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DSO-prosumers cooperative scheduling approach considering multi-timescale peer-to-peer transactions of electricity and flexibility resources

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2025年 42卷

作者： Wang, Kang Wang, Chengfu Dai, Jianwei Dong, Shuang Cui, Yongling Wang, Guoying Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Shandong Elect Power Engn Consulting Inst Corp Ltd Jinan 250061 Shandong Peoples R China

The rapid evolution of peer-to-peer (P2P) transaction mechanisms has facilitated end-use prosumers in energy sharing to enhance energy utilization and address uncertainties in renewable energy sources (RES). However, the lack of coordination across different timescales and heterogeneous distributed resources results in potential economic losses. To this end, a cooperative scheduling approach considering multi-timescale P2P transactions is proposed. Firstly, multi-timescale P2P transactions mechanism is proposed to coordinate the heterogeneous resources between prosumers. In day-ahead stage, prosumers engage in electricity transactions using expected output of RES. In intraday stage, flexible resources are traded among prosumers to mitigate prediction deviation of RES. Meanwhile, the Nash bargaining theory is introduced to allocate the interests. Then, to determine reasonable flexibility requirement in intraday stage, a two-side chance constrained economic dispatch (TS-CCED) model is proposed, in which DSO can set the reference requirement interval at given confidence level to balance the economy and safety of system operation. Finally, to reduce the computational complexity, the Gaussian mixture model is applied to convert the TS-CCED model into a convex optimization problem with guaranteed accuracy. Case study based on the IEEE 33-bus system and IEEE-123 bus system verifies the effectiveness of the proposed method.

关键词： Peer-to-peer transaction Two-side chance constrained economic dispatch Gaussian mixture model Multi-timescale Nash bargaining theory

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Analytical monodromy matrix method for small-signal stability analysis of grid-connected modular multilevel converter systems

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 164卷

作者： Jia, Xiaofan Ye, Hua Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Shandong Res Inst Ind Technol Jinan 250101 Peoples R China

The modular multilevel converter (MMC) has been widely used in high-voltage/high-power applications, e.g., high-voltage direct current transmission. However, its nonlinear time-periodic nature leads to complex harmonic interactions and then complicates the small-signal stability modeling and analysis of grid-connected MMC systems. To address this, the linear time-periodic (LTP) theory and the Floquet theory-based monodromy matrix method are applied in this paper. First, an analytical expression of the monodromy matrix (i.e., the state transition matrix over a period) for the LTP model of grid-connected MMC systems is constructed by applying the Chebyshev collocation method. In addition to avoiding time-consuming numerical integration, the analytical matrix facilitates to perform the derivative-based eigenvalue sensitivity analysis. Then, the system free-response solution is efficiently computed by means of a set of analytical state transition matrices. The effective oscillation components in critical LTP modes and relative contributions thus can be identified. On this basis, the participation factor analysis and damping ratio analysis can be performed to gain insightful characterization of system dynamics. The correctness and effectiveness of the proposed method are verified on an exemplary grid-connected MMC system by both numerical and experimental results.

关键词： Floquet characteristic multiplier (FCM) Linear time-periodic (LTP) system Modular multilevel converter (MMC) Monodromy matrix method Small-signal stability

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Coordinated Distributionally Robust Optimal Allocation of Energy Storage system for HV-MV Distribution Network Resilience Enhancement

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2025年第2期61卷 2011-2024页

作者： Cao, Kuan Liu, Yutian Wang, Chunyi Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China State Grid Shandong Elect Power Co Dev Planning Dept Jinan 250001 Peoples R China

