Pub Date : 2025-01-27DOI: 10.35833/MPCE.2024.000316
Francisco Jesús Matas-Díaz;Manuel Barragán-Villarejo;José María Maza-Ortega
The integration of converter-interfaced generators (CIGs) into power systems is rapidly replacing traditional synchronous machines. To ensure the security of power supply, modern power systems require the application of grid-forming technologies. This study presents a systematic small-signal analysis procedure to assess the synchronization stability of gridforming virtual synchronous generators (VSGs) considering the power system characteristics. Specifically, this procedure offers guidance in tuning controller gains to enhance stability. It is applied to six different grid-forming VSGs and experimentally tested to validate the theoretical analysis. This study concludes with key findings and a discussion on the suitability of the analyzed grid-forming VSGs based on the power system characteristics.
{"title":"A Systematic Small-signal Analysis Procedure for Improving Synchronization Stability of Grid-forming Virtual Synchronous Generators","authors":"Francisco Jesús Matas-Díaz;Manuel Barragán-Villarejo;José María Maza-Ortega","doi":"10.35833/MPCE.2024.000316","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000316","url":null,"abstract":"The integration of converter-interfaced generators (CIGs) into power systems is rapidly replacing traditional synchronous machines. To ensure the security of power supply, modern power systems require the application of grid-forming technologies. This study presents a systematic small-signal analysis procedure to assess the synchronization stability of gridforming virtual synchronous generators (VSGs) considering the power system characteristics. Specifically, this procedure offers guidance in tuning controller gains to enhance stability. It is applied to six different grid-forming VSGs and experimentally tested to validate the theoretical analysis. This study concludes with key findings and a discussion on the suitability of the analyzed grid-forming VSGs based on the power system characteristics.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"102-114"},"PeriodicalIF":5.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10855740","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-23DOI: 10.35833/MPCE.2024.000677
Qing Sun;Junjie Tang;Sui Peng;Weijie Zhong;Liu Zhu;Yuan Zhao;Wenyuan Li
This paper constructs a synthetic framework for the operational reliability evaluation and risk mitigation of asynchronous grids coupled through flexible high-voltage DC (HVDC) systems (AGs-FDCSs). First of all, an analytical model for the unavailability of DC units is reformulated to refine and facilitate the reliability modeling of such flexible HVDC systems considering their time-dependent features as well as the impacts of converter station configurations. Subsequently, the operational risk associated with the redispatch procedure is extended to the reliability evaluation of composite power system, and the risk is mitigated through an optimal power flow (OPF) based short-term state assessment model. In addition, some new reliability indices like expected DC transmission power (EDCTP) and DC terminal outage probability (DCTOP) are defined to quantify the impact of the reliability of flexible HVDC systems on the entire grid. The effectiveness of the proposed framework on a modified IEEE RTS-79 system is validated with the elabo-rate discussions on the time-dependent reliability of AGs-FDC-Ss as well as the impacts of the converter station configurations.
