Yalun Li;Minggao Ouyang;C. C. Chan;Xueliang Sun;Yonghua Song;Wei Cai;Yilin Xie;Yuqiong Mao
{"title":"Key Technologies and Prospects for Electric Vehicles Within Emerging Power Systems: Insights from Five Aspects","authors":"Yalun Li;Minggao Ouyang;C. C. Chan;Xueliang Sun;Yonghua Song;Wei Cai;Yilin Xie;Yuqiong Mao","doi":"10.17775/CSEEJPES.2024.00190","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2024.00190","url":null,"abstract":"The energy revolution requires coordination in energy consumption, supply, storage and institutional systems. Renewable energy generation technologies, along with their associated costs, are already fully equipped for large-scale promotion. However, energy storage remains a bottleneck, and solutions are needed through the use of electric vehicles, which traditionally play the role of energy consumption in power systems. To clarify the key technologies and institutions that support EVs as terminals for energy use, storage, and feedback, the CSEE JPES forum assembled renowned experts and scholars in relevant fields to deliver keynote reports and engage in discussions on topics such as vehicle-grid integration technology, advanced solid-state battery technology, high-performance electric motor technology, and institutional innovation in the industry chain. These experts also provided prospects for energy storage and utilization technologies capable of decarbonizing new power systems.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"439-447"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436621","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hybrid Modular Smart Transformer for Asymmetrically Bidirectional Power Flow Operation","authors":"Kangan Wang;Youngjong Ko;Rongwu Zhu;Siyu Wu;Weimin Wu;Marco Liserre","doi":"10.17775/CSEEJPES.2022.05650","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.05650","url":null,"abstract":"The presence of renewable energy resources in LV distribution networks may lead to a distribution transformer, also known as a Smart Transformer (ST), experiencing the bidirectional power flow. Therefore, the ST must have the capability to operate in both directions. However, the reverse power is less as compared to the forward power, thus the design of ST with the same capacity in both directions increases the hardware cost and decreases the system efficiency. This paper proposes a Hybrid-modular-ST (H-ST), composed of a mixed use of single active bridge-based series resonant converter and dual active bridge instead of complete use of uni-or bi-directional converter adopted in the conventional solid-state-transformer. Based on the proposed H-ST, the impacts of power imbalance among cascaded modules in reverse operation mode are analyzed and then an effective solution based on reactive power compensation combined with the characteristics of the proposed architecture is adopted. The simulation and experimental results clearly validate the effectiveness and feasibility of the theoretical analyses.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1384-1398"},"PeriodicalIF":6.9,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436625","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems","authors":"Edeh Vincent;Mehdi Korki;Mehdi Seyedmahmoudian;Alex Stojcevski;Saad Mekhilef","doi":"10.17775/CSEEJPES.2023.01250","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.01250","url":null,"abstract":"The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"797-806"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jian Xu;Zhonghao He;Siyang Liao;Yuanzhang Sun;Liangzhong Yao;Deping Ke;Jun Yang
{"title":"Detection Method for Cascading Failure of Power Systems Based on Epidemic Model","authors":"Jian Xu;Zhonghao He;Siyang Liao;Yuanzhang Sun;Liangzhong Yao;Deping Ke;Jun Yang","doi":"10.17775/CSEEJPES.2022.07410","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07410","url":null,"abstract":"The early detection of cascading failure plays an important role in the safe and stable operation of the power system with high penetration of renewable energy. This paper proposes a fault propagation dynamic model based on the epidemic model, and further puts forward a method to detect the development of cascading failures. Through the simulation of the IEEE 39-bus and 118-bus systems, this model is proven to be valid and capable of providing practical technical support for the prevention of cascading failures in power systems with high penetration of renewable energy. This paper also provides an analysis method for the choice of different protection and control measures at each stage of cascading failure, which has critical significance and follow-up value.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1356-1370"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436607","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhigang Li;Wenjian Zheng;Junbo Zhao;J. H. Zheng;Q. H. Wu
{"title":"Observability Analysis of Integrated Electricity and Heating Systems with Thermal Quasi-Dynamics in Pipelines","authors":"Zhigang Li;Wenjian Zheng;Junbo Zhao;J. H. Zheng;Q. H. Wu","doi":"10.17775/CSEEJPES.2022.04860","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.04860","url":null,"abstract":"Observability analysis (OA) is vital to obtaining the available input measurements of state estimation (SE) in an integrated electricity and heating system (IEHS). Considering the thermal quasi-dynamics in pipelines, the measurement equations in heating systems are dependent on the estimated results, leading to an interdependency between OA and SE. Conventional OA methods require measurement equations be known exactly before SE is performed, and they are not applicable to IEHSs. To bridge this gap, a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency. As its core procedure, the observable state identification and observability restoration are formulated in terms of integer linear programming. Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1145-1158"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436601","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Dolatabadi;Alireza Zakariazadeh;Alberto Borghetti;Pierluigi Siano
{"title":"Distributed Energy and Reserve Scheduling in Local Energy Communities Using L-BFGS Optimization","authors":"Mohammad Dolatabadi;Alireza Zakariazadeh;Alberto Borghetti;Pierluigi Siano","doi":"10.17775/CSEEJPES.2023.06270","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.06270","url":null,"abstract":"Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy system. Local energy communities (LECs) are expected to play a vital role in this context. However, energy scheduling in LECs presents various challenges, including the preservation of customer privacy, adherence to distribution network constraints, and the management of computational burdens. This paper introduces a novel approach for energy scheduling in renewable-based LECs using a decentralized optimization method. The proposed approach uses the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, significantly reducing the computational effort required for solving the mixed integer programming (MIP) problem. It incorporates network constraints, evaluates energy losses, and enables community participants to provide ancillary services like a regulation reserve to the grid utility. To assess its robustness and efficiency, the proposed approach is tested on an 84-bus radial distribution network. Results indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"942-952"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yi Wang;Yanxin Liu;Mingdong Wang;Venkata Dinavahi;Jun Liang;Yonghui Sun
