Journal of Modern Power Systems and Clean Energy最新文献_第4页

Offline-Training Online-Execution Framework for Volt-Var Control in Distribution Networks 配电网电压无功控制的离线训练在线执行框架

IF 6.1 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-02-21 DOI: 10.35833/MPCE.2024.000887

Shu Zheng;Zhi Wu;Xiao Zhang;Wei Gu;Jingtao Zhao;Zhihua Xu

{"title":"Offline-Training Online-Execution Framework for Volt-Var Control in Distribution Networks","authors":"Shu Zheng;Zhi Wu;Xiao Zhang;Wei Gu;Jingtao Zhao;Zhihua Xu","doi":"10.35833/MPCE.2024.000887","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000887","url":null,"abstract":"With the increasing integration of uncertain distributed renewable energies (DREs) into distribution networks (DNs), communication bottlenecks and the limited deployment of measurement devices pose significant challenges for advanced data-driven voltage control strategies such as deep reinforcement learning (DRL). To address these issues, this paper proposes an offline-training online-execution framework for volt-var control in DNs. In the offline-training phase, a graph convolutional network (GCN) -based denoising autoencoder (DAE), referred to as the deep learning (DL) agent, is designed and trained to capture spatial correlations among limited physical quantities. This agent predicts voltage values for nodes with missing measurements using historical load data, DRE outputs, and global voltages from simulations. Furthermore, the dual-timescale voltage control problem is formulated as a multi-agent Markov decision process. A DRL agent employing the multi-agent soft actor-critic (MASAC) algorithm is trained to regulate the tap position of on-load tap changer (OLTC) and reactive power output of photovoltaic (PV) inverters. In the online-execution phase, the DL agent supplements the limited measurement data, providing enhanced global observations for the DRL agent. This enables precise equipment control based on improved system state estimation. The proposed framework is validated on two modified IEEE test systems. Numerical results demonstrate its ability to effectively reconstruct missing measurements and achieve rapid, and accurate voltage control even under severe measurement deficiencies.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1726-1737"},"PeriodicalIF":6.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10899105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090133","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}

引用次数: 0

Reshaping Reactive Power Control Loop to Suppress Sub-synchronous Oscillation of Grid-forming Converters at Low Power Levels 改造无功控制回路抑制低功率变流器的次同步振荡

IF 6.1 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-02-21 DOI: 10.35833/MPCE.2024.000903

Jinhao Wang;Chao Wu;Qianchen Sun;Yakun Liu;Yong Wang

引用次数: 0

Quasi-Deterministic Proxy for Network-Constrained Stochastic Unit Commitment 网络约束随机单元承诺的准确定性代理

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-02-21 DOI: 10.35833/MPCE.2024.001046

Xuan Liu;Antonio J. Conejo

引用次数: 0

Evolving Symbolic Model for Dynamic Security Assessment in Power Systems 电力系统动态安全评估的演化符号模型

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000478

Francisco S. Fernandes;Ricardo J. Bessa;João Peças Lopes

引用次数: 0

A Decentralized Peer-to-Peer Framework for Integrated Electricity-Heat-Carbon Sharing Among Multiple Microgrids 多微电网集成电-热-碳共享的分散式点对点框架

IF 6.1 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000618

Jie Wang;Hongjie Jia;Xiaolong Jin;Xiaodan Yu;Yunfei Mu;Kai Hou;Wei Wei;Jiarui Zhang;He Meng

{"title":"A Decentralized Peer-to-Peer Framework for Integrated Electricity-Heat-Carbon Sharing Among Multiple Microgrids","authors":"Jie Wang;Hongjie Jia;Xiaolong Jin;Xiaodan Yu;Yunfei Mu;Kai Hou;Wei Wei;Jiarui Zhang;He Meng","doi":"10.35833/MPCE.2024.000618","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000618","url":null,"abstract":"The increasing focus on carbon neutrality has led to heightened interest in multiple microgrids (MGs) due to their potential to significantly reduce emissions by the integrated electricity-heat-carbon sharing among them. In this paper, a decentralized peer-to-peer (P2P) framework for integrated electricity-heat-carbon sharing is proposed to optimize the trading process of multi-energy and carbon among multiple MGs. The proposed framework considers certified emission reductions (CERs) of photovoltaic (PV) systems in each MG, and carbon allocation and trading among multiple MGs. The P2P trading behaviors among multiple MGs are modelled as a non-cooperative game. A decentralized optimization method is then developed using a price-based incentive scheme to solve the non-cooperative game and optimize the transactions of the electricity-heat-carbon jointly. The optimization problem is solved using sub-gradient in a decentralized manner. And the Nash equilibrium of the non-cooperative game is proven to exist uniquely, ensuring the convergence of the model. Furthermore, the proposed decentralized optimization method safeguards the private information of the MGs. Numerical results show that the total operational cost of the MGs and the carbon emissions can be reduced significantly.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1787-1799"},"PeriodicalIF":6.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100448","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}