{"title":"Operational Reliability Evaluation and Risk Mitigation of Asynchronous Grids Coupled Through Flexible HVDC Systems","authors":"Qing Sun;Junjie Tang;Sui Peng;Weijie Zhong;Liu Zhu;Yuan Zhao;Wenyuan Li","doi":"10.35833/MPCE.2024.000677","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000677","url":null,"abstract":"This paper constructs a synthetic framework for the operational reliability evaluation and risk mitigation of asynchronous grids coupled through flexible high-voltage DC (HVDC) systems (AGs-FDCSs). First of all, an analytical model for the unavailability of DC units is reformulated to refine and facilitate the reliability modeling of such flexible HVDC systems considering their time-dependent features as well as the impacts of converter station configurations. Subsequently, the operational risk associated with the redispatch procedure is extended to the reliability evaluation of composite power system, and the risk is mitigated through an optimal power flow (OPF) based short-term state assessment model. In addition, some new reliability indices like expected DC transmission power (EDCTP) and DC terminal outage probability (DCTOP) are defined to quantify the impact of the reliability of flexible HVDC systems on the entire grid. The effectiveness of the proposed framework on a modified IEEE RTS-79 system is validated with the elabo-rate discussions on the time-dependent reliability of AGs-FDC-Ss as well as the impacts of the converter station configurations.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1701-1713"},"PeriodicalIF":6.1,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10851867","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-23DOI: 10.35833/MPCE.2024.000683
Jiaxiang Hu;Weihao Hu;Di Cao;Jianjun Chen;Sayed Abulanwar;Mohammed K. Hassan;Zhe Chen;Frede Blaabjerg
This paper develops a physics-guided graph network to enhance the robustness of distribution system state estimation (DSSE) against anomalous real-time measurements, as well as a deep auto-encoder (DAE)-based detector and a Gaussian process-aided residual learning (GARL) to deal with challenges arising from topology changes. A global-scanning jumping knowledge network (GSJKN) is first designed to establish the regression rule between the measurement data and state variables. The structural information of distribution system (DS) and a global-scanning module are incorporated to guide the propagation of scarce measurements in the graph topology, contributing to valid estimation precision in sparsely measured DSs. To monitor the topology changes of the network, a DAE network is employed to learn an efficient representation of the measurements of the system under a certain topology, which can achieve online monitoring of the network structure by observing the variation tendency of the reconstruction error. When the topology change occurs, a Gaussian process with a composite kernel is applied to the modeling of the pretrained GSJKN residual to adapt to the new topology. The embedding of the physical structural knowledge enables the proposed GSJKN method to restore the missing/noisy values utilizing the adjacent measurements, which enhances the robustness to typical data acquisition errors. The adopted DAE network and special GARL-based transfer method further allow the DSSE method to rapidly detect and adapt to the topology change, as well as achieve effective quantification of the estimation uncertainties. Comparative tests on balanced and unbalanced systems demonstrate the accuracy, robustness, and adaptability of the proposed DSSE method.
{"title":"Robust Distribution System State Estimation Considering Anomalous Real-Time Measurements and Topology Change","authors":"Jiaxiang Hu;Weihao Hu;Di Cao;Jianjun Chen;Sayed Abulanwar;Mohammed K. Hassan;Zhe Chen;Frede Blaabjerg","doi":"10.35833/MPCE.2024.000683","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000683","url":null,"abstract":"This paper develops a physics-guided graph network to enhance the robustness of distribution system state estimation (DSSE) against anomalous real-time measurements, as well as a deep auto-encoder (DAE)-based detector and a Gaussian process-aided residual learning (GARL) to deal with challenges arising from topology changes. A global-scanning jumping knowledge network (GSJKN) is first designed to establish the regression rule between the measurement data and state variables. The structural information of distribution system (DS) and a global-scanning module are incorporated to guide the propagation of scarce measurements in the graph topology, contributing to valid estimation precision in sparsely measured DSs. To monitor the topology changes of the network, a DAE network is employed to learn an efficient representation of the measurements of the system under a certain topology, which can achieve online monitoring of the network structure by observing the variation tendency of the reconstruction error. When the topology change occurs, a Gaussian process with a composite kernel is applied to the modeling of the pretrained GSJKN residual to adapt to the new topology. The embedding of the physical structural knowledge enables the proposed GSJKN method to restore the missing/noisy values utilizing the adjacent measurements, which enhances the robustness to typical data acquisition errors. The adopted DAE network and special GARL-based transfer method further allow the DSSE method to rapidly detect and adapt to the topology change, as well as achieve effective quantification of the estimation uncertainties. Comparative tests on balanced and unbalanced systems demonstrate the accuracy, robustness, and adaptability of the proposed DSSE method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"928-939"},"PeriodicalIF":5.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10851869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-23DOI: 10.35833/MPCE.2024.000202
