internal resistance correction is reliable when the current fluctuation is large, and that the maximum absolute error of SOC estimation of the proposed method is not more than 2.6%.
{"title":"An Improved State-of-Charge Estimation Method for Sodium-Ion Battery Based on Combined Correction of Voltage and Internal Resistance","authors":"Yongqi Li;Cheng Chen;Youwei Wen;Qikai Lei;Kaixuan Zhang;Yifei Chen;Rui Xiong","doi":"10.23919/IEN.2024.0017","DOIUrl":"https://doi.org/10.23919/IEN.2024.0017","url":null,"abstract":"The accurate state-of-charge (SOC) estimation of sodium-ion batteries is the basis for their efficient application. In this paper, a new SOC estimation method suitable for sodium-ion batteries and their application conditions is proposed, which considers the combination of open circuit voltage (OCV) and internal resistance correction. First, the optimal order of equivalent circuit model is analyzed and selected, and the monotonic and stable mapping relationships between OCV and SOC, as well as between ohmic internal resistance and SOC are determined. Then, a joint estimation algorithm for battery model parameters and SOC is established, and a joint SOC correction strategy based on OCV and ohmic internal resistance is established. The test results show that OCV correction is reliable when polarization is small, that the ohmic internal resistance correction is reliable when the current fluctuation is large, and that the maximum absolute error of SOC estimation of the proposed method is not more than 2.6%.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"128-134"},"PeriodicalIF":0.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10689486","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368272","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}
Wenfa Kang;Jianquan Liao;Minyou Chen;Josep M. Guerrero;Kai Sun
This paper introduces a novel fully distributed economic power dispatch (EPD) strategy for distribution networks, integrating dynamic tariffs. A two-layer model is proposed: the first layer comprises the physical power distribution network, including photovoltaic (PV) sources, wind turbine (WT) generators, energy storage systems (ESS), flexible loads (FLs), and other inflexible loads. The upper layer consists of agents dedicated to communication, calculation, and control tasks. Unlike previous EPD strategies, this approach incorporates dynamic tariffs derived from voltage constraints to ensure compliance with nodal voltage constraints. Additionally, a fast distributed optimization algorithm with an event-triggered communication protocol has been developed to address the EPD problem effectively. Through mathematical and simulation analyses, the proposed algorithm's efficiency and rapid convergence capability are demonstrated.
{"title":"Distributed Event-Triggered Optimal Power Management of Distribution Networks Considering Dynamic Tariff","authors":"Wenfa Kang;Jianquan Liao;Minyou Chen;Josep M. Guerrero;Kai Sun","doi":"10.23919/IEN.2024.0016","DOIUrl":"https://doi.org/10.23919/IEN.2024.0016","url":null,"abstract":"This paper introduces a novel fully distributed economic power dispatch (EPD) strategy for distribution networks, integrating dynamic tariffs. A two-layer model is proposed: the first layer comprises the physical power distribution network, including photovoltaic (PV) sources, wind turbine (WT) generators, energy storage systems (ESS), flexible loads (FLs), and other inflexible loads. The upper layer consists of agents dedicated to communication, calculation, and control tasks. Unlike previous EPD strategies, this approach incorporates dynamic tariffs derived from voltage constraints to ensure compliance with nodal voltage constraints. Additionally, a fast distributed optimization algorithm with an event-triggered communication protocol has been developed to address the EPD problem effectively. Through mathematical and simulation analyses, the proposed algorithm's efficiency and rapid convergence capability are demonstrated.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"142-151"},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10682540","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368483","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}
In November 2018, during the 26th General Conference on Weights and Measures (CGPM) in Versailles, France, a landmark resolution was adopted to redefine four base units of the International System of Units (SI)(https://www.bipm.org/en/committees/cg/cgpm/26-2018/resolution-1). The kilogram, mole, ampere, and kelvin were redefined in terms of fundamental physical constants: the Planck constant $(h)$ , the Avogadro constant $(N_{mathrm{A}})$ , the elementary charge $(e)$ , and the Boltzmann constant $(k)$ , respectively. As illustrated in Figure 1(a), the new SI framework defines all seven base units based on fundamental constants, marking a complete transition of metrology into the quantum era. This system has been in effect globally since May 20, 2019, on World Metrology Day.
