Pub Date : 2024-02-14DOI: 10.17775/CSEEJPES.2022.04860
Zhigang Li;Wenjian Zheng;Junbo Zhao;J. H. Zheng;Q. H. Wu
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.
可观测性分析（OA）对于获得综合电力和供热系统（IEHS）中状态估计（SE）的可用输入测量值至关重要。考虑到管道中的热准动力学，供热系统中的测量方程取决于估计结果，从而导致 OA 和 SE 之间的相互依存关系。传统的 OA 方法要求在执行 SE 之前准确知道测量方程，因此不适用于 IEHS。为了弥补这一缺陷，我们为 IEHS 设计了一种基于情景的 OA 方案，该方案可为一组预定义的时延情景提供可靠的分析结果，以应对这种相互依赖关系。作为其核心程序，可观测状态识别和可观测性恢复是通过整数线性规划来实现的。为证明所提方案的有效性和优越性，进行了数值测试。
{"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":null,"pages":null},"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}
Pub Date : 2024-02-14DOI: 10.17775/CSEEJPES.2023.06270
Mohammad Dolatabadi;Alireza Zakariazadeh;Alberto Borghetti;Pierluigi Siano
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.
{"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":null,"pages":null},"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}
Pub Date : 2024-02-14DOI: 10.17775/CSEEJPES.2023.06900
Yi Wang;Yanxin Liu;Mingdong Wang;Venkata Dinavahi;Jun Liang;Yonghui Sun
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).
{"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":null,"pages":null},"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}
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.
{"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":null,"pages":null},"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}
Pub Date : 2024-02-14DOI: 10.17775/CSEEJPES.2023.01670
Quan Sui;Lei Zhang
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%.
在发生重大停电事件时，如果移动应急发电机（MEG）能够共享能源，关键园区微电网（PMGs）就能自我维持。然而，隐私保护的需求和分钟级灵活电力支持的价值尚未得到足够重视。为解决这一问题，本文提出了一种新的关键永磁发电机整合移动应急发电机的自我维持策略。首先，为促进 PMG 与 MEG 之间的合作，本文设计了一种双层利益分配机制，即对参与者的多重角色和贡献进行识别，并对良好行为进行奖励。此外，考虑到可再生能源发电和负荷的波动性，为提高联盟效益，提出了三种损耗协调模式，以指导 MEG 和 PMG 在分钟级的电力交换。在此基础上，通过乘法交替方向法（ADMM）制定了多时间尺度的电力-能源调度策略，以协调 PMG 和 MEG。最后，设计了一种降维技术来等效简化优化问题，以促进基于自适应步长的 ADMM 求解。仿真研究表明，所提出的策略实现了永磁发电机与多元气体发电机的自我维持，同时提高了不少于 3.1% 的经济效益。
{"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":null,"pages":null},"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}
Pub Date : 2023-12-28DOI: 10.17775/CSEEJPES.2023.02720
Lirong Deng;Xuan Zhang;Tianshu Yang;Hongbin Sun;Yang Fu;Qinglai Guo;Shmuel S. Oren
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.
{"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":null,"pages":null},"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}
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.
在电力系统中，当发生冰风暴等极端事件时，大规模停电可能不可避免。这种小概率但高风险的事件会对电力系统产生巨大影响。大多数电力系统复原力研究只考虑物理方面的故障，这将导致过于理想化的结果。本文提出了一种考虑到储能（ES）系统的两阶段网络物理弹性增强方法。第一阶段计算 ES 系统的最优规划，第二阶段评估 ES 系统在灾难期间的恢复能力和增强能力。在所提出的模型中，网络故障会使控制中心的监控功能失效，从而间接损害系统。因此，当物理故障的检测和响应过程被网络故障阻断时，就会出现严重的甩负荷现象。这种故障、响应和恢复过程的网络-物理耦合机制在修改后的 IEEE 可靠性测试系统-79（RTS-79）中得到了验证。仿真结果表明，与纯物理系统相比，网络物理系统具有更高的准确性，但弹性性能有所下降。此外，在适当位置设置 ES 系统可有效提高网络物理输电系统的恢复能力，减少甩负荷。
{"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":null,"pages":null},"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}
Pub Date : 2023-12-28DOI: 10.17775/CSEEJPES.2023.06400
Qing-Chang Zhong;Marcio Stefanello
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.
{"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":null,"pages":null},"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}
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.
{"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":null,"pages":null},"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}
Pub Date : 2023-12-28DOI: 10.17775/CSEEJPES.2022.05250
Hongyuan Liang;Zhigang Li;J. H. Zheng;Q. H. Wu
Line-commutated converter (LCC)-based high-voltage DC (HVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.
{"title":"Convexification of Hybrid AC-DC Optimal Power Flow with Line-Commutated Converters","authors":"Hongyuan Liang;Zhigang Li;J. H. Zheng;Q. H. Wu","doi":"10.17775/CSEEJPES.2022.05250","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.05250","url":null,"abstract":"Line-commutated converter (LCC)-based high-voltage DC (HVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":null,"pages":null},"PeriodicalIF":7.1,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351542","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}
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