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最新刊期
卷 48 ， 期 2 ， 2024
- 摘要：With the increase of installed capacity and proportion of wind power, the problem of extremely slow electromagnetic transient simulation speed of large-scale wind farms is becoming more and more prominent. In view of the complexity of the existing modeling methods, the inability to reflect internal characteristics of the wind farm, and the lack of flexibility, this paper proposes an electromagnetic transient controlled source based decoupling acceleration model (CS-DAM) for the large-scale offshore wind farm. This method realizes the decoupling between the internal components of the wind turbine (WT) and the ports between different WTs by transmitting the voltage and current information between the ports through the controlled source, so that the high-order matrix in the system solution process is decomposed into multiple small matrices to achieve simulation acceleration. The effectiveness of the method is proved based on the node analysis method and Kirchhoff’s law. The proposed modeling method of CS-DAM, which can build a model by dragging existing modules in the simulation software, is simple. The CS-DAM can accurately simulate various transient and steady-state conditions of the wind farm, and the acceleration effect is obvious. Meanwhile, the proposed CS-DAM can complement the methods proposed in the existing literature and expand their flexibility. Finally, wind farm models with different numbers of WTs are built in PSCAD/EMTDC to verify the simulation accuracy and acceleration effect of the CS-DAM. The results show that the proposed CS-DAM can achieve acceleration effects of 1~2 orders of magnitude, and has higher simulation accuracy compared to the detailed model.关键词：offshore wind farm;wind turbine;electromagnetic transient simulation;controlled source based decoupling acceleration model;equivalent modeling3|1|0更新时间：2025-06-16
- 摘要：The medium-voltage DC (MVDC) collection and DC transmission systems of wind turbines based on distributed diode rectifiers do not require offshore booster stations and offshore converter stations, and have outstanding economic advantages for medium-to-long-distance and medium-scale offshore wind power. Aiming at its unique transmission current ripple problem, a multi-unit dynamic phase-shifting reference frame (DPSRF) is established and voltage vector control oriented to the d-axis of the DPSRF coordinate system is proposed to interleave the rectification current vectors and output current ripple of the distributed diode rectifiers. The staggered distribution of output current ripple effectively reduces DC transmission current and voltage ripple. Considering the influence of the dynamic phase shift angle in the ripple interleaving algorithm, a small-signal state-space model of the wind turbine grid-side converter is established, and the weak damping link of the system is identified based on the characteristic root analysis, and a stabilization control strategy is proposed. Taking advantage of the system’s potential to avoid DC circuit breakers, a fault location strategy based on the disturbance injection is formulated, and the relay protection logic and turbine operation sequence are used to realize fault localization and isolation of multiple fault locations in the DC internal network without a communication system. Finally, PSCAD simulation and RT-LAB-based hardware-in-the-loop experiments verify the effectiveness of the proposed control and protection strategy.关键词：offshore wind power;DC collection;DC transmission;control and protection4|2|0更新时间：2025-06-16
- 摘要：Due to the capacitive effect of power cables, the phenomenon of harmonic resonance amplification tends to occur in the offshore wind power collection system via power cables, which leads to decline in power quality. The distributed power flow controller (DPFC) is a device based on the voltage source converter, which can regulate power flow and control harmonics at the same time. In this paper, the frequency-domain correlation model of the offshore wind power system is constructed, and the reason for harmonic resonance amplification is analyzed based on this model. Then, the harmonic mitigation method of connecting the DPFC to the offshore wind power system is proposed, and the harmonic characteristics of the offshore wind power system with the DPFC are derived. Based on the these characteristics, a control strategy is designed, which reduces the harmonic voltage content of the grid-connected point by controlling the DPFC to track the harmonic compensation voltage that makes the harmonic voltage amplitude at the grid-connected point zero in real time. The simulation results show that the proposed harmonic mitigation method and control strategy of the offshore wind power system based on DPFC can effectively reduce the harmonic voltage at the grid-connected point and improve the power quality.关键词：offshore wind power;power quality;harmonic mitigation;distributed power flow controller (DPFC);variable incremental conductance incremental method4|0|0更新时间：2025-06-16