{"title":"Advancing Quantum Metrology in China's Power Grids","authors":"Shisong Li","doi":"10.23919/IEN.2024.0018","DOIUrl":"https://doi.org/10.23919/IEN.2024.0018","url":null,"abstract":"In November 2018, during the 26th General Conference on Weights and Measures (CGPM) in Versailles, France, a landmark resolution was adopted to redefine four base units of the International System of Units (SI)(https://www.bipm.org/en/committees/cg/cgpm/26-2018/resolution-1). The kilogram, mole, ampere, and kelvin were redefined in terms of fundamental physical constants: the Planck constant \u0000<tex>$(h)$</tex>\u0000, the Avogadro constant \u0000<tex>$(N_{mathrm{A}})$</tex>\u0000, the elementary charge \u0000<tex>$(e)$</tex>\u0000, and the Boltzmann constant \u0000<tex>$(k)$</tex>\u0000, respectively. As illustrated in Figure 1(a), the new SI framework defines all seven base units based on fundamental constants, marking a complete transition of metrology into the quantum era. This system has been in effect globally since May 20, 2019, on World Metrology Day.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"125-127"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368482","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}
Electric vehicles and battery energy storage are effective technical paths to achieve carbon neutrality, and lithium-ion batteries (LiBs) are very critical energy storage devices, which is of great significance to the goal. However, the battery's characteristics of instant degradation seriously affect its long life and high safety applications. The aging mechanisms of LiBs are complex and multi-faceted, strongly influenced by numerous interacting factors. Currently, the degree of capacity fading is commonly used to describe the aging of the battery, and the ratio of the maximum available capacity to the rated capacity of the battery is defined as the state of health (SOH). However, the aging or health of the battery should be multifaceted. to realize the multi-dimensional comprehensive evaluation of battery health status, a novel SOH estimation method driven by multidimensional aging characteristics is proposed through the improved single-particle model. The parameter identification and sensitivity analysis of the model were carried out during the whole cycle of life in a wide temperature environment. Nine aging characteristic parameters were obtained to describe the SOH. Combined with aging mechanisms, the current health status was evaluated from four aspects: capacity level, lithium-ion diffusion, electrochemical reaction, and power capacity. The proposed method can more comprehensively evaluate the aging characteristics of batteries, and the SOH estimation error is within 2%.
{"title":"A New Multi-Dimensional State of Health Evaluation Method for Lithium-Ion Batteries","authors":"Peng Peng;Yue Sun;Man Chen;Yuxuan Li;Zhenkai Hu;Rui Xiong","doi":"10.23919/IEN.2024.0020","DOIUrl":"https://doi.org/10.23919/IEN.2024.0020","url":null,"abstract":"Electric vehicles and battery energy storage are effective technical paths to achieve carbon neutrality, and lithium-ion batteries (LiBs) are very critical energy storage devices, which is of great significance to the goal. However, the battery's characteristics of instant degradation seriously affect its long life and high safety applications. The aging mechanisms of LiBs are complex and multi-faceted, strongly influenced by numerous interacting factors. Currently, the degree of capacity fading is commonly used to describe the aging of the battery, and the ratio of the maximum available capacity to the rated capacity of the battery is defined as the state of health (SOH). However, the aging or health of the battery should be multifaceted. to realize the multi-dimensional comprehensive evaluation of battery health status, a novel SOH estimation method driven by multidimensional aging characteristics is proposed through the improved single-particle model. The parameter identification and sensitivity analysis of the model were carried out during the whole cycle of life in a wide temperature environment. Nine aging characteristic parameters were obtained to describe the SOH. Combined with aging mechanisms, the current health status was evaluated from four aspects: capacity level, lithium-ion diffusion, electrochemical reaction, and power capacity. The proposed method can more comprehensively evaluate the aging characteristics of batteries, and the SOH estimation error is within 2%.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"175-184"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703143","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368256","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}
This paper presents an optimization model for the location and capacity of electric vehicle (EV) charging stations. The model takes the multiple factors of the “vehicle-station-grid” system into account. Then, ArcScene is used to couple the road and power grid models and ensure that the coupling system is strictly under the goal of minimizing the total social cost, which includes the operator cost, user charging cost, and power grid loss. An immune particle swarm optimization algorithm (IPSOA) is proposed in this paper to obtain the optimal coupling strategy. The simulation results show that the algorithm has good convergence and performs well in solving multi-modal problems. It also balances the interests of users, operators, and the power grid. Compared with other schemes, the grid loss cost is reduced by 11.1% and 17.8%, and the total social cost decreases by 9.96% and 3.22%.