Zhongjie Guo;Jiayu Bai;Wei Wei;Haifeng Qiu;Weihao Hu
This paper studies the problem of multi-stage robust unit commitment with discrete load shedding. In the day-ahead phase, the on-off status of thermal units is scheduled. During each period of real-time dispatch, the output of thermal units and the action of load shedding are determined, and the discrete choice of load shedding corresponds to the practice of tripping substation outlets. The entire decision-making process is formulated as a multi-stage adaptive robust optimization problem with mixed-integer recourse, whose solution takes three steps. First, we propose and apply partially affine policy, which is optimized ahead of the day and restricts intertemporal dispatch variables as affine functions of previous uncertainty realizations, leaving remaining continuous and binary dispatch variables to be optimized in real time. Second, we demonstrate that the resulting model with partially affine policy can be reformulated as a two-stage robust optimization problem with mixed-integer recourse. Third, we modify the standard nested column-and-constraint generation algorithm to accelerate the inner loops by warm start. The modified algorithm solves the two-stage problem more efficiently. Case studies on the IEEE 118-bus system verify that the proposed partially affine policy outperforms conventional affine policy in terms of optimality and robustness; the modified nested column-and-constraint generation algorithm significantly reduces the total computation time; and the proposed method balances well optimality and efficiency compared with state-of-the-art methods.
{"title":"Multi-Stage Robust Unit Commitment with Discrete Load Shedding Based on Partially Affine Policy and Two-Stage Reformulation","authors":"Zhongjie Guo;Jiayu Bai;Wei Wei;Haifeng Qiu;Weihao Hu","doi":"10.35833/MPCE.2024.000202","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000202","url":null,"abstract":"This paper studies the problem of multi-stage robust unit commitment with discrete load shedding. In the day-ahead phase, the on-off status of thermal units is scheduled. During each period of real-time dispatch, the output of thermal units and the action of load shedding are determined, and the discrete choice of load shedding corresponds to the practice of tripping substation outlets. The entire decision-making process is formulated as a multi-stage adaptive robust optimization problem with mixed-integer recourse, whose solution takes three steps. First, we propose and apply partially affine policy, which is optimized ahead of the day and restricts intertemporal dispatch variables as affine functions of previous uncertainty realizations, leaving remaining continuous and binary dispatch variables to be optimized in real time. Second, we demonstrate that the resulting model with partially affine policy can be reformulated as a two-stage robust optimization problem with mixed-integer recourse. Third, we modify the standard nested column-and-constraint generation algorithm to accelerate the inner loops by warm start. The modified algorithm solves the two-stage problem more efficiently. Case studies on the IEEE 118-bus system verify that the proposed partially affine policy outperforms conventional affine policy in terms of optimality and robustness; the modified nested column-and-constraint generation algorithm significantly reduces the total computation time; and the proposed method balances well optimality and efficiency compared with state-of-the-art methods.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"415-425"},"PeriodicalIF":5.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10851868","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-23DOI: 10.35833/MPCE.2024.000810
Pengfei Han;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Zhenfei Tan;Han Wang;Gang Li
The integrated electricity-heat-hydrogen system (IEHHS) facilitates the efficient utilization of multiple energy sources, while the operational flexibility of IEHHS is hindered by the high heat inertia of alkaline electrolyzers (AELs) and the variations of renewable energy. In this paper, we propose a robust scheduling of IEHHS considering the bidirectional heat exchange (BHE) between AELs and district heating networks (DHNs). First, we propose an IEHHS model to coordinate the operations of AELs, active distribution networks (ADNs), and DHNs. In particular, we propose a BHE that not only enables the waste heat recovery for district heating but also accelerates the thermal dynamics in AELs. Then, we formulate a two-stage robust optimization (RO) problem for the IEHHS operation to consider the variability of renewable energy in ADNs. We propose a new solution method, i. e., multi-affine decision rule (MADR), to solve the two-stage RO problem with less conservatism. The simulation results show that the operational flexibility of IEHHS with BHE is remarkably improved compared with that only with unidirectional heat exchange (UHE). Compared with the traditional affine decision rule (ADR), the MADR effectively reduces the IEHHS operating costs while guaranteeing the reliability of scheduling strategies.
