CSEE Journal of Power and Energy Systems最新文献_第3页

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming 通过随机动态编程实现定价者社区储能的能源管理

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.02720

Lirong Deng;Xuan Zhang;Tianshu Yang;Hongbin Sun;Yang Fu;Qinglai Guo;Shmuel S. Oren

{"title":"Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming","authors":"Lirong Deng;Xuan Zhang;Tianshu Yang;Hongbin Sun;Yang Fu;Qinglai Guo;Shmuel S. Oren","doi":"10.17775/CSEEJPES.2023.02720","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.02720","url":null,"abstract":"In this paper, we propose an analytical stochastic dynamic programming (SDP) algorithm to address the optimal management problem of price-maker community energy storage. As a price-maker, energy storage smooths price differences, thus decreasing energy arbitrage value. However, this price-smoothing effect can result in significant external welfare changes by reducing consumer costs and producer revenues, which is not negligible for the community with energy storage systems. As such, we formulate community storage management as an SDP that aims to maximize both energy arbitrage and community welfare. To incorporate market interaction into the SDP format, we propose a framework that derives partial but sufficient market information to approximate impact of storage operations on market prices. Then we present an analytical SDP algorithm that does not require state discretization. Apart from computational efficiency, another advantage of the analytical algorithm is to guide energy storage to charge/discharge by directly comparing its current marginal value with expected future marginal value. Case studies indicate community-owned energy storage that maximizes both arbitrage and welfare value gains more benefits than storage that maximizes only arbitrage. The proposed algorithm ensures optimality and largely reduces the computational complexity of the standard SDP.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"492-503"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351539","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}

引用次数: 0

Cyber-Physical Resilience Enhancement for Power Transmission Systems with Energy Storage Systems 利用储能系统增强输电系统的网络物理复原力

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2022.07570

Wenhao Zhang;Dongyang Rui;Weihong Wang;Yang Guo;Zhaoxia Jing;Wenhu Tang

{"title":"Cyber-Physical Resilience Enhancement for Power Transmission Systems with Energy Storage Systems","authors":"Wenhao Zhang;Dongyang Rui;Weihong Wang;Yang Guo;Zhaoxia Jing;Wenhu Tang","doi":"10.17775/CSEEJPES.2022.07570","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07570","url":null,"abstract":"In a power system, when extreme events occur, such as ice storm, large scale blackouts may be unavoidable. Such small probability but high risk events have huge impact on power systems. Most resilience research in power systems only considers faults on the physical side, which would lead to overly idealistic results. This paper proposes a two-stage cyber-physical resilience enhancement method considering energy storage (ES) systems. The first stage calculates optimal planning of ES systems, and the second stage assesses resilience and enhancement of ES systems during the disaster. In the proposed model, cyber faults indirectly damage the system by disabling monitoring and control function of control center. As a result, when detection and response process of physical faults are blocked by cyber failures, serious load shedding occurs. Such a cyber-physical coupling mechanism of fault, response, restoration process is demonstrated in the modified IEEE Reliable Test System-79 (RTS-79). Simulation results show compared with the physical-only system, the cyber-physical system has a more accurate but degraded resilient performance. Besides, ES systems setting at proper place effectively enhance resilience of the cyber-physical transmission system with less load Shedding.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"844-855"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351558","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}

引用次数: 0

Generic Modeling and Control Framework for Power Systems Dominated by Power Converters Connected Through a Passive Transmission and Distribution Grid 通过无源输配电网连接的变流器主导电力系统的通用建模和控制框架

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.06400

Qing-Chang Zhong;Marcio Stefanello

{"title":"Generic Modeling and Control Framework for Power Systems Dominated by Power Converters Connected Through a Passive Transmission and Distribution Grid","authors":"Qing-Chang Zhong;Marcio Stefanello","doi":"10.17775/CSEEJPES.2023.06400","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.06400","url":null,"abstract":"In this paper, a compact mathematical model having an elegant structure, together with a generic control framework, are proposed for generic power systems dominated by power converters that are interconnected through a passive transmission and distribution (T&D) grid, by adopting the port-Hamiltonian (pH) systems theory and the fundamental circuit theory. The models of generic T&D lines are developed and then the model of a generic T&D grid is established. With the proposed control framework, the controlled converters are proven to be passive and Input-to-State Stable (ISS). The compact mathematical model is scalable and can be applied to power systems with multiple power electronic converters with generic passive controllers, passive local loads, and different types of passive T&D lines connected in a meshed configuration without self-loops, so it is very generic. Moreover, the resulting power system is proven to be ISS as well. The analysis is carried out without assumptions on constant frequency/voltage, constant loads, and/or lossless networks, except the need of passivity for all parts involved, and without using the Clarke/Park transformations or the graph theory. To simplify the presentation, three-phase balanced systems are adopted but the results can be easily adapted for single-phase or unbalanced three-phase systems.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 1","pages":"292-301"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139695051","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}