引用次数: 0

Deep-Learning-Based Short-Term Voltage Stability Assessment with Topology-Adaptive Voltage Dynamic Feature and Domain Transfer 基于拓扑自适应电压动态特征和域转移的深度学习短期电压稳定性评估

IF 6.1 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000507

Xin Chen;Long Huo;Chengqian Sun

{"title":"Deep-Learning-Based Short-Term Voltage Stability Assessment with Topology-Adaptive Voltage Dynamic Feature and Domain Transfer","authors":"Xin Chen;Long Huo;Chengqian Sun","doi":"10.35833/MPCE.2024.000507","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000507","url":null,"abstract":"Short-term voltage stability (STVS) assessment is a critical monitoring technology in modern power systems. During daily operations, transmission lines may switch on or off due to scheduled maintenance or unexpected faults, which poses challenges to the STVS assessment under varying topology change conditions. To adapt the STVS assessment to the system topology changes, we propose a deep-learning-based STVS assessment model with the topology-adaptive voltage dynamic feature and the fine-tuning domain transfer for power systems with changing system topologies. The topology-adaptive voltage dynamic feature, extracted from streaming time-series data of phasor measurement units (PMUs), is used to characterize transient voltage stability. The voltage dynamic features depend on the balance of reactive power flow and system topology, effectively revealing both spatiotemporal patterns of post-disturbance system dynamics. The simulation results based on large disturbances in the New England 39-bus power system demonstrate that the proposed model achieves superior STVS assessment performance, with an accuracy of 99.65% in predicting voltage stability compared with the existing deep learning methods. The proposed model also performs well when applied to the larger IEEE 145-bus power system. The fine-tuning domain transfer of the proposed model adapts very well to system topology changes in power systems. It achieves an accuracy of 99.50% in predicting the STVS for the New England 39-bus power system with the transmission line alternation. Further-more, the proposed model demonstrates strong robustness to noisy and missing data.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1545-1555"},"PeriodicalIF":6.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089982","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}

引用次数: 0

Fast Frequency Support of Self-Synchronizing Voltage Source Inverter Under Weak Grid Based on Adaptive Additional Damping Control 基于自适应附加阻尼控制的弱电网自同步电压源逆变器的快速频率支持

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000687

Youze Fu;Yandong Chen;Zili Wang;Zhiwei Xie;Xuyang Li

{"title":"Fast Frequency Support of Self-Synchronizing Voltage Source Inverter Under Weak Grid Based on Adaptive Additional Damping Control","authors":"Youze Fu;Yandong Chen;Zili Wang;Zhiwei Xie;Xuyang Li","doi":"10.35833/MPCE.2024.000687","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000687","url":null,"abstract":"The self-synchronizing voltage source inverter (SSVSI) is widely studied because of its grid-forming capability. However, the slow response of the active power control loop (APCL) under the weak grid makes it difficult for the SSVSI to quickly support the frequency of a low-inertia grid. In this paper, a grid framework is established to analyze the frequency support service process of the SSVSI, and the shortcomings of the regulation of the damping coefficient and virtual inertia co-efficient for frequency support are analyzed. Then, an adaptive additional damping control method is proposed to optimize the ability of SSVSI to support the grid frequency. The proposed control method adjusts the damping of the APCL without affecting the system steady-state characteristics, which improves the active power response speed of the SSVSI. Besides, the proposed control method adaptively adjusts the additional damping coefficient based on the active power response without measuring the grid parameters. Compared with other forms of control, the proposed control method excels in minimizing the rate of change of frequency (RoCoF) and the frequency deviation (FD) within the grid, without succumbing to the constraints posed by unknown grid parameters. Furthermore, the analysis of the system stability is also presented. Finally, the experimental hardware results obtained from a miniaturized grid proto-type are presented, corroborating the effectiveness of the proposed control method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1458-1467"},"PeriodicalIF":5.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716122","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}