电-热-氢一体化系统（IEHHS）有利于多种能源的高效利用，但碱性电解槽（ael）的高热惯性和可再生能源的变化阻碍了IEHHS的运行灵活性。在本文中，我们提出了一种考虑AELs和区域供热网络之间双向热交换（BHE）的IEHHS鲁棒调度方法。首先，我们提出了一个IEHHS模型来协调AELs、active distribution networks （adn）和dhn的运作。我们特别提出了一种BHE，它不仅可以实现区域供热的废热回收，而且可以加速AELs的热动力学。然后，考虑ADNs中可再生能源的可变性，提出了IEHHS运行的两阶段鲁棒优化（RO）问题。针对保守性较差的两阶段RO问题，提出了一种新的求解方法——多仿射决策规则（MADR）。仿真结果表明，与单向换热（UHE）相比，采用BHE的IEHHS的运行灵活性得到了显著提高。与传统的仿射决策规则（ADR）相比，MADR在保证调度策略可靠性的同时，有效降低了IEHHS的运行成本。
{"title":"Robust Scheduling of Integrated Electricity-Heat-Hydrogen System Considering Bidirectional Heat Exchange Between Alkaline Electrolyzers and District Heating Networks","authors":"Pengfei Han;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Zhenfei Tan;Han Wang;Gang Li","doi":"10.35833/MPCE.2024.000810","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000810","url":null,"abstract":"The integrated electricity-heat-hydrogen system (IEHHS) facilitates the efficient utilization of multiple energy sources, while the operational flexibility of IEHHS is hindered by the high heat inertia of alkaline electrolyzers (AELs) and the variations of renewable energy. In this paper, we propose a robust scheduling of IEHHS considering the bidirectional heat exchange (BHE) between AELs and district heating networks (DHNs). First, we propose an IEHHS model to coordinate the operations of AELs, active distribution networks (ADNs), and DHNs. In particular, we propose a BHE that not only enables the waste heat recovery for district heating but also accelerates the thermal dynamics in AELs. Then, we formulate a two-stage robust optimization (RO) problem for the IEHHS operation to consider the variability of renewable energy in ADNs. We propose a new solution method, i. e., multi-affine decision rule (MADR), to solve the two-stage RO problem with less conservatism. The simulation results show that the operational flexibility of IEHHS with BHE is remarkably improved compared with that only with unidirectional heat exchange (UHE). Compared with the traditional affine decision rule (ADR), the MADR effectively reduces the IEHHS operating costs while guaranteeing the reliability of scheduling strategies.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1248-1260"},"PeriodicalIF":5.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10851866","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 rapid integration of communication and information technology into substations, the risk of cyber attacks has significantly increased. Attackers may infiltrate sub-station networks, manipulate switches, and disrupt power lines, potentially causing severe damage to the power system. To minimize such risks, this paper proposes a three-layer defender-attacker-defender (DAD) model for optimally allocating limited defensive resources to substations. To model the uncertainty surrounding the knowledge of defender of potential attacks in real-world scenarios, we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory (FAHP-DEMATEL). This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers, which serves as an evaluation metric to simulate the likelihood of various attack scenarios. These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents: the decision-maker., the attacker, and the operator. The decision-maker devises a defense strategy before the attack, while the attacker aims to identify the strategy that causes the maximum load loss. Meanwhile, the operator seeks to minimize the load loss through optimal power flow scheduling. To solve the model, the original problem is transformed into a two-layer subproblem and a single-layer master problem, which are solved iteratively using a column-and-constraint generation algorithm. Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model. Comparative experiments further highlight the advantages of the proposed model.
