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MA Peng, QI Jun, XIONG Yi, HU Kaijun, HAN Yongming, ZHAO Xuan
Available online:February 05, 2025 DOI: 10.7500/AEPS20231219004
Abstract:The peak shaving resource at demand side is an important component of peak shaving resources in new power system. However, due to the internal and external factors such as the uncertainty in user behavior and abnormal equipment status, some loads often fail to respond reliably. Aiming at the low response reliability of demand-side resources in industrial parks during the actual peak shaving, a precision peak shaving strategy at demand side is proposed considering load response reliability and aggregator scheduling economy. Firstly, a regulation model is established for the direct control of central air conditioning load and industrial load, and the relevant factors that affect its response reliability are analyzed by combining diversified characteristic loads. Secondly, the load response reliability index is defined to quantitatively characterize the influence degree of internal and external factors on load response reliability. Together with load regulation cost, it is used as a decision variable for load aggregation, and the peak shaving response optimization scheme at demand side is solved through iterative algorithms. Finally, based on the central air conditioning load data from the OEDI dataset of USA and the load data from an industrial park in Hubei Province, China, the proposed precision peak shaving strategy is compared and simulated with the economic-only peak shaving strategy by using economic incentives as the only means, and the total scheduling cost and actual response rate of load aggregators are analyzed as evaluation indicators to verify the effectiveness of the proposed strategy.
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XU Ruidong, CHANG Zhongxue, YANG Jiayi, WANG Chenqing, YUAN Yubo, SONG Guobing
Available online:January 24, 2025 DOI: 10.7500/AEPS20240327005
Abstract:In the flexible interconnected distribution network based on soft open point (SOP), the sensitivity and reliability of current protection cannot meet the requirements due to the weak feed and nonlinear regulation characteristics of power electronic equipment. Therefore, based on the idea of detection protection, a single power system excited by the dual-frequency detection signals injected by SOP is established, and the fault distance solution equation including fault distance, transition resistance and parameters of the opposite end system is proposed. A detective phase-to-phase distance protection for flexible interconnected distribution network is designed by setting the action delay based on the fault distance and implementing coordination with the inverse time action strategy. Simulation verification is carried out based on PSCAD, and the protection device prototype is developed. The simulation and hardware-in-the-loop test results prove the effectiveness of the proposed scheme. Compared with the traditional protection principle, the proposed protection scheme is not affected by the weak feed characteristics and overcomes the effects of infeed and out flowing current caused by the opposite end system and branch lines during the fault through the transition resistance.
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GUO Kuixing, LI Yaowang, HE Xiaoyi, LIU Heng, LI Xuecheng, ZHANG Ning
Available online:January 24, 2025 DOI: 10.7500/AEPS20240613008
Abstract:The electric carbon meter system is an important carrier for realizing real-time and accurate electric carbon measurement. With the advancement of the goal of carbon emission peak and carbon neutrality, the requirements for the accuracy and continuity of measurement by electric carbon meter become increasingly stringent. It will be difficult to cope with the increasing requirements relying on an independent carbon meter system, and it is urgent to explore the optimal configuration method for the backup carbon meter system. Considering the characteristics of “one hair affecting the whole body” of the electric carbon measurement and the strong coupling relationship between the electric carbon measurement and the power flow, this paper proposes an optimal configuration method of the backup carbon meter system. The method is conducted in a stepwise optimization manner. Firstly, to ensure that the carbon meter system can measure the full carbon information of the power system, this paper proposes an optimization method to determine the number of spare carbon meter devices with the lowest configuration cost. Then, with the aim of minimizing the measurement error of the backup carbon meter system, this paper proposes a method of optimizing the distribution of the backup carbon meter device. Finally, the simulation test is carried out based on the PJM 5-bus system and the actual power system data of a certain city in China. The results show that the proposed method can achieve a carbon emission measurement error of less than 0.2% with the minimum configuration cost of the backup carbon meter system, with the premise of ensuring the complete carbon emission information measurement of the power system.
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CHEN Zeyu, CHEN Yanbo, ZHANG Zhi, HUANG Wei
Available online:January 22, 2025 DOI: 10.7500/AEPS20240611007
Abstract:Dynamic line rating (DLR), as an effective technique to alleviate the intermittent network congestion, can significantly increase the operation benefits of modern power systems. However, since congestion management is inherently embedded within the solution process of security-constrained economic dispatch (SCED), the intricate details of this process are not easy to obtain. Consequently, market operators are often difficult to accurately analyze the economic benefits of DLR and formulate DLR plans combining economic efficiency with safety. To address this challenge, this paper proposes a traceback method for congestion management process with quantitative analysis of contributing factors for the single-branch congestion scenarios. By comprehensively dissecting and analyzing the congestion management process within the framework of SCED, a linkage relationship among DLR plans, congestion management, and locational marginal price is established. On this basis, a benefits calculation method of DLR that incorporates the traceback of congestion management process is further introduced. Finally, through case analysis, the effectiveness of the proposed traceback method and the feasibility of the benefits calculation method of DLR are validated.
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WANG Yingjie, LIU Han, ZHANG Xiao, ZHANG Shunchao
Available online:January 22, 2025 DOI: 10.7500/AEPS20240607002
Abstract:In a system with multiple inverters connected to the power grid, the harmonic interaction among inverters and the harmonic interaction between the inverters and the power grid can significantly impact both the inverters and the overall operation of the power grid. Aiming at the difficulty in identifying and evaluating the effects of interactions in multi-machine systems, this paper first establishes a current small-signal model for a single inverter considering specified current disturbances. The model is extended to the multi-inverter parallel system. Meanwhile, the concepts of the independent-interaction factor and the self-interaction factor of harmonic admittance are proposed to categorize the system disturbances into independent disturbances and self-disturbances. On this basis, the peak of the interaction factor is analyzed. Using the derived peak criterion, the quantization conditions for harmonic amplification resulting from the system harmonic interactions are obtained, and an exclusion zone to mitigate harmonic interaction amplification is proposed. Finally, this paper discusses the harmonic interaction rules of the multi-inverter parallel system in the influences of current control parameters, phase-locked loop parameters, inverter damping strategies, power grid impedance parameters, and the number of parallel inverters through case analysis. The correctness and effectiveness of the proposed analytical approach are validated.
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SONG Zhen, LI Yong, WANG Hongtao, WANG Haobo, LI Shaoyan, LIU Yutian
Available online:January 22, 2025 DOI: 10.7500/AEPS20240429014
Abstract:Permanent magnet synchronous wind turbines can be modified to serve as black-start power sources, enhancing grid recovery capabilities in extreme outage scenarios. To address the problem of insufficient grid-forming support capacity of wind turbines under fluctuating wind conditions during black-start load impacts, this paper proposes a permanent magnet synchronous wind turbine-energy storage combined power source, along with a coordinated control method. First, on the electromechanical transient time scale, the method improves the ability of wind turbines to track load power changes by capturing wind power based on the black-start load power prediction. Then, on the electromagnetic transient time scale, a coordinated control method for the inverter combining wind turbine with energy storage is proposed to enhance the response capability of the wind turbine-energy storage combined power source. Finally, a black-start and load connection method based on the inertia and kinetic energy of the wind turbine is presented. This involves connecting to the grid and load at high rotational speeds of the wind turbine, utilizing the released kinetic energy to complete the black-start. Simulation results show that compared with the conventional black-start method for wind power, the proposed method can significantly improve the stability of wind power systems against load shock under wind speed fluctuations, while reducing the power and capacity requirements for energy storage.