- 摘要：After a busbar fault in the low-frequency transmission system of offshore wind power takes place, the equivalent potential and impedance of the converter-type power source are no longer considered constant like traditional power grids due to the switching and adjustment process of control. The paper theoretically analyzes the adaptability of busbar current differential protection and clarifies the impact modes of fault control strategies on the sensitivity of differential protection. A busbar protection is proposed based on time-domain full component model identification, utilizing the different equivalent fault models corresponding to internal and external busbar faults. This protection principle reflects the changes in the topology of the protected components themselves, and theoretically has the advantage of not being affected by power source characteristics. It is also applicable to other converter-type power grids. At the same time, the proposed protection is implemented in the time domain without the problem of phasor extraction, and the operation speed is fast. Finally, a simulation model is built in PSCAD/EMTDC to verify the reliability and speed of the proposed busbar protection.关键词：offshore wind power;low-frequency transmission system;busbar protection;adaptability;model recognition;full component in time domain4|2|0更新时间：2025-06-16
Key Technologies for Offshore Wind Power System
- 摘要：The widespread of photovoltaic-battery storage systems (PBSSs) in the distribution networks provides considerable potential of flexible resources in power grid dispatch. To enhance the control fineness of the PBSS, the operation dynamic characteristics are analyzed and modeled while the dispatch model of PBSS considering electrochemical model is developed. With the expectation of preserving users’ privacy and utilizing distributed computational resources, the matrix form of the dispatch model is put forward and the distributed subproblems of each node for scheduling optimization of the distribution network are presented and solved by the distributed computing. The proposed method is validated in the case study of IEEE 33-bus system. The results show that the proposed method achieves superiority in terms of the feasibility of the dispatch plan, the operation efficiency of energy storage, and the suppression of aging关键词：photovoltaic-battery storage system;distribution network;electrochemical model;distributed optimization;dispatch;ancillary service4|1|0更新时间：2025-06-16
- 摘要：Frequent extreme natural disasters are highly likely to cause large-scale faults in the distribution network, and the distributed generator (DG) based load recovery is an important means to improve the resilience level of the distribution network. However, existing studies generally make independent decisions during the in- and post-disaster stages, while neglecting the continuity and coupling of the two decisions, and slowing down the recovery process. Therefore, this paper proposes a fast recovery method for the distribution network based on the in- and post-disaster two-stage coordinated decisions, which fully considers the interactions between the in- and post-disaster processes, and integrates the recovery measures including DG scheduling, network topology change, and maintenance personnel scheduling to guarantee the optimality of the consecutive decisions during the in- and post-disaster stages. Firstly, considering the demand relationship between post-disaster energy supply path and the in-disaster network topology, the topology adjustment model with DG as the core and the cellular load recovery model are established during the in-disaster stage to achieve the power supply for partial important loads. Secondly, considering the impact of the in-disaster decisions on the post-disaster recovery, a joint decision-making model for the fault maintenance personnel scheduling and fast load recovery is established during the post-disaster stage to achieve orderly recovery of all loads. Then, with the objective of minimizing the loss of load during the in- and post-disaster stages, the coordinated decision-making for the in- and post-disaster recovery is achieved. Finally, the validity of the proposed model is verified through an IEEE 123-bus distribution system.关键词：distributed generator;distribution network;resilience;in- and post-disaster coordination;maintenance personnel scheduling;energy supply path;load recovery7|3|0更新时间：2025-06-16
- 摘要：In the low-voltage distribution network, frequent extensions and modifications by users lead to the issues such as delayed information updates and missing data in the account, making it difficult to obtain the topology and line parameters under the current operating conditions. For low-voltage distribution networks that lack phase angle measurement information and include an indeterminate number of “hidden nodes” with zero injection power, this paper presents a method for joint identification of the network topology and line parameters utilizing data from smart meters. Based on the electrical and structural characteristics of radial low-voltage distribution network, a linear inverse power flow model in the form of power-to-voltage ratio is derived. The impedance distance matrix is obtained by linear regression solution, and then the topology and line parameters are jointly identified using an improved recursive grouping algorithm without threshold setting. Finally, the effectiveness of the proposed algorithm is verified by arithmetic simulation in the IEEE European low-voltage test feeder and an actual low-voltage distribution network in Nanjing, China.关键词：low-voltage distribution network;smart meter;power flow;topology identification;line parameter identification4|2|0更新时间：2025-06-16