{"title":"Defense Strategy Against Cyber Attacks on Substations Considering Attack Resource Uncertainty","authors":"Tianlei Zang;Yujian Xiao;Yunfei Liu;Shijun Wang;Zi'an Wang;Yi Zhou","doi":"10.35833/MPCE.2024.000375","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000375","url":null,"abstract":"With the rapid integration of communication and information technology into substations, the risk of cyber attacks has significantly increased. Attackers may infiltrate sub-station networks, manipulate switches, and disrupt power lines, potentially causing severe damage to the power system. To minimize such risks, this paper proposes a three-layer defender-attacker-defender (DAD) model for optimally allocating limited defensive resources to substations. To model the uncertainty surrounding the knowledge of defender of potential attacks in real-world scenarios, we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory (FAHP-DEMATEL). This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers, which serves as an evaluation metric to simulate the likelihood of various attack scenarios. These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents: the decision-maker., the attacker, and the operator. The decision-maker devises a defense strategy before the attack, while the attacker aims to identify the strategy that causes the maximum load loss. Meanwhile, the operator seeks to minimize the load loss through optimal power flow scheduling. To solve the model, the original problem is transformed into a two-layer subproblem and a single-layer master problem, which are solved iteratively using a column-and-constraint generation algorithm. Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model. Comparative experiments further highlight the advantages of the proposed model.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1335-1346"},"PeriodicalIF":5.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10847935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-20DOI: 10.35833/MPCE.2024.000616
Guanyu Song;Chiyuan Ma;Haoran Ji;Hany M. Hasanien;Jiancheng Yu;Jinli Zhao;Hao Yu;Peng Li
The volatility of increasing distributed generators (DGs) poses a severe challenge to the supply restoration of active distribution networks (ADNs). The integration of power electronic devices represented by soft open points (SOPs) and mobile energy storages (MESs) provides a promising opportunity for rapid supply restoration with high DG penetration. Oriented for the post-event rapid restoration of ADNs, a bi-level supply restoration method is proposed considering the multi-resource co-ordination of switches, SOPs, and MESs. At the upper level (long-timescale), a multi-stage supply restoration model is developed for multiple resources under uncertainties of DGs and loads. At the lower level (short-timescale), a rolling correction restoration strategy is proposed to adapt to the DG and load fluctuations on short timescales. Finally, the effectiveness of the proposed method is verified based on a modified practical distribution network and IEEE 123-node distribution network. Re-sults show that the proposed method can fully utilize the coordination potential of multiple resources to improve load restoration ratio for ADNs with DG uncertainties.
{"title":"Bi-Level Supply Restoration Method for Active Distribution Networks Considering Multi-Resource Coordination","authors":"Guanyu Song;Chiyuan Ma;Haoran Ji;Hany M. Hasanien;Jiancheng Yu;Jinli Zhao;Hao Yu;Peng Li","doi":"10.35833/MPCE.2024.000616","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000616","url":null,"abstract":"The volatility of increasing distributed generators (DGs) poses a severe challenge to the supply restoration of active distribution networks (ADNs). The integration of power electronic devices represented by soft open points (SOPs) and mobile energy storages (MESs) provides a promising opportunity for rapid supply restoration with high DG penetration. Oriented for the post-event rapid restoration of ADNs, a bi-level supply restoration method is proposed considering the multi-resource co-ordination of switches, SOPs, and MESs. At the upper level (long-timescale), a multi-stage supply restoration model is developed for multiple resources under uncertainties of DGs and loads. At the lower level (short-timescale), a rolling correction restoration strategy is proposed to adapt to the DG and load fluctuations on short timescales. Finally, the effectiveness of the proposed method is verified based on a modified practical distribution network and IEEE 123-node distribution network. Re-sults show that the proposed method can fully utilize the coordination potential of multiple resources to improve load restoration ratio for ADNs with DG uncertainties.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"967-979"},"PeriodicalIF":5.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10847936","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems. Meanwhile, integrating small-capacity battery energy storage systems into distribution network is a growing trend in the construction of virtual power plants (VPPs), which offer great potential advantages in improving the system frequency regulation capabilities. However, the process of power dispatch for VPPs may be hindered by imperfections in the communication network, which affects their frequency control performance. Simultaneously, the economic benefits associated with their frequency control services are often overlooked. As such, we propose a co-design method of power dispatch with dynamic power regulation and communication transmission optimization for frequency control in VPPs. First, a joint design scheme of power dispatch and routing optimization under cloud-edge collaborations is proposed. This scheme encompasses a power dispatch method considering the influences of communication network and a routing optimization policy based on graph convolutional neural networks, both of which are designed to ensure the accurate and real-time frequency control service. Further, we propose a dynamic power regulation strategy under edge-edge collaborations. Specifically, according to the established correction control objective, an adaptive distributed auction algorithm (ADAA) based dynamic power regulation control method is designed to determine the optimal regulation power of VPPs, thereby improving the economic benefits of frequency control service. Finally, the simulation results validate the feasibility and superiority of the proposed co-design method for frequency control.