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YU Zhipeng, LIN Jin, LEI Jinyong, WANG Yang, SONG Yonghua, JIANG Lilong, PAN Jun, ZHANG Hang
Available online:January 22, 2025 DOI: 10.7500/AEPS20240910004
Abstract:Utilizing renewable energy sources such as wind and photovoltaic to identify cost-effective decarbonization pathways for coastal receiving-end power systems in China is one of the core challenges in achieving the goals of “carbon emission peak and carbon neutrality” of China. By analyzing the techno-economic differences between hydrogen-ammonia storage and existing energy storage technologies (such as electrochemical and compressed air storage), a multi-year expansion planning model for power systems incorporating coupled co-firing hydrogen-ammonia storage under temporal decarbonization constraints is established, and the techno-economic feasibility of achieving low-cost decarbonization within the power system is explored. The case selects actual data from Guangdong power grid for research. The results demonstrate that under increasingly stringent carbon reduction constraints, it is necessary to progressively achieve decarbonization targets through technical pathways, such as the newly added wind and photovoltaic storage, the transition from coal to gas in thermal power planning modes, and the newly added hydrogen-ammonia storage (including hydrogen co-firing in gas turbines, ammonia co-firing in coal-fired plants, and ammonia decomposition). Compared to a decarbonization mode relying solely on lithium-ion battery peak shaving, the introduction of coupled co-firing hydrogen-ammonia storage technology can avoid overloading excessive wind and photovoltaic storage capacity, thus significantly reducing the wind and photovoltaic curtailment rates. This approach not only achieves intensive resource utilization but also further reduces the decarbonization cost of hydrogen-ammonia storage through the reuse of existing thermal power infrastructure. Therefore, the use of hydrogen-ammonia storage technology for power system decarbonization presents a scalable and economically feasible decarbonization pathway.
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ZHENG Xin, QI Lei, SUN Xiaofeng, JIANG Haoyu, ZHAO Wei
Available online:January 21, 2025 DOI: 10.7500/AEPS20240514003
Abstract:The integration of a large number of distributed power generation units leads to a weakening of the power grid strength, which in turn causes harmonic resonance of the output current of the photovoltaic cluster, threatening the safe and stable operation of the system. Therefore, considering the constraint of harmonic resonance, based on the source and grid impedance aggregation model and stability index of the system, the objective function of the optimal stability margin for the system under a certain grid-connected power of renewable energy is constructed, Newton numerical iteration is integrated into the Lagrange condition extremum solution process to achieve rapid adjustment of impedance sensitivity towards consistency. Aiming at the application scenarios of constant power and the allocation of maximum grid-connected power, an optimal allocation method of grid-connected power based on Newton iterative sensitivity collaboration is proposed. Compared with conventional cluster power allocation methods and similar optimal allocation methods, the proposed optimal power allocation method has high solving efficiency and low computing power requirements. Finally, an IEEE 33-bus case is built on the real-time digital simulation system hardware in the loop simulation platform to validate the above researches.
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CAI Yunfan, XU Xiandong, YU Xiaodan, JIA Hongjie, HU Xiao
2025,49(3):1-12, DOI: 10.7500/AEPS20231218012
Abstract:As a typical interruptible load in steel plants, the hot rolling load has great potential in participating in the demands of power grid dispatching and control such as peak regulation. In recent years, with the successive introduction of demand-side electricity market policies, it is urgent to evaluate the regulation capacity of hot rolling loads while fully considering production characteristics and peak regulation service requirements. First, according to the production characteristics of multi-line, multi-product and continuous production of hot rolling loads, a multi-line model of hot rolling loads is established considering the demands of power grid dispatching and control. Then, on this basis, the correlation demand between the electricity peak regulation market and the production energy optimization in the hot rolling process is analyzed, and a comprehensive evaluation method for the adjustable power capacity is proposed, which takes into account both the peak regulation and cost constraints of multi-line hot rolling loads. Finally, the effectiveness of the proposed method is verified through the simulation case analysis, and the capacity, cost and key influencing factors of hot rolling loads participating in intra-day and day-ahead peak-regulation markets are analyzed.
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JIANG Tingyu, TAO Jinyu, WANG Ke, JU Ping, HUANG Qifeng, DUAN Meimei
2025,49(3):13-21, DOI: 10.7500/AEPS20230806003
Abstract:Energy-intensive industrial loads have high power consumption, high automation levels, and strong controllability, which show great demand response (DR) potentials and can be regarded as an important means to deal with the continuous expansion of the peak-valley difference in the new power system. Therefore, the estimation of the response behaviors of the industrial loads and the formulation of the relevant strategies are helpful to fulfill their DR potentials. Firstly, the response characteristics of the energy-intensive industrial loads are analyzed, and the specific threshold judgment method for industrial loads participating in peak regulation is proposed. Secondly, the models are established to describe the response behaviors of the typical industrial loads and the decision-making behavior of the dispatching and control center, respectively. Thirdly, considering the rationality of the behaviors for peak-regulation market participants, a 1-N non-cooperative game model is established to describe the interaction behaviors between the peak-regulation market participants. Then, the impact of the different incentive modes on peak-regulation market participants is further discussed, and the corresponding solution algorithm is given. Finally, the case simulation analyses are conducted with an industrial park, and the results verify that the proposed strategy has significant peak-regulation effects, and all the peak-regulation market participants can obtain the optimal benefits.
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LIAO Siyang, XIAO Yuduo, XU Jian, LI Lingfang, XU Xiandong, JIA Hongjie
2025,49(3):22-30, DOI: 10.7500/AEPS20240414003
Abstract:Energy-intensive industrial loads, such as cement plants, have considerable potential for adjustment due to their high power consumption and low transformation costs, but their complex process requirements and strict process constraints limit the enthusiasm of enterprises to participate in demand response. Therefore, this paper proposes an economic dispatch model considering the production process of the cement plant under demand response. Firstly, based on the latest demand-side market-oriented response electricity price policy, a joint price and incentive demand response strategy is proposed, and the potential of load-side adjustment under mixed scenarios with long-term peak shaving and valley filling and short-term supply-demand imbalance is explored. Then, the typical production process of the cement plant is analyzed. The coupling relationship of each production link is described by using the state-task network method. The production process constraints are proposed to ensure the production safety in the process of power regulation. The economic dispatch model of the cement production process oriented to demand response is constructed, and the most economical safety production plan is formulated for the cement plant. Finally, based on the production data of the cement plant, the simulation case analysis shows that the proposed model can reduce the comprehensive electricity cost of industrial enterprises on the premise of ensuring their production safety, improve the enthusiasm of enterprises to participate in demand response, and realize the balance between the production power demand of enterprises and the needs of grid-side dispatch.
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ZHOU Suyang, GUAN Aobo, GU Wei, LI Yi, LYU Hongkun, CHEN Qingquan
2025,49(3):31-41, DOI: 10.7500/AEPS20240629002
Abstract:It is an effective way to promote the green development of industrial energy consumption by considering the potential of process scheduling and fully exploring the synergistic complementary characteristics of heterogeneous energy flows such as electricity, gas, cooling, and heat during the planning process of industrial integrated energy systems. This paper discusses the methods of unified modeling for typical industrial processes and optimal configuration for supply-demand energy equipment capacity from the perspective of integrated energy system planning. Firstly, an industrial integrated energy supply and demand scheme considering the difference of energy flow grade is designed. Then, the production-energy flow-carbon flow model and additional model of variable operation conditions for typical industrial processes are constructed to achieve the accurate depiction of process energy consumption. Finally, the planning model of industrial integrated energy systems considering the production-side process scheduling is proposed. To address the non-linear characteristics of the model, a linearization method based on discrete values of multi-linear terms is proposed to ensure the accuracy and efficiency of the solution. The case analysis shows that considering the potential of process scheduling during the planning process of industrial integrated energy systems can reduce the investment cost of industrial enterprises and total cost.