To solve the problem of power imbalance under extreme and normal scenarios in high voltage (HV) and middle voltage (MV) distribution networks with high penetrations of photovoltaic (PV), the paper proposes a distributionally robust optimal allocation method of energy storage system (ESS) for equilibrating resilience and economy. Firstly, due to the strong relation between resilience enhancement and ESS location, the siting-sizing sequential updating method is adopted to site ESS based on the planning resilience indexes. Secondly, to generate normal and extreme PV-load scenarios with continuous labels, an adversarial autoencoder (AAE) combined with transfer learning is improved by introducing the conditional neural network. Based on the improved AAE and clustering techniques, a Kullback-Leibler divergence-based ambiguity set is constructed to characterize the joint probability distribution of PV and load. Thirdly, considering the boundary information interaction of HV-MV distribution networks, a two-stage coordinated distributionally robust optimization model is established to size ESS. In the model, centralized ESS in HV distribution network participates in frequency regulation and peak shaving while distributed ESS in MV distribution network regulates voltage profiles in the four-quadrant mode. For further improving resilience, an operational resilience index as a chance constraint considering extreme scenarios is embedded into the model. Fourthly, the C&CG algorithm is nested into the analytical target cascading method to handle the model. Finally, case studies show that the proposed method can effectively balance resilience enhancement and economic operation.

关键词： Adversarial autoencoder distributionally robust optimization ESS allocation ESS allocation HV-MV distribution network HV-MV distribution network resilience resilience resilience

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Distributed Chance-Constrained Optimal dispatch for Integrated Energy system With Electro-Thermal Couple and Wind-Storage Coordination

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2025年第1期61卷 833-846页

作者： Zhang, Zhenwei Wang, Yan Wang, Chengfu Su, Ya Wang, Yong Dai, Yong Cui, Can Zhang, Wei Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Taian Power Supply Co State Grid Shandong Elect Power Co Tai An 271000 Peoples R China

Cross-regional long-distance transmission is a promising way for utilizing renewable energy sources (RESs) with geographically imbalanced distribution. However, the stochastic fluctuations of RESs will be transferred to the receiving energy networks, and the complex operating conditions of cross-regional transmission lines further affect energy delivery. In this paper, we propose a coordinated optimization model for an integrated energy system (IES) that considers the uncertain injection from long-distance wind farms. First, a dynamic capacity calculation model of overhead transmission lines (OTLs) is established, taking into account the electro-thermal couple characteristics and real-time ambient conditions. Second, an IES model integrating electricity and natural gas distribution networks is built and converted into second-order conic programming using the McCormick approach. Third, a distributed chance-constrained optimization framework is proposed to coordinate the wind-storage system and IES. The probabilistic constraints are converted into certain constraints based on stochastic scenario sampling. Besides, to maintain the variable consistency of the connection lines between cross-regional systems, we employ the virtual node approach to achieve a fast-distributed iterative solution. Finally, simulation results on a modified IEEE33-Belgium20 test system demonstrate the superiority of the proposed method in operational economy and RESs utilization.

关键词： Wind power generation Stochastic processes power transmission lines Optimization Resistance Reactive power Load flow Fluctuations Electricity Convex functions Integrated energy system wind-storage system cross-regional coordination electro-thermal couple

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Synchronization Stability of Multiple VSGs Embedded power system With controller Limits

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IEEE TRANSACTIONS ON power systemS 2025年第1期40卷 834-849页

作者： Li, Yujun Lu, Yiyuan Yang, Jialun Liu, Jingrui Mu, Tongpeng Ye, Hua Du, Zhengchun Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China

This article investigates the synchronization stability of one multiple virtual synchronous generators (VSGs) embedded power system with the current saturation and limits of frequency. The dynamic model of the multiple VSGs integrated system with controller limits is built. Accordingly, the transient energy function (TEF) for the autonomous system without touching controller limits is established, and the stability region is determined via the method of the closet unstable equilibrium point (UEP). Further, it is found that the system leaves away from the bounds of frequency at several leaving bound points. Among these, there exists two special ones with the minimal transient energy, and they are fixed irrespective of the switching times. Finally, one stabilizing condition is proposed that only if the energy of two special leaving bound points is less than the system critical energy, the global stability is ensured. The system critical energy is determined by the minimum of two values, namely, the method by closet UEP, and the maximum potential energy to ensure the system does not enter the mode of current limiting control (CLC). The numerical simulations of 9-buses and 39-buses power systems have verified the correctness of the proposed analysis.

