Table of Content

28 April 2024, Volume 57 Issue 4

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Optimization Configuration Strategy for Integrated Energy System

Bi-level Collaborative Configuration Optimization of Biogas-Wind-Solar Integrated Energy System Based on Energy Hub

Zimeng LI, Tiankuo WANG, Pengfei HU, Yanxue YU, Yi DU, Qiyuan CAI

2024, 57(4):  1-13.  DOI: 10.11930/j.issn.1004-9649.202303062

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In order to solve the collaborative optimization problem of rural biogas-wind-solar integrated energy system, a bi-level planning model of collaborative optimization of biogas-wind-solar integrated energy system was proposed based on energy hub. In the upper level, the Pareto optimal solutions of the configuration scheme were obtained using the NSGA-II algorithm with the goal of minimizing the annual total cost and carbon emissions. In the lower level, the optimal operation scheme was obtained with the objective of minimizing the operation cost (including carbon emission cost). The heuristic rule was introduced to eliminate the possible equipment redundancy of the configuration scheme from the upper and speed up the optimal configuration process. Finally, the proposed model was verified through a rural biogas-wind-solar integrated energy system in Fujian. The results have proved the plurality and superiority of the proposed optimal configuration and operation scheme.

Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives

Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

2024, 57(4):  14-24.  DOI: 10.11930/j.issn.1004-9649.202306117

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The reasonable planning and configuration of composite system in low-carbon park is of great significance for improving system energy efficiency and reducing costs and pollutant emissions. Firstly, based on the energy-demand fast prediction method for park and the composite energy system dynamic simulation platform, this paper proposed an optimal planning and configuration method for low-carbon park composite energy system, and established a hybrid optimization algorithm combining Hook-Jeff algorithm and particle swarm optimization. Secondly, by taking a multi-energy system with triple supply of cooling, heating and power system coupled with ground source heat pump, energy storage, and gas boiler in a typical low-carbon park as an example, a comparative analysis was made on the configuration results and optimization speed with different optimization algorithms, and a study was conducted on the impacts of different optimization objectives such as optimal comprehensive optimization objective and lowest whole life-cycle cost and energy consumption on the capacity optimization configuration results and typical daily operation situation. The results show that the proposed optimal configuration method and hybrid optimization algorithm can ensure the optimization capacity and accuracy with higher calculation performance. The energy system configuration results with optimal comprehensive evaluation objectives can take into account multiple factors such as system cost, economic operation, environmental impacts and low-carbon emissions, which can effectively realize the optimal energy form of low-carbon parks.

Optimization Scheduling of Integrated Energy System Scheduling in Industrial Park containing Electric Vehicles

Zhipeng LV, Zhenhao SONG, Lisheng LI, Yang LIU

2024, 57(4):  25-31.  DOI: 10.11930/j.issn.1004-9649.202402003

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The paper proposes an optimal scheduling strategy for the integrated energy system of an industrial park containing electric vehicle loads. First, based on the differences in load characteristics at different times and the differences in demand of electric vehicle users, a flexible charging and discharging model for electric vehicles is established. Second, the relevant hydrogen energy equipment model is established for the special hydrogen energy demand in the park. Then, the electric vehicle cluster, distributed photovoltaic and hydrogen equipment are integrated into the comprehensive energy system, and an integrated mathematical model is formed by the second-order cone relaxation process. Finally, the energy management and energy trading of the integrated energy system in an industrial park with solar photovoltaic and electric vehicle clusters are considered to further analyze its daily operation status. The results show that the proposed strategy can balance the operational benefits and risk-cost of the integrated energy system.

Optimization of Integrated Energy System Coupled with Power-to-Gas and Carbon Capture and Storage Equipment under Demand Response Incentive

Yuefen GAO, Chengbo YUN, Fanpeng KONG, Xuesong WANG

2024, 57(4):  32-41.  DOI: 10.11930/j.issn.1004-9649.202307056

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In order to fully mobilize user-side flexible load resources and take advantage of the low-carbon characteristics of hydrogen energy, this paper proposes an integrated energy system optimization method coupled with two-stage power-to-gas and carbon capture and storage (CCS) equipment under demand response incentive. Firstly, a hydrogen-based integrated energy system consisting of two-stage power-to-gas, CCS, hydrogen fuel cells, and hydrogen storage tanks is constructed. Secondly, combined with the conversion coupling relationship between load and energy, and the flexibility characteristics, the stepped demand response incentive mechanism is introduced, and adaptive optimization is conducted for three parameters including compensation base price, interval length and price growth rate. Finally, multiple scenarios are set up, and the multi-objective gray wolf algorithm is used to optimally solve the the supply-side, demand-side, and stepped demand response incentive mechanism of the system. The results show that the total cost of the system operation and CO₂ emissions are reduced with the proposed method.

New Energy

Research on the Optimal Configuration Method of New Energy and Flexible Regulation Resources Considering Carbon Emission Constraint

Hujun LI, Dong ZHANG, Mengxuan LV, Fangzhao DENG, Meng YANG, Bo YUAN

2024, 57(4):  42-51.  DOI: 10.11930/j.issn.1004-9649.202303046

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In the goal of the "Dual Carbon", with the rapid increase of the installed capacity of new energy, the demand for system regulation resources is also growing fast. Hence the coordination and optimization of the new energy and regulation resources is getting more attentions in building a new-type power system with high quality. This paper constructs an optimization model for new energy and regulation resources development with the objective of minimizing investment cost of additional units and operating cost of the system subject to carbon emission constraint and other constraints. Multiple development scenarios are set up with respect to different utilization rates of the new energy, and the operational economics of power system under each scenario are studied. Considering the carbon emission reduction target will be established and assessed for each province individually in the future, a provincial power grid in central China is taken as an example to verify the effectiveness of the proposed model, and research results and conclusions are provided at the end of paper.