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DAI Lei, WANG Yubing, GUO Siqing, HU Hao, FANG Sidun
2025,49(3):42-59, DOI: 10.7500/AEPS20231225005
Abstract:Shore power systems reduce the emission of port area by shutting down the power generation equipment of docked ships, and is the central equipment of port energy-transportation integration. Its operation and planning play an important role in realizing the goal of “carbon neutrality” in the future port integrated energy system. In order to clarify the current research status and point out the bottleneck problems restricting the development of shore power systems, the port shore power system is reviewed from three aspects: environmental benefit assessment, technical standards and deployment schemes of shore power systems, policy planning and operation strategies of shore power systems. The analysis shows that the shore power system plays a key role in port green development, but the installation rate and utilization rate of shore power system present a great contradiction. In view of the future development of shore power system, three future development priorities are proposed, namely, the whole life cycle planning of shore power, the energy-transportation integration management of shore power system, and the multi-agent operation management of shore power system.
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FU Taiguoyi, DU Youtian, LYU Hao, LI Zonghan, LIU Jun
2025,49(3):60-70, DOI: 10.7500/AEPS20240318003
Abstract:Existing transient stability assessment methods based on graph deep learning consider the topological structure characteristics of power grids. However, the information transmission characteristics among multi-scale subgraphs in the topological structure of power grids are not effectively modeled, resulting in the insufficient capturing of the local and global dynamic coupling relationship of power grids by the stability judgment model, which reduces the stability judgment accuracy of the model under complex perturbations. Therefore, an assessment method for power angle transient stability integrating the information transmission process of multi-scale subgraphs is proposed. Firstly, a
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MA Xiaoyang, ZHAO Yangjun, LIANG Jinwen, XIAO Xianyong, WAN Yuheng, WANG Ying
2025,49(3):71-81, DOI: 10.7500/AEPS20240515004
Abstract:The nonlinear bifurcation phenomenon caused by time delay in power systems containing wind power has an important influence on the system stability. The introduction of time delay may transform the wind power system into the infinite-dimensional power system, causing difficulty in describing the stability region of the system directly with bifurcation theory. Therefore, a stability region partition method based on Lyapunov-Schmidt reduction for time-delay wind power systems is proposed to realize the bifurcation analysis and small-signal stability region partitioning. Firstly, the nonlinear differential-algebraic equation (DAE) model of the system is established, various types of bifurcation points are located based on the extension method, and the small-signal stability region on the parameter plane is divided by this boundary. Secondly, considering the effect of time delay, a modified dynamics model of the wind power system is established. Then, the dimensionality of infinite-dimensional multi-time-delay wind power systems is reduced based on Lyapunov-Schmidt reduction. Then, by solving the finite-dimensional bifurcation map after dimensionality reduction, the distribution of the bifurcation points under the influence of time delay is obtained, and then the small-signal multiply connected stability region in the time-delay space is partitioned. Finally, the accuracy of the stability region partition in the time-delay space is verified by time domain simulation.
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ZHANG Lei, SUN Yuanyuan, LI Yahui, ZHANG Fan, LIU Yang, LI Lisheng
2025,49(3):82-92, DOI: 10.7500/AEPS20240331008
Abstract:With the development of new power systems, renewable energy represented by wind power generation is widely utilized. Due to the influence of switching characteristics of electronic devices, wind turbines inevitably generate harmonics during the grid connection. During large-scale grid connections, the interaction between wind power cluster devices further exacerbates harmonic issues. Therefore, the measurement data based modeling method for harmonic characteristics of direct-drive wind turbines is proposed, which is used to analyze the harmonic characteristics of wind turbines in engineering practice. Firstly, the key influencing factors of harmonic characteristics at different frequencies are identified, and a harmonic characteristic analysis model for wind turbines is proposed, which simplifies the overall process of harmonic modeling for wind turbines. Secondly, based on the actual topology of wind power clusters, an aggregation harmonic model of wind power clusters is established, which clarifies the interactive effect of harmonics among wind turbines and quantifies the correlation between individual units and clusters considering the coupling effects between wind turbines. Finally, the harmonic characteristics of direct-drive wind turbines are validated by experiments; the accuracy for the aggregated harmonic model of clusters is validated by simulations, and the accuracy of wind power cluster modeling is improved.
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HUANG Chen, SHEN Yi, LI Yinhong
2025,49(3):93-102, DOI: 10.7500/AEPS20240316002
Abstract:Unlike traditional generators, the output current of a doubly-fed induction generator (DFIG) with crowbar protection switched on contains a considerable rotor frequency component close to the power frequency, which cannot be filtered out by protection algorithms based on power frequency measurement principles, posing a challenge to the setting of the power frequency protection in the new power systems. Based on the time-domain expression of the DFIG output current with crowbar protection switched on, this paper comprehensively analyzes the different factors that affect the envelope intervals, explores the calculation method of each factor in the envelope intervals by categorizing and summarizing them, and obtains a two-layer overall calculation process. On this basis, the calculation method for the DFIG current envelope intervals with crowbar protection switched on is proposed. This method takes into account various possible fault conditions, and comprehensively considers the influence of different factors on the rotor frequency component, and obtains a more accurate output current envelope interval by setting discrete steps and solving point by point. The simulation of DFIG integrating the infinity system is carried out on the MATLAB/Simulink platform. The results indicate that the errors between the calculated values of the proposed method and simulated values are relatively small, thus verifying the correctness of the proposed calculation method.
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LIU Yumeng, LI Jiasong, GU Xueping, DANG Yujie
2025,49(3):103-113, DOI: 10.7500/AEPS20240604005
Abstract:While the coupling relationship between the power grid and the natural gas network tends to be close, fault propagation across heterogeneous energy systems introduces new risks of cascading failures in the gas-electricity interconnected system. However, none of the related studies conducted at the current stage has taken into account the characteristics of gas temperature change during the transmission process of natural gas, which may make it difficult to reflect the actual evolution of cascading failures and conduct an accurate impact assessment. Firstly, this paper deduces the non-isothermal transport equation in the steady state of a natural gas pipeline and establishes the corresponding model. Through theoretical analysis and simulation, it is proven that there is a relationship among the gas flow rate, gas temperature, and pressure difference between the beginning and end of the pipeline. On this basis, a model for evaluating the cascading failures of gas-electricity interconnected system considering the non-isothermal characteristics of natural gas is proposed to more accurately assess the impact of natural gas on the cascading failures. Finally, the validity of the proposed model is verified with a test case consisting of an IEEE 39-bus system and a modified Belgian 20-bus natural gas system, and compared and analyzed with related studies based on the isothermal assumption. The results show that the proposed model can adequately reflect the non-isothermal characteristic of the natural gas system, with regard to its accuracy and practicality in assessing the impacts of cascading failures in the power system.