{"title":"Optimal Urban EV Charging Station Site Selection and Capacity Determination Considering Comprehensive Benefits of Vehicle-Station-Grid","authors":"Hongwei Li;Yufeng Song;Jiuding Tan;Yi Cui;Shuaibing Li;Yongqiang Kang;Haiying Dong","doi":"10.23919/IEN.2024.0021","DOIUrl":"https://doi.org/10.23919/IEN.2024.0021","url":null,"abstract":"This paper presents an optimization model for the location and capacity of electric vehicle (EV) charging stations. The model takes the multiple factors of the “vehicle-station-grid” system into account. Then, ArcScene is used to couple the road and power grid models and ensure that the coupling system is strictly under the goal of minimizing the total social cost, which includes the operator cost, user charging cost, and power grid loss. An immune particle swarm optimization algorithm (IPSOA) is proposed in this paper to obtain the optimal coupling strategy. The simulation results show that the algorithm has good convergence and performs well in solving multi-modal problems. It also balances the interests of users, operators, and the power grid. Compared with other schemes, the grid loss cost is reduced by 11.1% and 17.8%, and the total social cost decreases by 9.96% and 3.22%.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"162-174"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368481","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}
Quantum power system state estimation (QPSSE) offers an inspiring direction for tackling the challenge of state estimation through quantum computing. Nevertheless, the current bottlenecks originate from the scarcity of practical and scalable QPSSE methodologies in the noisy intermediate-scale quantum (NISQ) era. This paper devises a NISQ-QPSSE algorithm that facilitates state estimation on real NISQ devices. Our new contributions include: (1) A variational quantum circuit (VQC)-based QPSSE formulation that empowers QPSSE analysis utilizing shallow-depth quantum circuits; (2) A variational quantum linear solver (VQLS)-based QPSSE solver integrating QPSSE iterations with VQC optimization; (3) An advanced NISQ-compatible QPSSE methodology for tackling the measurement and coefficient matrix issues on real quantum computers; (4) A noise-resilient method to alleviate the detrimental effects of noise disturbances. The encouraging test results on the simulator and real-scale systems affirm the precision, universality, and scalability of our QPSSE algorithm and demonstrate the vast potential of QPSSE in the thriving NISQ era.
{"title":"Noisy-Intermediate-Scale Quantum Power System State Estimation","authors":"Fei Feng;Peng Zhang;Yifan Zhou;Yacov A. Shamash","doi":"10.23919/IEN.2024.0019","DOIUrl":"https://doi.org/10.23919/IEN.2024.0019","url":null,"abstract":"Quantum power system state estimation (QPSSE) offers an inspiring direction for tackling the challenge of state estimation through quantum computing. Nevertheless, the current bottlenecks originate from the scarcity of practical and scalable QPSSE methodologies in the noisy intermediate-scale quantum (NISQ) era. This paper devises a NISQ-QPSSE algorithm that facilitates state estimation on real NISQ devices. Our new contributions include: (1) A variational quantum circuit (VQC)-based QPSSE formulation that empowers QPSSE analysis utilizing shallow-depth quantum circuits; (2) A variational quantum linear solver (VQLS)-based QPSSE solver integrating QPSSE iterations with VQC optimization; (3) An advanced NISQ-compatible QPSSE methodology for tackling the measurement and coefficient matrix issues on real quantum computers; (4) A noise-resilient method to alleviate the detrimental effects of noise disturbances. The encouraging test results on the simulator and real-scale systems affirm the precision, universality, and scalability of our QPSSE algorithm and demonstrate the vast potential of QPSSE in the thriving NISQ era.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"3 3","pages":"135-141"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368210","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}
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