- 摘要：The existing non-intrusive load decomposition algorithms often require a large number of electrical load data at equipment level to ensure the decomposition accuracy, but it is difficult to obtain these data due to the user's consideration of privacy and high installation cost. Therefore, a time-series generative adversarial network which can deeply explore the time-series characteristics of power load data and the correlation of electrical appliances is constructed. The dimensionality reduction network is used to reduce the dimensionality of the high-dimensional vector composed of the active power sequence of all electrical appliances to reduce the computational complexity, and the result is restored to the high-dimensional vector through the restoration network. Based on the non-intrusive decomposition method of electrical appliance operation status and deep learning, the load decomposition regression model of complex-state electrical appliances is built by using the convolutional neural network-bidirectional gated recurrent unit, and the load identification and classification model of simple-state electrical appliances is constructed by using the deep neural network. The effectiveness of the proposed method is verified by comparing other data generation methods and the load decomposition results obtained by changing the proportion of the generated data in typical public datasets.关键词：non-intrusive load decomposition;generative adversarial network;dimensionality reduction network;convolutional neural network-bidirectional gated recurrent unit;deep neural network4|1|0更新时间：2025-06-16
- 摘要：The integration of renewable energy increases the likelihood of cascading failures, posing challenges in identifying critical lines during fault propagation. In light of this, a cascading failure simulation model that incorporates the fault voltage ride-through characteristics of wind turbines and line reliability is built. An indicator evaluation set of line comprehensive risk is also introduced, which encompasses line load loss severity and non-uniformity, and structural vulnerability perspectives. The security risk index and the uneven risk index are defined based on the state-failure-network,the degree of line load loss severity and non-uniformity. Based on the electrical betweenness, a fragile structure index accounting for distributed renewable energy access is proposed. Meanwhile, to measure the overall impact of line disconnection, a fuzzy entropy weight method is employed to define the comprehensive risk index, which considers the network structure and state transition characteristics of the power grid. Numerical examples involving the IEEE 39-bus and IEEE 118-bus systems validate the effectiveness of the proposed method in identifying critical lines. Additionally, mitigation measures for critical lines can significantly reduce the risk of blackouts.关键词：cascading failure;renewable energy;wind turbine;fault voltage ride-through;electric betweenness;fuzzy entropy weight method4|0|0更新时间：2025-06-16
- 摘要：Virtual synchronous generator (VSG) technology can effectively improve the voltage support ability of the power grid. However, it also introduces complex low-frequency oscillation (LFO) problems. At present, most of the LFO studies on traditional VSG ignore the DC-side and generator-side dynamics, which makes it difficult to accurately characterize the LFO characteristics of virtual synchronous direct-driven wind turbine generators. To deal with the above problems, a unified damping torque model considering both the generator-side dynamics and the DC voltage dynamics is established. By using the damping torque method, it is revealed that the negative damping torque produced by the rotor dynamics on the generator side is the main reason of the LFO for wind turbines. Then, the influence law of each link on the LFO characteristics of the wind turbine is analyzed. Furthermore, a damping compensation control is proposed to reduce the negative damping effect of the machine-side dynamics and effectively improve the stability of wind turbine generator grid-connected system under machine-side coupling. Finally, the applicability of the proposed control in multi-computer systems is briefly analyzed, and the cases studies based on the MATLAB/Simulink simulation are conducted to verify the accuracy of the theoretical analysis and the effectiveness of the proposed control.关键词：low-frequency oscillation;virtual synchronous generator;direct-driven wind turbine generator;damping torque method;stability4|0|0更新时间：2025-06-16
Basic Research