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YU Jinyu, ZHOU Lidan, YU Tianyou, WANG Ziqiang, ZHAO Xuanhui, YAO Gang
2025,49(3):114-124, DOI: 10.7500/AEPS20240626003
Abstract:Energy storage systems can smooth out fluctuations in renewable energy and store excess electricity. However, a single type of storage unit cannot meet demand due to limitations in response speed and capacity. To increase the capacity of islanded DC microgrids to accommodate renewable energy, this paper proposes a control scheme for an electricity-hydrogen hybrid energy storage system based on distributed model predictive control (DMPC). This scheme makes full use of the high power density of lithium batteries and the high energy density of unitized renewable hydrogen fuel cells. Firstly, DMPC controllers are designed for the electricity and hydrogen energy storage subsystems. Under normal operation conditions, the electricity and hydrogen energy storage systems respectively support high- and low-frequency loads, reducing the number of charging-discharging cycles for the batteries and extending their lifespan. Under the condition of hydrogen energy storage system shutdown, the electricity energy storage system independently supports the load to maintain system stability alone. Secondly, considering the different response speeds of the electricity and hydrogen energy storage systems, this paper introduces a weight-adaptive operator into the state-of-charge recovery term of the DMPC cost function. It prevents a significant drop in the average voltage recovery capability of the electricity energy storage system, which is responsible for rapid response, thereby improving DC voltage transient stability. Finally, the effectiveness of the proposed control strategy is verified through simulation by Simulink.
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LIANG Zhonghao, WANG Lifang, LI Jianlin
2025,49(3):125-134, DOI: 10.7500/AEPS20240627002
Abstract:An optimal control method based on Nash equilibrium is proposed for hydrogen production systems with photovoltaic-storage coupling. The method regulates and distributes the output of photovoltaic, the charging/discharging power of the energy storage battery pack, and the input power of the hybrid electrolyzer. In the method, the output capacity of the energy storage battery pack, the power fluctuation rate of the hybrid electrolyzer and the sum of economic benefits generated by photovoltaic and hydrogen sales are selected as the three players. The corresponding payment functions of the players are then set up, and the optimal control model is built. In order to simulate and verify the proposed control method, a Nash equilibrium-based simulation model for the optimal control of hydrogen production systems with photovoltaic-storage coupling is established. Simulation results show that the proposed strategy not only reduces the abandonment rate of photovoltaic to less than 5%, but also optimizes the output power of the energy storage battery pack to maintain the range of the state of charge between 20% and 90%, effectively avoiding the overcharging and overdischarging. In addition, on the basis of maximizing the utilization of photovoltaic power generation, the input power of the hybrid electrolyzer is optimized to maximize hydrogen production. During the optimized operation of the hydrogen production system with photovoltaic-storage coupling, the operating voltage of the alkaline electrolyzer/proton exchange membrane electrolyzer fluctuates up and down by about 0.7%, and the bus voltage fluctuates up and down by about 0.2%, that is, the proposed strategy improves the operation performance of the whole system to a certain extent.
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LUO Jiayi, XING Haijun, QUAN Wenbin, SHI Yiqin
2025,49(3):135-144, DOI: 10.7500/AEPS20240413003
Abstract:Under extreme high temperature, the cooling load of new power systems increases rapidly and the failure rate of transmission equipment increases, which makes it difficult to operate safely and reliably. To enhance the resilience of the new power system against such extreme high temperature, a differentiated planning based resilience enhancement scheme is proposed by taking into account the impact of critical loads on system resilience. Firstly, a relationship model between system load and line failure rates under high temperature is established to identify vulnerable lines. Secondly, to avoid the “overshadowing” phenomenon caused by neglecting critical loads in the assessment, a resilience assessment method that considers load classification is proposed. Then, considering the uncertainty of failures, based on differentiated planning, a two-stage robust optimization model for vulnerable lines and energy storage is established with the objective of minimizing operation costs and load losses. The column-and-constraint generation (C&CG) algorithm is also used to solve and obtain the optimal planning scheme. Finally, the effectiveness of the scheme is validated through numerical cases.
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JI Xingquan, JIANG Haiyang, ZHANG Yumin, YANG Ming, CAI Fudong, WANG Chengfu
2025,49(3):145-155, DOI: 10.7500/AEPS20240506009
Abstract:The existing optimal configuration methods of microphasor measurement units (μPMUs) fail to consider the frequent changes in the actual topology of distribution networks and the three-phase imbalance. Therefore, this paper proposes a combined optimal configuration method of μPMUs for three-phase unbalanced distribution networks considering network reconfiguration. Firstly, based on the three-phase unbalanced characteristics of distribution networks, the concept of zero-injection phase is put forward, and its effect on the local observability of the network is analyzed. Incorporating zero-injection phases into the μPMU configuration rules can effectively reduce the number of μPMUs that need to be configured for complete observability of the network. Secondly, to deal with the problem of partial unobservability caused by the changes in the topology of distribution networks, an optimal configuration model of μPMUs considering the dynamic reconfiguration of three-phase unbalanced distribution networks is proposed. This model takes the typical topology obtained by dynamic reconfiguration solution as the basis for μPMU configuration, and considers the cost differences between three-phase and single-phase μPMU configuration. While minimizing the combined configuration cost of μPMUs, the system measurement redundancy is improved. Finally, taking the IEEE 34-bus and IEEE 123-bus systems as cases for simulation verification, the results show that the proposed model can adapt to the changes in the topology of distribution networks and significantly reduce the configuration cost of μPMUs.
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HUANG Hua, XU Taishan, GAO Zonghe, BO Lin, LU Jinjun, TU Mengfu
2025,49(3):156-169, DOI: 10.7500/AEPS20231008002
Abstract:A two-stage optimization algorithm based on complementary constraints and absolute value linearization relaxation is proposed to efficiently solve the large-scale nonlinear day-ahead reactive power schedule optimization problems with multi-time period coupling absolute value constraints and integer variables. By using a linearization method to relax the multi-time period coupling absolute value constraints, and based on equivalence transformation between complementary conditions and discrete variables, the original problem is transformed into a continuous mathematical programming problem with complementary constraints. The solution steps are decomposed into two stages which are solved by the interior point method sequentially. Firstly, the approximate optimization solution for discrete variables is quickly obtained without considering complementary constraints. Then, the complete model with complementary constraints is solved to obtain the accurate optimization solutions for both discrete and continuous variables. In addition, a fast sparse storage calculation method is proposed to reduce the computational complexity of the integrated Hessian matrix during the iteration of the interior point method. The simulation results of standard test systems such as the IEEE 118-bus system and an actual provincial power grid demonstrate the effectiveness and rapidity of the proposed algorithm, as well as its engineering applicability in real large-scale power systems.
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LI Peijie, YU Junlian, SUN Zhiyuan
2025,49(3):170-177, DOI: 10.7500/AEPS20240318001
Abstract:The scenarios that cause safety problems, such as power flow overloads, in power systems are on the rise. Topology optimization can eliminate the problem of power flow overload by transforming the network topology. However, the complex model transformation logic and the introduction of large-scale integer variables significantly increase the complexity of modeling and the difficulty in solving. Therefore, this paper proposes a topology optimization method for the transmission network that considers the topology transformation of the main connection line. Firstly, based on the general transformation model for main connection topology of substations, a mixed-integer second-order cone programming (MISOCP) model is established. The model can not only consider the impact of topology transformation on active power flow, but also take into account the constraints of reactive power balance and voltage, solving the problem that previous topology optimization models based on DC power flow may have potentially optimistic scheduling modes or even deteriorated voltage indicators when eliminating the active power overload. Secondly, to solve the proposed model efficiently, an accelerated solution method for neighborhood search is proposed. Finally, simulation calculations are conducted on IEEE 14-bus, IEEE118-bus, and Polish 2383-bus systems. The results show that the proposed optimization model can solve the problem of line overload economically and effectively, and the proposed solving method can improve the solving efficiency of the proposed model.