引用次数: 0

Low-Frequency Impedance Modeling of Wind Energy Conversion System Considering Mechanical Dynamics and Operating Regions 考虑机械动力学和工作区域的风能转换系统低频阻抗建模

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000518

Peng Wang;Haoran Zhao;Jia Luo;Vladimir Terzija

{"title":"Low-Frequency Impedance Modeling of Wind Energy Conversion System Considering Mechanical Dynamics and Operating Regions","authors":"Peng Wang;Haoran Zhao;Jia Luo;Vladimir Terzija","doi":"10.35833/MPCE.2024.000518","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000518","url":null,"abstract":"Oscillation accidents emerge in power systems integrated with increasing penetration of renewable energy sources. The impedance of electromagnetic dynamics is investigated in recent years, where the mechanical dynamics are neglected. So far, the low-frequency oscillations are not well addressed with the impedance analysis method. A novel analytical impedance is formulated and implemented for wind energy conversion system consisting of wind turbine generators (WTGs) and wind farm, which fills the gap in the mechanical dynamics of the impedance. Instead of assuming constant values, the electromechanical dynamics of the rotor speed and the pitch angle are involved in the WTG impedance. Besides, the impedance framework is generally and modularly designed and is adaptive to different operating regions. With the developed analytical impedance, the stability assessment can cover the low-frequency oscillations, providing an in-depth insight into the mechanical parameters influencing the small-signal stability performance. As an application, the impedance characteristic and stability performance of systems with active power reserve for grid supporting are analyzed and optimized. Furthermore, the shafting torsional vibrations of WTGs in wind farms are analyzed with modal decomposition and the low-frequency impedance model. The improved accuracy of the developed analytical impedance is illustrated by comparison with commonly used impedance, which ignores the coupling between the electrical and mechanical dynamics. It is proven that the mechanical dynamics have a significant influence on the impedance, particularly in the low-frequency range. Experimental validation is carried out to validate the low-frequency impedance model and the stability performance.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1224-1237"},"PeriodicalIF":5.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716306","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}

引用次数: 0

Generic Multi-Output Spectral Representation Method for Uncertainty Propagation Analysis of Power System Dynamics 电力系统动力学不确定性传播分析的通用多输出谱表示方法

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000586

Zhaoyuan Wang;Siqi Bu

引用次数: 0

Smart Inverter Enabled Meter Encoding for Detecting False Data Injection Attacks in Distribution System State Estimation 基于智能逆变器的电表编码检测配电系统状态估计中的假数据注入攻击

IF 6.1 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2025-01-30 DOI: 10.35833/MPCE.2024.000882

Hang Zhang;Bo Liu;Hongyu Wu

{"title":"Smart Inverter Enabled Meter Encoding for Detecting False Data Injection Attacks in Distribution System State Estimation","authors":"Hang Zhang;Bo Liu;Hongyu Wu","doi":"10.35833/MPCE.2024.000882","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000882","url":null,"abstract":"Meter encoding, as a side-effect-free scheme, has been proposed to detect false data injection (FDI) attacks without significantly affecting the operation of power systems. However, existing meter encoding schemes either require encoding lots of measurements from different buses to protect a substantial proportion of a power system or are unhidden from alert attackers. To address these issues, this paper proposes a smart in-verter enabled meter encoding scheme for detecting FDI attacks in distribution system state estimation. The proposed scheme only encodes the measurements from the existing programmable smart inverters. Meanwhile, this scheme can protect all the downstream buses from the encoded inverter bus. Compared with existing schemes, the proposed scheme encodes fewer meters when protecting the same number of buses, which decreases the encoding cost. In addition, by following the physical power flow laws, the proposed scheme is hidden from alert attackers who can implement the state estimation-based bad data detection (BDD). Simulation results from the IEEE 69-bus distribution system demonstrate that the proposed scheme can mislead the attacker's state estimation on all the downstream bus-es from the encoded bus without arousing the attacker's suspicion. FDI attacks that are constructed based on the misled estimated state are very likely to trigger the defender's BDD alarm.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1776-1786"},"PeriodicalIF":6.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858607","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089989","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}

引用次数: 0