引用次数: 0

Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support 考虑车辆到电网功能和无功功率支持的有功配电网与电动汽车充电站联合规划

IF 6.9 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.03930

Yongheng Wang;Xinwei Shen;Yan Xu

{"title":"Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support","authors":"Yongheng Wang;Xinwei Shen;Yan Xu","doi":"10.17775/CSEEJPES.2023.03930","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.03930","url":null,"abstract":"This paper proposes a collaborative planning model for active distribution network (ADN) and electric vehicle (EV) charging stations that fully considers vehicle-to-grid (V2G) function and reactive power support of EVs in different regions. This paper employs a sequential decomposition method based on physical characteristics of the problem, breaking down the holistic problem into two sub-problems for solution. Subproblem I optimizes the charging and discharging behavior of autopilot electric vehicles (AEVs) using a mixed-integer linear programming (MILP) model. Subproblem II uses a mixed-integer second-order cone programming (MISOCP) model to plan ADN and retrofit or construct V2G charging stations (V2GCS), as well as multiple distributed generation resources (DGRs). The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN planning. The presented model is tested in the 47-node ADN in Longgang District, Shenzhen, China, and the IEEE 33-node ADN, demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"2100-2113"},"PeriodicalIF":6.9,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397513","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}

引用次数: 0

Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework 发电机跳闸方案的智能预测：基于知识融合的深度强化学习框架

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2022.08970

Lingkang Zeng;Wei Yao;Ze Hu;Hang Shuai;Zhouping Li;Jinyu Wen;Shijie Cheng

{"title":"Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework","authors":"Lingkang Zeng;Wei Yao;Ze Hu;Hang Shuai;Zhouping Li;Jinyu Wen;Shijie Cheng","doi":"10.17775/CSEEJPES.2022.08970","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.08970","url":null,"abstract":"Generator tripping scheme (GTS) is the most commonly used scheme to prevent power systems from losing safety and stability. Usually, GTS is composed of offline predetermination and real-time scenario match. However, it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power system. To improve efficiency of predetermination, this paper proposes a framework of knowledge fusion-based deep reinforcement learning (KF-DRL) for intelligent predetermination of GTS. First, the Markov Decision Process (MDP) for GTS problem is formulated based on transient instability events. Then, linear action space is developed to reduce dimensionality of action space for multiple controllable generators. Especially, KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making process. This can enhance the efficiency and learning process. Moreover, the graph convolutional network (GCN) is introduced to the policy network for enhanced learning ability. Numerical simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 1","pages":"66-75"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375964","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139695052","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}

引用次数: 0

Convexification of Hybrid AC-DC Optimal Power Flow with Line-Commutated Converters 带线路换流器的交直流混合优化功率流的凸化

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2022.05250

Hongyuan Liang;Zhigang Li;J. H. Zheng;Q. H. Wu

引用次数: 0

System Strength Assessment Based on Multi-task Learning 基于多任务学习的系统强度评估

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.00440

Baoluo Li;Shiyun Xu;Huadong Sun;Zonghan Li;Lin Yu

{"title":"System Strength Assessment Based on Multi-task Learning","authors":"Baoluo Li;Shiyun Xu;Huadong Sun;Zonghan Li;Lin Yu","doi":"10.17775/CSEEJPES.2023.00440","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.00440","url":null,"abstract":"Increase in permeability of renewable energy sources (RESs) leads to the prominent problem of voltage stability in power system, so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable range. Therefore, a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven method. First, calculation of critical short circuit ratio (CSCR) is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative indicator. Then, the construction process of CSCR dataset is proposed, and a batch simulation program of samples is developed accordingly, which provides a data basis for subsequent research. Finally, a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point, which significantly reduces evaluation error caused by weak links. Predictive performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system, which provides strong technical support for real-time monitoring of system strength.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 1","pages":"41-50"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375966","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139695066","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}

引用次数: 0

Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control 基于并行系统的有功功率校正控制人工智能量化评估与自我进化