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WANG Yichen, WANG Feng, ZHUO Fang, YU Kefan
2025,49(3):178-188, DOI: 10.7500/AEPS20240130003
Abstract:The capacitor-inductor-inductor-capacitor (CLLC) resonant converter is an isolated bidirectional DC/DC converter with high operating efficiency and good soft switching characteristics, which is suitable for DC power systems. However, the traditional frequency modulation control used in resonant converters involves only one control variable, which makes it difficult to simultaneously maintain stable output voltage of the converter and optimize the resonant current. To enhance the overall operating efficiency of the CLLC resonant converter, this paper proposes an over-resonant frequency modulation and extended phase-shift control method based on the particle swarm optimization algorithm. This control method introduces two phase-shift control variables based on the frequency modulation control method, which increases the freedom degree of controlling the CLLC resonant converter. Moreover, based on the accurate time-domain model and utilizing the particle swarm optimization algorithm, the optimal operating point of the converter can be explicitly determined when employing the over-resonant frequency modulation and extended phase-shift control method. Thus, the operating efficiency of the converter under different operation conditions is significantly improved. Finally, the feasibility of the proposed current optimization method is verified through a 2 kW-level experimental prototype.
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WANG Chuyang, DONG Xuan, LIN Jinjiao, WANG Xinying, ZHANG Li
2025,49(3):189-199, DOI: 10.7500/AEPS20240125006
Abstract:The unified power flow controller can quickly and accurately adjust the power flow in the power grid. However, it comes with a high cost. The phase-shifting transformer has a low cost but cannot realize the continuous adjustment, exhibits lower compensation accuracy, and generates higher impacts when switching voltage levels. This paper improves the thyristor valve group in the phase-shifting transformer and derives a hybrid valve group of insulated gate bipolar transistors (IGBTs) and thyristors based on the two-level matrix-type direct AC-AC conversion topology. Without the adoption of electrolytic capacitors and reactors, this hybrid valve group utilizes fully controllable devices for continuous high-precision voltage regulation and employs thyristors for polarity reversal of valve groups. Then, a hybrid phase-shifting transformer with rapid and continuous voltage regulation based on this valve group is proposed. While retaining the main structure of the traditional thyristor-based phase-shifting transformer, a hybrid valve group of IGBTs and thyristors is incorporated into each phase. The cooperative operation of hybrid and common valve groups realizes millisecond-level rapid adjustment of the operating condition of the phase-shifting transformer. In addition, a strategy for valve group driving with additional spike suppression is proposed to mitigate voltage and current surges during valve group switching. Finally, the practicality of the proposed phase-shifting transformer is validated through simulation.
Volume 49,2025 Issue 3
>Power Supply and Demand Interaction for Re-electrification in Industrial Production Processes
>Basic Research
>Application Research
Special Issue
Virtual Special Issue
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- Hot Topics
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JIAO Zhijie, XU Yin, LIU Zhao, WANG Xiaojun, HE Jinghan, SI Fangyuan
Available online:December 30, 2024 DOI: 10.7500/AEPS20240519001
Abstract:The arrival of a cold wave triggers a sudden drop in weather temperature, at this time, the energy consumption of the load increases, the output of renewable energy sharply decreases, the system backup and the power supply capacity of the higher-level power grid are insufficient, resulting in a significant power shortage problem within the power grid in a short period of time. With the increasing number of electric vehicles on the load side and the improvement in the responsiveness of flexible resources, the load-side flexible resources are adjusted to compensate compensate for the power shortage caused by the cold wave. This paper first clarifies that the flexibility of resources varies with changing scenarios, explores and constructs models of flexible resources such as electric vehicles during cold wave events. Secondly, considering that electric vehicles in flexible resources need to participate in grid scheduling through aggregation, a method for aggregating electric vehicles with uncertain connection times is developed. Subsequently, based on the flexible resources during cold wave events, non-residential loads, and residential loads, a rolling optimal scheduling method for the power grid during cold wave weather is proposed with the objective of minimizing social losses. The electricity adjustment of various resources in the grid during cold wave weather is determined. Finally, through case studies, the proposed method is shown to effectively address power shortages in the grid during cold wave events.
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WANG Pengwei, XU Bingyin, LIANG Dong, WANG Lianhui, WANG Chao, ZOU Guofeng
Available online:October 31, 2024 DOI: 10.7500/AEPS20240315002
Abstract:Distinguishing whether faults in medium voltage distribution lines are caused by lines touching trees is of great significance for clarifying the causes of forest fires and preventing line faults from causing forest fires. The zero-sequence currents of various high-impedance grounding faults are obtained through prototype experiments in the paper, and the long-term variation features of the zero-sequence current waveforms of high-impedance grounding faults are analyzed. Analysis shows that there are significant differences in the fluctuation, monotonicity, and sharpness of the waveforms of the effective value of the zero-sequence currents for line touching trees grounding faults compared to other high-impedance grounding faults. A multi feature fusion parameter set including standard deviation, discrete coefficient, kurtosis, skewness of the zero-sequence current effective value curve is designed, and a ientification method for tree-touching grounding fault of medium-voltage line based on support vector machine is constructed. The results showed that the proposed method achieved a fault recognition accuracy of 98%.
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LIU Jie, SHI Fang, SONG Xuemeng, TIAN Shuoshuo, NIE Liqiang
Available online:October 17, 2024 DOI: 10.7500/AEPS20231101004
Abstract:The existing intelligent assessment methods for transient frequency in power systems do not adequately consider the temporal characteristics of input data. Therefore, a frequency safety assessment method for power systems based on intelligent prediction of transient frequency response curves is proposed in the paper. A multivariate sample convolutional interactive network is designed to fully exploit the temporal characteristics of power system measurement data, thereby improving the prediction accuracy of power system transient frequency response curves; Key indicators such as maximum frequency deviation, occurrence time of maximum frequency deviation, and the metastability frequency are calculated based on the predicted frequency response curves, and the frequency safety of the system is comprehensively assessed. Simulation tests are conducted on frequency stability standard examples, and the results showed that the proposed method effectively improved the accuracies of frequency response curve prediction and system frequency safety assessment compared to classical methods such as deep learning.
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LI Yong, LI Yinhong, LIU Huanzhang, LIU Yang
Available online:October 09, 2024 DOI: 10.7500/AEPS20240228008
Abstract:The last section of zero-sequence current protection of AC line adopts 300 A, which has the risk of disordered tripping.Therefore, a new principle of high-resistance grounding distance relay based on zero-sequence reactance line and non-fault phase polarization is proposed. The relay adopts the technical route of phase selection before measurement. The phase selection element combines zero-sequence reactance line and non-fault phase polarization method to form a variety of combined criteria to complete the phase selection. Due to the phase difference between the zero-sequence current at the protection installation and the zero-sequence current at the fault point, the zero-sequence reactance lines of the single-phase grounding fault phase and the advance phase of the inter-phase grounding fault have aliasing region when the fault point is near the setting point. The large variation of the operation voltage of the non-fault phase is not conducive to distinguishing the two types of faults in the aliasing region, and thus the phase selection element is divided into low-resistance module and high-resistance module. The low-resistance module adopts the zero-sequence reactance line with the downward bias, which is used to identify the near end and low-resistance short circuit. With the assistance of the low-resistance module, the high-resistance module only needs to deal with the faults near the set point, which reduces the difficulty of distinguishing the two types of faults . After phase selection, the operation voltage before fault is obtained by non-fault phase polarization method, so as to determine the operation characteristics of the relay. The ability of high-resistance distance relay to withstand the transition resistance is far beyond the requirements of the regulations, which improves the selectivity of ground backup protection to high-resistance faults.