关键词： power system stability Transient analysis Stability criteria Synchronization Frequency control power system dynamics Frequency conversion controller limits leaving bound points synchronization stability transient energy function virtual synchronous generator

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An efficient approach for diagnosing faults in photovoltaic array using 1D-CNN and feature selection Techniques

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 166卷

作者： Ali, Yousif Mahmoud Ding, Lei Qin, Shiyao Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China China Elect Power Res Inst 15 Xiaoying East Rd Beijing 100192 Peoples R China

Diagnosing faults in Photovoltaic (PV) systems is essential for operation and maintenance. Selecting relevant features is necessary for successful fault diagnosis because redundant and irrelevant features reduce fault diagnosing accuracy. This paper proposes a novel and efficient approach to diagnosing faults in PV systems. The Feature Selection and Fault Diagnosis (FSFD) method is executed for diagnosing five types of faults in PV array (PVA): partial shading condition, line-line fault, arc fault, open-circuit fault, and degradation fault. Firstly, a PVA modeling method using MATlab/Simulink is employed to simulate I-V curves and extract their features. Next, a feature permutation technique-based method is proposed for selecting the most relevant features. A simple and accurate one-dimensional convolutional neural network (1D-CNN) model is developed to classify the faults based on the selected features. Finally, a confusion matrix is utilized to evaluate the performance of the trained model. Three datasets of PVAs have been utilized to evaluate the effectiveness of the proposed FSFD method. The results indicate that the FSFD method has effectively identified the best five features out of eight for training the 1DCNN model. The trained model has achieved diagnosing accuracy rates of 99.85%, 99.73%, and 99.97% in series-parallel PVA, total cross-tied PVA, and series PVA datasets, respectively. The proposed method accurately diagnoses single faults in three PVA configurations. Therefore, we recommend conducting additional studies to improve the proposed method for diagnosing hybrid faults.

关键词： Photovoltaic array Current-voltage curve Fault diagnosis Convolutional Neural Network Feature selection

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Microgrid energy management strategy considering source-load forecast error

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 164卷

作者： Zhang, Kaikai Zou, Guibin Zhang, Jinliang Li, Houlei Sun, Yazhong Li, Guoliang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Shandong Peoples R China State Grid Jinan Elect Power Co Jinan Shandong Peoples R China State Grid Shandong Zaozhuang Elect Power Co Zaozhuang Peoples R China

Hybrid energy storage system (HESS) can stabilize renewable energy power generation, but unreasonable energy storage power distribution and photovoltaic-load forecast errors will affect the economic benefits of the whole system. Aiming at the microgrid (MG) composed of photovoltaic (PV) and HESS, an energy management strategy (EMS) of MG considering forecast errors is proposed. Firstly, an optimization model considering the depreciation cost of battery is established. Secondly, day-ahead EMS is implemented under multiple operating modes considering minimum fluctuation and optimal economy. Then, according to the real-time forecast results and the feedback of system operation status, the intraday rolling energy management strategy (REMS) is developed to alleviate the impact of forecast errors. Finally, the real-time state of charge (SOC) of the supercapacitor (SC) is introduced to adjust the filter coefficient, which avoids the SC working in the charge/discharge restricted area for a long time and improves the adjustment effect. The results of the case analysis show that the proposed intraday REMS can effectively reduce the influence of forecast errors on energy management.