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.00190

Tianyun Zhang;Jun Zhang;Feiyue Wang;Peidong Xu;Tianlu Gao;Haoran Zhang;Ruiqi Si

{"title":"Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control","authors":"Tianyun Zhang;Jun Zhang;Feiyue Wang;Peidong Xu;Tianlu Gao;Haoran Zhang;Ruiqi Si","doi":"10.17775/CSEEJPES.2023.00190","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.00190","url":null,"abstract":"In artificial intelligence (AI) based-complex power system management and control technology, one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution. However, there is, currently, nearly no standard technical framework for objective and quantitative intelligence evaluation. In this article, based on a parallel system framework, a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems, by resorting to human intelligence evaluation theories. On this basis, this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning (AutoRL) systems. A parallel system based quantitative assessment and self-evolution (PLASE) system for power grid corrective control AI is thereby constructed, taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment results. Experiment results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent, and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results, effectively, as well as intuitively improving its intelligence level through self-evolution.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 1","pages":"13-28"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375965","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139695071","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}

引用次数: 0

Design and Experimental Testing of a Moving Coil Actuator with Compensation Coils 带补偿线圈的动圈致动器的设计与实验测试

IF 7.1 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2023.05240

Boyuan Yin;Xianwu Zeng;John Frederick Eastham;Emelie Nilsson;Jean-francois Rouquette;Jean Rivenc;Ludovic Ybanez;Xiaoze Pei

{"title":"Design and Experimental Testing of a Moving Coil Actuator with Compensation Coils","authors":"Boyuan Yin;Xianwu Zeng;John Frederick Eastham;Emelie Nilsson;Jean-francois Rouquette;Jean Rivenc;Ludovic Ybanez;Xiaoze Pei","doi":"10.17775/CSEEJPES.2023.05240","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.05240","url":null,"abstract":"Hydrogen-powered electric aircraft have attracted significant interests aiming to achieve decarbonization targets. Onboard DC electric networks are facing great challenges in DC fault protection requirements. Vacuum interrupters are widely used in low voltage and medium voltage power systems due to being environmentally friendly with low maintenance. In this paper a moving coil actuator with compensation coils for a vacuum interrupter, as part of a hybrid direct current circuit breaker, is designed and experimentally tested. Compensation coils are used to improve operating speed compared with original moving coil actuator. Comparisons between four possible connections of compensation coils and original moving coil actuator are carried out. Experimental results show comparisons between different connections of actuator coils in terms of opening time and coil current with a range of pre-charged capacitor voltages. Dynamic performance of each actuator connection is also compared. The actuator with compensation coils is shown to have a higher current rising rate and achieve faster opening speed, which is a critical requirement for electric aircraft network protection. The parallel connection actuator achieves the highest opening speed within 3.5 ms with capacitor voltage of 50 V.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 2","pages":"707-716"},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375970","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351466","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}

引用次数: 0

Adaptive Emergency Control of Power Systems Based on Deep Belief Network 基于深度信念网络的电力系统自适应应急控制

IF 6.9 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2023-12-28 DOI: 10.17775/CSEEJPES.2022.00070

Junyong Wu;Baoqin Li;Liangliang Hao;Fashun Shi;Pengjie Zhao

{"title":"Adaptive Emergency Control of Power Systems Based on Deep Belief Network","authors":"Junyong Wu;Baoqin Li;Liangliang Hao;Fashun Shi;Pengjie Zhao","doi":"10.17775/CSEEJPES.2022.00070","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.00070","url":null,"abstract":"Emergency control is an essential means to help system maintain synchronism after fault clearance. Traditional “offline calculation, online matching” scheme faces significant challenges on adaptiveness and robustness problems. To address these challenges, this paper proposes a novel closed-loop framework of transient stability prediction (TSP) and emergency control based on Deep Belief Network (DBN). First, a hierarchical real-time anti-jitter TSP method using sliding time windows is adopted, which takes into account accuracy and rapidity at the same time. Next, a sensitivity regression model is established to mine the implicit relationship between power angles and sensitivity. When impending instability of the system is foreseen, optimal emergency control strategy can be determined in time. Lastly, responses after emergency control are fed back to the TSP model. If prediction result is still unstable, an additional control strategy will be implemented. Comprehensive numerical case studies are conducted on New England IEEE 39-bus system and Northeast Power Coordinated Council (NPCC) 140-bus system. Results show the proposed method can detect instability of system as soon as possible and assist in maintaining reliable system synchronism.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1618-1631"},"PeriodicalIF":6.9,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965777","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}

引用次数: 0