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HAN Zhaoru, SHI Fang, ZHANG Hengxu, JIN Zongshuai, YUN Zhihao
Available online:September 29, 2024 DOI: 10.7500/AEPS20240116008
Abstract:The accurate and reliable detection of high-impedance grounding fault (HIGF) is a challenging issue in fault handling for distribution networks, and normal capacitor switching operations can cause interference. Addressing this problem, a disturbance-resistant detection method for HIGFs based on zero-sequence Lissajous curve analysis is proposed in this paper. Firstly, the zero-sequence electrical quantities of HIGFs and capacitor switching disturbances are theoretically derived. There is no regular difference in the traditional time-frequency domain feature aspect between the two, thereby clarifying the cause of the interference. Further, the zero-sequence current and voltage waveforms are reconstructed into zero-sequence Lissajous curves. A quantitative index for the distortion complexity of the Lissajous curve trajectory shape based on the mathematical morphology theory is proposed, and an adaptive starting criterion is designed in combination with the probability distribution law of the zero-sequence Lissajous curve area. The disturbance-resistant detection algorithm for high-impedance grounding faults in the noise scenario is presented. Finally, the effectiveness and reliability of the proposed method are verified through electromagnetic transient simulation examples and real fault tests in the distribution network.
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HE Zhiyuan, GAO Chong, YE Hongbo, YANG Jun, WANG Chenghao, SHENG Caiwang
Available online:August 29, 2024 DOI: 10.7500/AEPS20240506007
Abstract:Controllable line-commutated converter(CLCC) is a new type of DC converter equipment proposed to solve the commutation failure problem of conventional DC transmission converter. In June 2023, the world"s first set of controllable phase converter valves for the ±500kV/1200MW Gezhouba to Shanghai Nanqiao high-voltage DC transmission system renovation project (hereinafter referred to as "Genan renovation project") was successfully put into operation. The technical requirements and principles of CLCC are analyzed, as well as its technical and economic benefits. Combined with the input conditions of the Genan renovation project system, the electrical parameters and structural design scheme of the controllable line-commutated converter valve were proposed, and the equipment development was completed. The type test scheme and test parameters were proposed, and the type test assessment was completed. According to the technical characteristics of the controllable line-commutated converter valve, field tests such as low-voltage test, open line test, and artificial short-circuit test were carried out to ensure the smooth operation of the project. The operation performance since the project put into operation was introduced, and the correctness of the control sequence during the AC fault was analyzed based on the field recording. Finally, the application prospects of the controllable? line-commutated converter valve in UHVDC projects, provincial AC liaison line renovation and other scenarios were prospected and analyzed, providing a reference for the further promotion and application of the controllable commutation converter valve.
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ZHAO Ziyu, CHEN Yuanrui, CHEN Tingwei, LIU Junfeng, ZENG Jun
Available online:April 28, 2024 DOI: 10.7500/AEPS20230914003
Abstract:A regional-level ultra-short-term load forecasting model based on a spatio-temporal graph attention network is proposed in this paper. Firstly, based on the existing regional-level load, cell partitioning is carried out to construct a graph topology that considers cell correlation. Secondly, effective features are extracted from the spatial, feature, and temporal dimensions through the graph attention network, one dimensional convolutional network and gated recurrent unit, connecting the fully connected layers to output the results. Finally, simulation validation is conducted based on real power load data from the New England region of the United States, and model attention weights are extracted to analyze spatial dependencies between cells. The results show that, compared with traditional models, the proposed model provides higher accuracy and stability with different prediction steps, effectively exploiting the spatial dependence of regional spatial load.
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XIE Longtao, XIE Shiwei, CHEN Kaiyue, ZHANG Yachao, CHEN Zhidong
Available online:January 04, 2024 DOI: 10.7500/AEPS20230628010
Abstract:With the large-scale development of electric vehicles, it is of great significance to study how to effectively consider the travel behavior mechanism of users and formulate rational charging prices for charging stations for the collaborative optimization and scheduling of power-transportation networks. To solve this problem, this paper proposes a pricing strategy for charging stations in the power-transportation coupling network considering the user travel cost budget. Firstly, a transportation user equilibrium model considering the travel cost budget is established, and the equilibrium state is equivalently described through variational inequalities, so as to characterize the travel demands and charging behaviors of electric vehicles. Secondly, a second-order cone optimization model for distribution networks considering power reduction is constructed. The charging station pricing problem has been transformed into an optimization problem with variational inequality constraints, and an alternating iteration algorithm combined with an extra-gradient algorithm is designed to solve the problem. Finally, the effectiveness of the proposed model and methods is verified through a case, and the results show the necessity of considering the travel cost budget for charging pricing in coupled networks.
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LI Xiang, Liu Yuhang, ZHANG Qi, WU Xin
Available online:September 12, 2023 DOI: 10.7500/AEPS20230425001
Abstract:The illegal charging behavior of electric bicycles (EBs) in households has temporal randomness and spatial concealment,which poses significant safety hazards and is difficult to effectively manage. A non-intrusive real-time monitoring system for EB charging based on wavelet detection and feature graph decision is proposed, utilizing the characteristics of real-time autonomous execution and easy promotion of non-invasive monitoring systems. Considering the physical structure and charging characteristics of EB loads, the typical common characteristics of EB loads are analyzed from both transient and steady-state perspectives. The EB proprietary feature map with strong distinguishability and universality is constructed in advance to realize consistent and structured expression of EB steady-state common features. In the actual monitoring process, in order to reduce the computational power demand and data transmission pressure of the system, EB specific transient phenomena with high-frequency components are accurately located based on wavelet transform to complete EB like event detection. Finally, extract event waveforms and train efficient classifiers through graphs for load identification and real-time upload. By monitoring actual users, the effectiveness of the monitoring system has been verified, which can effectively solve the problem of charging EBs in buildings and households.
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ZHENG Yao, ZHANG Jie, YAO Wenxuan, QIU Wei, TANG Sihao
Available online:March 16, 2023 DOI: 10.7500/AEPS20220813001
Abstract:As the power system gradually moves toward a new ecosystem of energy interconnection and the deep coupling of the network layer and physical layer, the threat of network attacks on the power system continues to rise. The source identity (ID) spoofing attack, as a new and complex, strong stealthy false data injection attack, can cause the grid control system to misjudge and cause system paralysis. To address this problem, a spatial feature-based method is proposed for detecting false data injection attacks on synchronized measurements of power grids. It has extracted different spatial features of the synchronized measurement devices at different locations by variational modal decomposition (VMD) and improved discrete orthonormal Stockwell transform (IDOST), so as to extract the authentication information of the measurement data without losing the spatial features of the measurements. Combined with light convolutional neural network (LCNN) to evaluate the likelihood of measurement data being attacked by source ID to enhance the speed of detection response. The effectiveness of the method is verified by the detection results of actual multi-point synchronous measurement data.