- 摘要：Load identification technology can quickly identify the types of electrical appliances, and plays an important role in household energy management, hazardous warning, response potential assessment and other aspects. Aiming at the problem that the existing load identification methods focus on the long-term or short-term single-scale load features, resulting in insufficient feature representation capabilities, and thus limiting model identification accuracy and generalization performance, a load identification and its interpretable interactive enhancement method based on multi-scale feature fusion is proposed. Firstly, short-term features of high-frequency scale and long-term features of medium- and low-frequency scales are extracted from the load sampling data, and a deep feature extraction network with a double-tower structure is constructed to efficiently mine deep features of each scale by using different branches of the network. Secondly, a feature fusion network combining self-attention and cross-attention is designed to fuse long-term and short-term features, improving the feature utilization of the model. Then, a training method of metric learning is used to shorten the feature distance of the same type of samples and improve the efficiency and effect of feature fusion. Finally, the interpretable analysis method based on gradient is used to quantify the importance of features, and realize the adaptive feature enhancement and model optimization combined with expert interaction. The experimental results show that the recognition accuracy and generalization ability of the proposed model are superior to those of existing models, and the interpretable analysis verifies that its effectiveness comes from the full use of multi-scale features.关键词：load identification;multi-scale feature;feature fusion;metric learning;interpretable analysis4|2|0更新时间：2025-06-16
- 摘要：In the background of new power systems, fast and effective detection of false data injection attack (FDIA) is crucial for the safe operation of power grids. However, the existing deep learning methods do not fully explore the spatiotemporal feature information in measurement data of power grids, which affects the detection performance of models. Meanwhile, the “black box” attribute of deep neural networks reduces the interpretability of the detection model, leading to the lack of credibility in detection results. To solve the above problems, an interpretable FDIA detection method is proposed based on multi-head graph attention network and time convolution network (MGAT-TCN) model. First, considering the spatial correlation between power grid topology connection and measurement data, a spatial topology aware attention mechanism is introduced to establish the multi-head graph attention network (MGAT) to extract spatial features of measurement data. Next, the time convolution network (TCN) is used to extract the temporal features of the measurement data in parallel. Finally, the proposed MGAT-TCN model is simulated and validated on the IEEE 14-bus system and IEEE 39-bus system. The results indicate that the proposed model has higher detection accuracy and efficiency compared to the existing detection models, and the visualization of attention weights through topological heat maps can achieve interpretability of the model in spatial dimensions.关键词：power grid;false data injection attack;graph attention;time convolution;Attention mechanism;interpretability4|0|0更新时间：2025-06-16
- 摘要：The interaction between the long transmission cable (LTC) and the grid-connected inverter can easily cause the risk of harmonic instability of the system. Ignoring the frequency-dependent characteristics of the line may lead to stability misjudgment. In order to evaluate the stability of the grid-connected inverter system, the distribution parameter characteristics and frequency-dependent characteristics of LTCs are taken into account in this paper. Firstly, the equivalence of the AC system is carried out based on the vector fitting method, and the high-frequency state-space model of the grid-connected inverter system in the dq coordinate system is established with consideration of the inner and outer loop control, phase-locked loop and control delay. Secondly, the key influencing links leading to the harmonic instability are identified by using the participation factor analysis method. Meanwhile, the influences of the frequency-dependent characteristics of LTCs, delay time, controller parameters, cable length, and power grid impedance on the system harmonic stability are analyzed by using the root locus method. Thirdly, a method for improving the system stability is proposed based on the parametric sensitivity analysis and the matrix similarity transformation, and the harmonic stability of the improved system is analyzed. Finally, the verification is carried out on the RT-LAB based hardware-in-loop experimental platform, and the experimental results verify the correctness of theoretical analysis.关键词：grid-connected inverter system;long transmission cable;harmonic instability;state-space model;root locus;sensitivity analysis4|0|0更新时间：2025-06-16