{"title":"Co-Design of Power Dispatch with Dynamic Power Regulation and Communication Transmission Optimization for Frequency Control in VPPs","authors":"Jinrui Guo;Chunxia Dou;Dong Yue;Zhijun Zhang;Zhanqiang Zhang;Bo Zhang","doi":"10.35833/MPCE.2024.000604","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000604","url":null,"abstract":"The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems. Meanwhile, integrating small-capacity battery energy storage systems into distribution network is a growing trend in the construction of virtual power plants (VPPs), which offer great potential advantages in improving the system frequency regulation capabilities. However, the process of power dispatch for VPPs may be hindered by imperfections in the communication network, which affects their frequency control performance. Simultaneously, the economic benefits associated with their frequency control services are often overlooked. As such, we propose a co-design method of power dispatch with dynamic power regulation and communication transmission optimization for frequency control in VPPs. First, a joint design scheme of power dispatch and routing optimization under cloud-edge collaborations is proposed. This scheme encompasses a power dispatch method considering the influences of communication network and a routing optimization policy based on graph convolutional neural networks, both of which are designed to ensure the accurate and real-time frequency control service. Further, we propose a dynamic power regulation strategy under edge-edge collaborations. Specifically, according to the established correction control objective, an adaptive distributed auction algorithm (ADAA) based dynamic power regulation control method is designed to determine the optimal regulation power of VPPs, thereby improving the economic benefits of frequency control service. Finally, the simulation results validate the feasibility and superiority of the proposed co-design method for frequency control.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1383-1394"},"PeriodicalIF":5.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10847933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The phenomenon of sub-synchronous oscillation (SSO) poses significant threats to the stability of power systems. The advent of artificial intelligence (AI) has revolutionized SSO research through data-driven methodologies, which necessitates a substantial collection of data for effective training, a requirement frequently unfulfilled in practical power systems due to limited data availability. To address the critical issue of data scarcity in training AI models, this paper proposes a novel transfer-learning-based (TL-based) Wasserstein generative adversarial network (WGAN) approach for synthetic data generation of SSO in wind farms. To improve the capability of WGAN to capture the bidirectional temporal features inherent in oscillation data, a bidirectional long short-term memory (BiLSTM) layer is introduced. Additionally, to address the training instability caused by few-shot learning scenarios, the discriminator is augmented with mini-batch discrimination (MBD) layers and gradient penalty (GP) terms. Finally, TL is leveraged to fine-tune the model, effectively bridging the gap between the training data and real-world system data. To evaluate the quality of the synthetic data, two indexes are proposed based on dynamic time warping (DTW) and frequency domain analysis, followed by a classification task. Case studies demonstrate the effectiveness of the proposed approach in swiftly generating a large volume of synthetic SSO data, thereby significantly mitigating the issue of data scarcity prevalent in SSO research.