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XIAO Bai, ZHANG Bo, WANG Xinwei, GAO Ningyuan
Available online:February 20, 2023 DOI: 10.7500/AEPS20220807002
Abstract:Wind power prediction is very important for the economic dispatch of power systems containing wind power. Aiming at the problem that point prediction is difficult to describe the uncertainty of wind power, a short-term wind power interval prediction method based on combined mode decomposition and deep learning is proposed. Firstly, the original wind power sequence is decomposed into multiple modal components by using the improved complete ensemble empirical mode decomposition with adaptive noise, and the high-frequency strong non-stationary components are decomposed again by using the variational mode decomposition. On this basis, the sample entropy is used to calculate the complexity of each component and reconstruct them into trend components, oscillation components and random components. Then, the three components are input into the Bayesian optimization bidirectional long short-term memory neural network to establish their respective prediction models, and the point prediction values of the three components are obtained. The mixed kernel density estimation method is used to estimate the error distribution of the prediction results of oscillation components and random components, and the overall interval prediction results are obtained by combining the point prediction values. Finally, the actual examples show that this method has higher prediction accuracy than other models.
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LIU Wensong, HU Zhuqing, ZHANG Jinhui, LIU Xuejing, LIN Feng, YU Jun
Available online:September 27, 2022 DOI: 10.7500/AEPS20210323003
Abstract:Considering the characteristics of small scale, nested entities and abbreviated entities for electric corpus, the named entity recognition (NER) based on enhanced vectors of text features is proposed. Firstly, by the way of the low grain word segment and the preset dictionary, the semantic information in Chinese words is properly utilized, and the transmission errors caused by word segment are decreased. Secondly, the features of inner structure of a single Chinese word is learned by the word-level bidirectional gated recurrent unit (Word BiGRU). Together with the features of the part of speech for words and word length, the enhanced word vector is built by concatenating these features vectors with word vectors. Finally, the NER model is designed with BiGRU, attention mechanism and conditional random field (CRF). The proposed method is verified using electric corpus and F1 measurement reaches 87.02%, which proves the effectiveness of NER for electric power industry.
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ZHANG Yi, YAO Wenxu, SHAO Zhenguo, ZHANG Liangyu
Available online:August 18, 2022 DOI: 10.7500/AEPS20211203007
Abstract:Aiming at the problems of abnormal operation condition monitoring for environmental protection in polluting enterprises at present, such as difficult implementation, large identification errors and easy tampering with the results, this paper proposes an identification method of abnormal operation conditions for environmental protection based on power quality monitoring data. The multi-dimensional power quality data obtained from non-invasive load monitoring at the public power entrance of enterprise equipment are used to train the model of condition classification, to realize abnormal condition identification, which is different from the existing scheme of power consumption monitoring with a separate meter installed for each device. First, the time series change-point detection and the clustering calculation for the characteristic data representing the production conditions are carried out to realize the division of production operation conditions of enterprises. Then, combined with the operation of environmental protection equipment, the categories of environmental protection operation conditions for classification are obtained. Furthermore, the operation condition scenarios related to environmental protection are classified and learned by the Stacking learning model. Finally, the trained classification model is used to identify the abnormal operation conditions for environmental protection in the enterprise. The effectiveness of the proposed method is verified by the simulation test data and the actual enterprise data.
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JIANG Wei, WANG Minghua, CHEN Jinming, LIU Jiangdong, PU Shi, XU Zhiqi
Available online:May 13, 2022 DOI: 10.7500/AEPS20211031001
Abstract:In order to improve the efficiency of power supply reliability calculation for the complex distribution system, a reliability calculation method based on the Neo4j graph database is proposed. Firstly, the topology structure of the distribution network is stored in vertex-edge form through the graph database. Meanwhile, the feeder classification and load partitioning in the complex distribution system is completed by using the characteristics of different types of edges in the Neo4j graph database, and the distribution network diagram model based on the graph database is built. Secondly, the subgraph division of the distribution network diagram model is combined with path search, and the model simplification is completed based on each subgraph. Finally, the power supply reliability analysis of the distribution system is realized based on the minimal path reliability algorithm combined with the efficient shortest path query and other functions of the Neo4j graph database. The effectiveness of the proposed method is verified by comparing the Roy Billinton test system and an actual 10 kV distribution network in China for algorithm verification.
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LI Zheng, CHEN Wu, HOU Kai, SHI Mingming, MOU Xiaochun, ZHU Jinsong
Available online:April 26, 2022 DOI: 10.7500/AEPS20210806005
Abstract:When the flexible ring network controller cancels the interface transformer, the transmission of the zero-sequence voltage component cannot be prevented when the AC side fails, thus increasing the fault range. Therefore, this paper uses classical circuit analysis and positive and negative sequence analysis algorithms to explain the basic principles of the formation and transmission of zero-sequence voltage components. A topology of the flexible ring network controller without the interface transformer is proposed. The AC side converters are all modular multilevel converters with traditional half-bridge sub-modules. And the full-bridge sub-module valve strings are connected in series on the positive and negative polarity busbars. Utilizing the ability of the full-bridge sub-module to output positive and negative voltages, the DC side voltage fluctuations are suppressed, and the fault range is prevented from expanding. By using the MATLAB/Simulink software, the characteristics of zero-sequence voltage suppressed during the fault are simulated and analyzed. The simulation results verify the correctness of the theoretical analysis and the effectiveness of the proposed topology.
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YOU Wenxia, LI Qingqing, YANG Nan, SHEN Kun, LI Wenwu, WU Zeli
Available online:March 30, 2022 DOI: 10.7500/AEPS20210731001
Abstract:Aiming at the problems that the consumer power consumption data categories are unbalanced in electricity theft detection, and the ensemble learning method using voting as a combination strategy can not give full play to the advantages of multiple different learners, a model using Stacking ensemble learning to fuse multiple different learners is proposed and applied to electricity theft detection. Firstly, starting from the factors affecting electricity metering, six electricity theft behavior modes are simulated according to five common electricity theft methods; Secondly, synthetic minority oversampling technique (SMOTE) is used to process the unbalanced power consumption data, and k-fold cross-validation method is used to divide the balanced training sets to alleviate the overfitting caused by repeated learning; Then, the evaluation indicators and diversity metrics are employed to optimize different primary learners and meta-learners of the model, and a Stacking combination learning electricity theft detection model integrating the advantages and differences of different learners is constructed; Finally, the comparative analysis results of examples show that the proposed electricity theft detection model can effectively solve the imbalance of power consumption data categories, give full play to the advantages of different learners, and the evaluation index is good.
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Available online:December 01, 2021 DOI: 10.7500/AEPS20210510001
Abstract:While the flexibility of power systems operation can be improved by topology optimization, the dimension of system-level discrete decision variables, including the connections of lines and substation busbars, is prohibitively high. Thus, the topology optimization problem of power systems can hardly be solved by the conventional mixed-integer optimization method. Aiming at this problem, a reinforcement learning based method is proposed combining asynchronous advantage actor-critic and power system domain knowledge, which transfers the computational burden of online optimization to the offline agent training stage. The defined reward function is adopted to minimize the violations of power transmission line flow limits. Forced constraints verification is employed to reduce the searching space and improve the efficiency of the reinforcement learning. The fast computation of the topological structure optimization of power system operation is realized,and the operation security of power systems is enhanced. The effectiveness of the proposed method is validated by simulation testing results.