- 摘要：With the increasing application of grid-forming (GFM) converters in the microgrid, the effects of GFM converters on the transient stability of the microgrid have received extensive attentions. Different from the single-machine infinite bus system, the frequency and power angle of the islanded system with parallel GFM converters are coupled with each other, and the transient response characteristics are more complex. In order to accurately analyze the transient response of the islanded system with parallel GFM converters, this paper establishes a three-order transient synchronization model of frequency and power angle difference of two GFM converters based on the power angle coupling equation of motion, and analyzes the characteristics of the influence of the power output difference and droop coefficients of two GFM converters on the transient stability. In order to reveal the coupling mechanism of power output and droop coefficient on transient stability, the equivalent synchronous power of parallel GFM converters is analyzed. An adaptive droop coefficient optimization strategy is also proposed based on the power output of GFM converters, which can adaptively increase the equivalent synchronous power of the parallel system and thus improve the transient stability of the system. Finally, the real-time simulation is used to verify the correctness of the three-order transient model and the effectiveness of the proposed control strategy.关键词：grid-forming converter;islanded microgrid;transient stability;phase-plane analysis;equivalent synchronous power;adaptive droop coefficient5|1|0更新时间：2025-06-16
- 摘要：To solve the problem that the effectiveness and adaptability of heuristic algorithms in distribution network fault recovery decision become poor when the topology of distribution network changes, a fault recovery decision method based on graph reinforcement learning is proposed. First, the graph data is used to characterize the decision information in fault recovery, including distribution network topology and electrical characteristics. Then, the pre-graph neural network is set up in the graph reinforcement learning model to receive the graph data input and cope with the topological changes of the distribution network in the process of fault recovery. Finally, the reinforcement learning agent of the embedded graph neural network outputs the final fault recovery strategy to improve the decision speed. A modified PG&E 69-bus distribution network case is used for validation. The results show that the proposed algorithm can reach millisecond level in solving speed, and improve the solving efficiency by 6%~7% compared with heuristic and genetic algorithms, Also, the load recovery rate of the fault recovery strategy is higher.关键词：graph reinforcement leaning;graph neural network;reinforcement learning;distribution network;fault recovery4|2|0更新时间：2025-06-16
Application Research
- 摘要：Battery energy storage system (BESS) has become a key component of the power grid due to its advantages of improving the accommodation capacity of renewable energy. However, the inconsistency of batteries caused by production and usage processes is a critical factor affecting the capacity and lifespan of energy storage systems. Based on the topology of high-voltage DC cascaded H-bridge converter-battery energy storage system (CHBC-BESS), a hierarchical control strategy is adopted. Based on the first-level control for a voltage mode and a power mode, a state of charge (SOC) self-equalizing control strategy with adaptive control parameters is proposed to solve the problem of battery SOC unequalizing. The strategy considers the battery SOC deviation, the voltage levels of each module capacitor, the margin in DC system voltage control, and the upper and lower limits of the output modulation ratio. The equalizing coefficient is calculated in real time. Experimental results verify that the proposed strategy can achieve fast self-equalizing and high equalizing efficiency under the working conditions of large SOC deviation and the extreme working conditions of full-power charge-discharge switching.关键词：cascaded H-bridge converter;converter;battery energy storage system;state of charge;equalizing4|4|0更新时间：2025-06-16
- 摘要：The emergency control mode of “online calculation and real-time matching” is an effective way and a technological development trend to reduce the risk of control strategy mismatching. To further improve the rapidity of online emergency control strategy generation, a rapid generation method of transient stability emergency control strategy based on feature matching is proposed. With the help of the quantitative analysis ability of the extended equal-area criterion for transient stability and the time-varying degree of the locus under the power grid fault, the matching indexes of the characteristic quantities of the operation mode are established by comprehensively considering the transient stability locus feature of the power grid and key characteristic quantities of the steady-state power flow. Then, the most similar mode can be matched in the historical modes to realize the rapid generation of the emergency control strategy, and the strategy is then distributed to the devices for execution after verification. Finally, the effectiveness of the proposed method is verified based on the actual power grid.关键词：transient stability;uncertainty;feature matching;extended equal-area criterion (EEAC);time-varying degree;emergency control4|2|0更新时间：2025-06-16
Engineering Application
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