{"title":"Transfer-Learning-Based BiLSTM-WGAN Approach for Synthetic Data Generation of Sub-Synchronous Oscillations in Wind Farms","authors":"Shuang Feng;Zhirui Zhang;Yuhang Zheng;Jiaxing Lei;Yi Tang","doi":"10.35833/MPCE.2024.000550","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000550","url":null,"abstract":"The phenomenon of sub-synchronous oscillation (SSO) poses significant threats to the stability of power systems. The advent of artificial intelligence (AI) has revolutionized SSO research through data-driven methodologies, which necessitates a substantial collection of data for effective training, a requirement frequently unfulfilled in practical power systems due to limited data availability. To address the critical issue of data scarcity in training AI models, this paper proposes a novel transfer-learning-based (TL-based) Wasserstein generative adversarial network (WGAN) approach for synthetic data generation of SSO in wind farms. To improve the capability of WGAN to capture the bidirectional temporal features inherent in oscillation data, a bidirectional long short-term memory (BiLSTM) layer is introduced. Additionally, to address the training instability caused by few-shot learning scenarios, the discriminator is augmented with mini-batch discrimination (MBD) layers and gradient penalty (GP) terms. Finally, TL is leveraged to fine-tune the model, effectively bridging the gap between the training data and real-world system data. To evaluate the quality of the synthetic data, two indexes are proposed based on dynamic time warping (DTW) and frequency domain analysis, followed by a classification task. Case studies demonstrate the effectiveness of the proposed approach in swiftly generating a large volume of synthetic SSO data, thereby significantly mitigating the issue of data scarcity prevalent in SSO research.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1199-1210"},"PeriodicalIF":5.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10847932","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-01-20DOI: 10.35833/MPCE.2024.000737
Xiangxu Wang;Weidong Li;Jiakai Shen;Qili Ding
Bulk power systems show increasingly significant frequency spatial distribution characteristics (FSDCs), leading to a huge difference in the frequency response between regions. Existing uniform-frequency models based on analytical methods are no longer applicable. This paper develops a reduced-order bus frequency response (BFR) model to preserve the FSDC and describe the frequency response of all buses. Its mathematical equation is proved to be isomorphic to the forced vibration of a mass-spring-damper system, and the closed-form solution (CFS) of the BFR model is derived by the modal analysis method and forced decoupling method in vibration mechanics. The correlation between its mathematical equation and the state equation for small-signal stability analysis is discussed, and related parameters in the CFS are defined by the eigen-analysis method without any additional devices or tools. Case studies show that the proposed reduced-order BFR model and its CFS can improve the solution accuracy while keeping the solution speed within milliseconds, which can preserve the significant FSDC of bulk power systems and represent a normalized mathematical description of distinct-frequency models.
{"title":"Reduced-Order Bus Frequency Response Model for Bulk Power Systems","authors":"Xiangxu Wang;Weidong Li;Jiakai Shen;Qili Ding","doi":"10.35833/MPCE.2024.000737","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000737","url":null,"abstract":"Bulk power systems show increasingly significant frequency spatial distribution characteristics (FSDCs), leading to a huge difference in the frequency response between regions. Existing uniform-frequency models based on analytical methods are no longer applicable. This paper develops a reduced-order bus frequency response (BFR) model to preserve the FSDC and describe the frequency response of all buses. Its mathematical equation is proved to be isomorphic to the forced vibration of a mass-spring-damper system, and the closed-form solution (CFS) of the BFR model is derived by the modal analysis method and forced decoupling method in vibration mechanics. The correlation between its mathematical equation and the state equation for small-signal stability analysis is discussed, and related parameters in the CFS are defined by the eigen-analysis method without any additional devices or tools. Case studies show that the proposed reduced-order BFR model and its CFS can improve the solution accuracy while keeping the solution speed within milliseconds, which can preserve the significant FSDC of bulk power systems and represent a normalized mathematical description of distinct-frequency models.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1127-1138"},"PeriodicalIF":5.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10847931","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：