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Zhang Yujia, YUAN Ye, ZHOU Suyang, ZHU Hong, ZHOU Aihua, CHEN Qingquan
Available online: DOI: 10.7500/AEPS20240112003
Abstract:With the rapid growth of the distribution network and the high penetration of distributed resources, the topology of distribution networks has become increasingly complex, posing significant challenges to fault location analysis. When applying matrix algorithms and intelligent optimization algorithms to fault location, it is necessary to construct network matrices or establish optimization models based on changing topology information. This greatly increases the computational burden and complexity, leading to low efficiency in data processing and computation. Therefore, this paper first constructs a graph data model for the distribution network topology. Utilizing graph projection techniques, it extracts optimized subgraphs tailored for fault tracing scenarios from the panoramic power grid graph. On this basis, the Yen"s shortest path search algorithm is employed to find potential fault paths from the power source to the abnormal nodes. By traversing the line nodes and assessing their overcurrent information, the fault section is identified, thereby resolving the issues of accurate representation and rapid search of the power grid topology. This enables quick and precise fault localization in large-scale complex distribution networks, greatly enhancing fault search efficiency while ensuring the accuracy of fault tracing.
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LI Bo, WEI Guangrui, ZHONG Haiwang, LIU Hui
Available online: DOI: 10.7500/AEPS20240409003
Abstract:The IEEE test case has been widely used for simulation testing in various fields such as power system planning and operation. However, due to data privacy concerns, it isn"t easy to access publicly available datasets of actual power system generation and network structures. To address the issue, based on the evolution concept of three-generation power grids, a new transmission test system generation method is proposed to build test cases that reflect actual power system network structures. Firstly, a transmission expansion planning model considering N-1 security constraints is established. Secondly, the optimization objectives and constraints are proposed according to the characteristics of different stages of network development to simulate the evolution process of the electricity network. To enhance the solving efficiency of the model, a binary representation method of transmission corridors is introduced to reduce the number of 0-1 variables. Finally, the provincial power grid is used as an example to verify the effectiveness of the proposed open-source power system dataset, according to the statistical characteristics of complex networks. The proposed dataset is also applied to optimal transmission switching for further verification.
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Wang Shen, WEI Xingshen, ZHU Weiping, ZHU Daohua, GUAN Zhitao
Available online: DOI: 10.7500/AEPS20240523001
Abstract:Log anomaly detection is one of the key technologies to monitor the operation of distribution master station system and identify abnormal behavior. Existing log anomaly detection methods based on deep learning rely on a large amount of in-domain training data, and the scarcity of training data will lead to a significant decline in performance. Aiming at the above problems, based on the contextual reasoning characteristics of large language models, an adaptive hint strategy is designed and a training-free anomaly detection scheme for distribution master logs is implemented. Firstly, a demonstration example filtering algorithm is designed to dynamically select several high-quality demonstration examples from a small number of labeled local logs for different online logs. Then, combined with the task description and human experience knowledge, a text hint is automatically constructed to guide the large language model to complete the anomaly detection task of distribution master station logs. The experimental results on the general data set and the self-built distribution master station data set show that the proposed scheme has better performance than the existing methods, showing higher flexibility and generalization.
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Chen Chun, ZHAN Luxin, CAO Bozhong, CAO Yijia, Li Yong, LIU Junle
Available online: DOI: 10.7500/AEPS20240723005
Abstract:The continuous integration of power electronic devices in distribution networks has led to an increasing level of harmonic currents, posing challenges for traditional transformer secondary harmonic restraint differential protection. Simultaneously, single-feature identification methods are influenced by distributed energy resource types and closing angles, making it difficult to accurately distinguish fault currents and excitation inrush currents in different scenarios. To enhance the accuracy of excitation inrush current identification, this paper proposes a multi-angle time-frequency analysis method that comprehensively integrates time-domain, frequency-domain, and time-frequency-domain features. It utilizes Bayesian optimization of XGBoost (extreme gradient boosting) classification parameters to improve model generalization, enabling accurate identification of fault currents and excitation inrush currents under various capacities and types of distributed energy resource integration. The SHAP (shapley additive explanations) value analysis method is employed to reveal the contribution of each feature value in the identification model. The proposed method was verified through PSCAD/EMTDC simulation data and field measured data. Within the data samples provided in this article, the Bayesian-XGBoost algorithm under multi-angle time-frequency analysis has an accuracy of identification of excitation inrush current close to 100%, which is better than several common classification algorithms compared in this paper.
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LIANG Hao, QIN Chuan, XIE Huan, LIANG Beihua, WU Tao, WANG Xuanyuan, WU Long
Abstract:It is an effective measure to improve the whole process voltage support ability of the power supply side to deploy the distributed synchronous condenser (SC) in renewable energy station. However, the current "reactive outer loop + voltage inner loop" cascade strategy is adopted to integrate the SC to the automatic voltage control system (AVC) of the station to restrict its low-frequency voltage source characteristics. This paper first describes the existing problems of SC access to the AVC of the station, and proposes the requirement of constant voltage in the whole process of SC. Then, based on the topology of the renewable energy station with SC, the reactive voltage conversion coefficient and the reactive power shunt influence factor are analyzed. Based on this, a new scheme of "constant voltage + reactive power shunt suppression" for integrating the SC to the AVC is proposed. The program was developed in a domestic mainstream manufacturer's equipment model, and the effectiveness of the scheme was verified by in-loop simulation of the SC and AVC dual controller at the station. Finally, the engineering application was completed in an actual new energy station. The field operation results show that the scheme realizes the steady-state regulation of AVC multi-type reactive power equipment of the station, effectively reduces the voltage fluctuation amplitude of PCC bus of the station, gives full play to the whole process voltage control of the SC, and guarantees the voltage stability margin of the system.
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TIAN Xincui, CHEN Kaiwen, SHAN Jieshan, ZHANG Yining, YU Jinyun, LI Qiang
Abstract:The fault information in grounding electrode lines is weak and well-hidden, making detection and fault location very difficult. Based on this, a new single-ended fault location algorithm for grounding electrode lines is proposed, utilizing broadband excitation injection and the short-time matrix pencil method (STMPM). First, a Gaussian signal excitation with an “oscillatory decay characteristic” is injected into the grounding electrode line in differential mode, ensuring that the injected excitation does not leak into the DC system side through the neutral bus and minimizing waveform distortion during the propagation of the signal along the grounding electrode line, thereby improving the detection efficiency of fault traveling waves. Secondly, sliding short-time windows are used to perform singular value decomposition (SVD) on the fault traveling waves. The eigenvalues obtained from the decomposition are used to distinguish between interference signals and fault signals, effectively amplifying the weak fault signals while suppressing the interference signals. Finally, the damping factor of the fault traveling wave within the short window is determined, establishing a one-to-one mapping relationship between the zero-crossing moment of the damping factor and the arrival time of the fault traveling wave, and the fault distance is then determined. Extensive simulations show that the distance measurement algorithm can effectively detect fault traveling waves and achieve high fault location accuracy.
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WANG Ziyuan, XU Yin, WU Xiangyu, LI jiaxu
Available online: DOI: 10.7500/AEPS20241024004
Abstract:The proportion of electricity received outside the urban power grid is high, and extreme events leading to connectivity failures in the power transmission channels of the urban superior power grid may cause major power outages. In this extreme scenario, by flexibly configuring and ensuring supply through microgrid clusters, critical load survival can be achieved. However, the transient frequency fluctuations of microgrids under sudden power shortages directly affect the success or failure of self configuration operation and supply guarantee. Firstly, a dynamic frequency constraint of microgrid considering multi resource collaboration was constructed based on the system frequency response model. Secondly, the frequency response model of microgrid containing nonlinear constraints such as ordinary differential equations and limiting links was discretized using the forward Euler method. Then, a microgrid extreme survival model was constructed considering the dynamic segmentation requirements of microgrid clusters