关键词： Energy management strategy Forecast error Photovoltaic-microgrid Hybrid energy storage system power distribution

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Ultra-short-term wind farm cluster interval power prediction based on cluster division and MQ-WaveNet-MSA

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ELECTRIC power systemS RESEARCH 2025年 244卷

作者： Wang, Chao Lin, Hong Yang, Ming Chen, Li Xinjiang Univ Sch Elect Engn Urumqi 830047 Peoples R China Changji Univ Sch Energy & Control Engn Changji 831100 Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

The grid integration of large-scale wind farms has posed challenges to the safety and stability of power systems. To address these challenges, this study proposes a clustering-based direct multi-step interval prediction method for wind farm clusters to quantify the uncertainty in regional wind power generation. In the proposed method, the empirical orthogonal function is combined with the K-means algorithm to divide a wind farm cluster. In addition, the training, validation, and test sets are constructed for each sub-cluster based on the division results. Further, by combining the long-term perception advantages of the multi-horizon quantile-WaveNet (MQWaveNet) model and the global information enhancement capability of the multi-head self-attention (MSA) mechanism, the MQ-WaveNet-MSA model is developed to predict an ultra-short-term interval of a wind farm cluster to realize the direct multi-step prediction of multiple quantiles. Finally, twelve wind farms in the Xinjiang area are selected for a case study. The results show that the proposed model has higher interval prediction accuracy than the existing prediction models, which verifies its effectiveness.

关键词： Cluster division Interval power prediction Multi-headed self-attention WaveNet model

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Open-source short-circuit current solver for power systems with renewable energy sources and HVDC links

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 167卷

作者： Wang, Jian Li, Changgang Yang, Junjun Qi, Hang Hua, Wen Dong, Wei Ye, Lin Terzija, Vladimir Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China State Grid Zhejiang Elect Power Co Ltd Res Inst Hangzhou 310014 Peoples R China State Grid Zhejiang Elect Power Co Ltd Dispatch & Control Ctr Hangzhou 310014 Peoples R China Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU England

Large-scale integration of renewable energy sources (RES) and high voltage direct current (HVDC) links have changed the power system short-circuit current (SCC) level significantly. Traditional SCC solvers for systems dominated by synchronous generators are no longer applicable. This paper provides an open-source SCC solver based on Simulation Toolkit for Electrical power systems (STEPS). It supports SCC analysis for power systems with RES and HVDC and allows customized extensions for emerging RES and HVDC control models. In the solver, the sequence models are created for RES and HVDC to support the research on changes in SCC characteristics. To speed up the calculation of equivalent impedance for different fault locations, a new method without adding new bus at the fault location is proposed. The solver provides iterative SCC calculation and direct solving functionality with a range of additional features. Flexible options are provided and configurable to cope with different calculation scenarios. The accuracy of the SCC solver is compared with PSS/E. Meanwhile, numerical examples considering RES and HVDC links are provided to demonstrate the practicality of the solver.

关键词： Short-circuit analysis Open-source Renewable energy source HVDC STEPS

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Mechanism and Methods for Fault Recovery of Grid-Forming Inverter by Graphical Illustration

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IEEE Transactions on power systems 2025年第2期40卷 1973-1976页

作者： Yang, Jialun Ye, Hua Wang, Yantuan Liu, Yutian Li, Yujun Du, Zhengchun Shandong Research Institute of Industrial Technology Jinan250061 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China Xi'an Jiaotong University Department of Electrical Engineering Xi'an710049 China

The existing priority-based current limiting control (CLC) for grid-forming (GFM) inverters may lead to failures in fault recovery, including being locked in CLC and mode oscillation between CLC and constant voltage control (CVC). To resolve these problems, this letter first reveals the fault recovery mechanism of droop controlled GFM inverters by illustrating the conditions of three fault recovery states in the phasor diagram. Then, two methods including determination of the optimal range of current angle and upper limit of saturation block are presented to guarantee successful fault recovery of GFM inverters. The correctness of theoretical analyses is verified and validated by multiple experimental tests. © 1969-2012 IEEE.

关键词： Fault current limiters

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