{"title":"Resilient Smart Power Grid Synchronization Estimation Method for System Resilience with Partial Missing Measurements","authors":"Yi Wang;Yanxin Liu;Mingdong Wang;Venkata Dinavahi;Jun Liang;Yonghui Sun","doi":"10.17775/CSEEJPES.2023.06900","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.06900","url":null,"abstract":"With the increasing demand for power system stability and resilience, effective real-time tracking plays a crucial role in smart grid synchronization. However, most studies have focused on measurement noise, while they seldom think about the problem of measurement data loss in smart power grid synchronization. To solve this problem, a resilient fault-tolerant extended Kalman filter (RFTEKF) is proposed to track voltage amplitude, voltage phase angle and frequency dynamically. First, a three-phase unbalanced network's positive sequence fast estimation model is established. Then, the loss phenomenon of measurements occurs randomly, and the randomness of data loss's randomness is defined by discrete interval distribution [0], [1]. Subsequently, a resilient fault-tolerant extended Kalman filter based on the real-time estimation framework is designed using the time-stamp technique to acquire partial data loss information. Finally, extensive simulation results manifest the proposed RFTEKF can synchronize the smart grid more effectively than the traditional extended Kalman filter (EKF).","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1307-1319"},"PeriodicalIF":7.1,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Self-Sustaining of Critical Park Microgrids Integrating Mobile Emergency Generators Subjective to Major Outage","authors":"Quan Sui;Lei Zhang","doi":"10.17775/CSEEJPES.2023.01670","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.01670","url":null,"abstract":"In the event of a major power outage, critical park microgrids (PMGs) could be self-sustaining if mobile emergency generators (MEGs) are stationed to share energy. However, the need for privacy protection and the value of flexible power support on minute-time scales have not been given enough attention. To address the problem, this paper proposes a new self-sustaining strategy for critical PMGs integrating MEGs. First, to promote the cooperation between PMG and MEG, a bi-level benefit distribution mechanism is designed, where the participants' multiple roles and contributions are identified, and good behaviors are also awarded. Additionally, to increase the alliance benefits, three loss coordination modes are presented to guide the power exchange at the minute level between the MEG and PMG, considering the volatility of renewable generation and load. On this basis, a multi-time scale power-energy scheduling strategy is formulated via the alternating direction method of multipliers (ADMM) to coordinate the PMG and MEG. Finally, a dimensionality reduction technology is designed to equivalently simplify the optimization problem to facilitate the adaptive-step-based ADMM solution. Simulation studies indicate that the proposed strategy achieves the self-sustaining of PMGs integrating MEGs while increasing the economy by no less than 3.1%.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1441-1453"},"PeriodicalIF":6.9,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Conjugate Vectors Method Applied to Asymmetrical Fault Analysis of Power Electronized Power Systems","authors":"Yingbiao Li;Xing Liu;Jiabing Hu;Jianhang Zhu;Jianbo Guo","doi":"10.17775/CSEEJPES.2023.04790","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.04790","url":null,"abstract":"With the wide application of power electronized resources (PERs), the amplitude and frequency of voltages show significant time-varying characteristics under asymmetrical faults. As a result, the traditional phasor model, impedance model, and symmetrical components method based on the constant amplitude and frequency of voltages are facing great challenges. Hence, a novel asymmetrical fault analysis method based on conjugate vectors is proposed in this paper which can meet the modeling and analysis requirements of the network excited by voltages with time-varying amplitude/frequency. Furthermore, asymmetrical fault characteristics are extracted. As an application, a faulted phase identification (FPI) strategy is proposed based on the fault characteristics. The correctness and superiority of the asymmetrical fault analysis method and FPI strategy are verified in time-domain simulations and a real-time digital simulator.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1536-1549"},"PeriodicalIF":6.9,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436617","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optical Sensor with Wide Range and High Sensitivity for Internal Magnetic Field Detection of Transformer","authors":"Meng Huang;Wei Zheng;Tong Ji;Mao Ji;Tianjiao Pu;Bo Qi","doi":"10.17775/CSEEJPES.2022.07270","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07270","url":null,"abstract":"The deterioration of winding defects is one of the important causes of power transformer fires and even explosion failures. The change of leakage magnetic field distribution is the most direct response to winding defects. Currently there are few sensors suitable for online measurement of the internal magnetic field of transformers. Based on the Faraday magneto-optical effect, a magnetic field sensor with wide range and high sensitivity is proposed in this paper, which is suitable for the interior use of transformers. The straight-through optical structure with interior polarizer is adopted, and the sensor has a measurement range of 1.5 T and a sensitivity of 1 mT. It also possesses a small size, with a length of about 30 mm after encapsulation. The influence mechanism of vibration and temperature is revealed through theoretical analysis and numerical simulation. It is proposed to filter out the interference of vibration by characteristic frequency analysis and to compensate for temperature by a two-probe structure. An anti-interference test verifies the effectiveness of this method, and it can reduce the error from 80.56% to 2.63% under the combined interference of vibration and temperature.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"2230-2244"},"PeriodicalIF":6.9,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10436606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142409042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}