Optimization and Simulation on Hydrogen Production System Using Water Electrolysis Powered by Renewable Energy

Siyu ZHANG, Ning ZHANG, Hongcai DAI, Changyou FENG, Zhuan ZHOU, Keping ZHU

2024, 57(4):  52-60.  DOI: 10.11930/j.issn.1004-9649.202306045

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Hydrogen produced from water electrolysis powered by renewable energy can help de-carbonize certain hard-to-abate sectors and promote synergy between different sectors and energy networks. As a matter of fact, the optimization of system configuration and operation scheme is vital to reduce the cost of hydrogen production and boost its economy competitiveness. In this paper, a planning optimization and production simulation model of water electrolysis system powered by renewable energy is proposed. The effects of critical components and related key factors, such as the wind power/photovoltaic-electrolyzer ratio, the electrochemical energy storage-electrolyzer ratio and electricity prices, on the levelized cost of hydrogen is analyzed in depth based on the typical configuration of hydrogen production system. Furthermore, two case studies representing typical areas in northwestern and southeastern China are carried out. The results show that the expense of electricity consumption is the major contributor affecting the economy of green hydrogen, which will drive these projects to be relocated to those places with plentiful renewable resources where the levelized cost of hydrogen is dropped to nearly 20 RMB/kg. In the future, the operation of green hydrogen projects will transit from in-grid mode to off-grid mode as system reserve backup if the electricity prices are roughly the same as that now. The research conclusions could provide theoretical guidance and important reference for the planning and construction of green hydrogen projects.

Power Supply Ensuring Measures and Implications of Foreign Countries' Power Systems with High Proportion of New Energy

Xiaoning YE, Caixia WANG, Qionghui LI, Chao YANG

2024, 57(4):  61-67.  DOI: 10.11930/j.issn.1004-9649.202310101

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With the global energy transformation and the rapid development of new energy, the power supply security issue of the power system with high proportion of new energy has become increasingly prominent and attracted focal attentions in some countries. Firstly, we analyzed in detail the power output characteristics of new energy and its challenges to power supply security in power balance and load support degree. Secondly, by selecting Germany, the United States, Japan and other typical countries with a relatively high proportion of new energy development, we made an in-depth study of their practical experience of ensuring the safe and reliable power supply in the power system with a high proportion of new energy from three aspects of policies and regulations, monitoring and early warning, dispatching and operation management. Finally, based on the actual situation of China's new power system construction, we proposed the implications for China's new energy development, which can provide a certain reference for China's power supply security.

Power Difference Feed-forward Oscillation Suppression Method for New Power System Based on Virtual Inertial Control

Xue WANG, Lin LIU, Qingdong ZHUO, Haipeng ZHANG, Ling YANG, Fangyuan XU, Yuchen CAO

2024, 57(4):  68-76.  DOI: 10.11930/j.issn.1004-9649.202312027

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To solve the problem of low inertia and weak damping in the new power system, virtual synchronous generator technology has attracted much attention. However, while the virtual synchronous generator provides inertia and damping for the system, it also causes the system to generate active oscillation when affected by disturbance, and it is easy to produce steady-state errors. Therefore, this paper proposes a power difference feedforward oscillation suppression method for a new power system based on virtual inertial control to optimize the control of a virtual synchronous generator. This effectively reduces the influence of active power and frequency generated under disturbance and improves the dynamic stability of the system. Meanwhile, the active closed-loop small-signal models of conventional control, differential feedforward control, and power difference feedforward control are built respectively, and the relevant parameter design methods are given. The effectiveness and superiority of the proposed strategy in solving dynamic oscillation and steady-state error problems are verified through simulation.

Transaction Decision-Making of Wind/Photovoltaic/Energy Storage Joint Participation in Spot Market under Renewable Portfolio Standards

Qunli WU, Xinyu ZHU

2024, 57(4):  77-88.  DOI: 10.11930/j.issn.1004-9649.202306053

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The parallel promotion of renewable portfolio standards (RPSs) and spot market construction leads to changes in the transaction decisions of wind power producers, photovoltaic producers, and energy storage power stations jointly participating in the spot market. This paper constructs a bi-level transaction decision-making model to solve and analyze the transaction decisions of wind/photovoltaic/energy storage jointly participating in the day-ahead energy and frequency modulation auxiliary service markets under RPSs. The upper level of the model solves the optimal transaction strategy of wind/photovoltaic/energy storage with the goal of maximizing the overall profit by considering the modulation within wind/photovoltaic/energy storage. The lower level realizes the joint clearing of the day-ahead energy and frequency modulation auxiliary service markets and the clearing of the green certificate market. Then, by using Karush-Kuhn-Tucker (KKT) conditions, the strong duality theorem, and other methods, the bi-level model is recast into a mixed-integer linear programming problem to be solved. Finally, an example is given to verify the effectiveness of the proposed model. The results show that the proposed framework and model in this paper can optimize the bidding strategies of wind/photovoltaic/energy storage. The introduction of the RPSs enriches the arbitrage means of wind/photovoltaic/energy storage, and the modulation within wind/photovoltaic/energy storage is more active. The changes of wind/photovoltaic penetration level and ratio of RPSs have an important influence on the transaction decisions of wind/photovoltaic/energy storage.

Development Status and Standardization of Electric Vehicle Charging Robots

Lei YANG, Lianming HUN, Guoqiang ZU, Shujun LI, Xinda LI, Junlong GUO, Yutao ZHANG

2024, 57(4):  89-99.  DOI: 10.11930/j.issn.1004-9649.202306108

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With the global push for carbon emission reduction, the rapid proliferation of electric vehicles (EVs) has brought significant attention to intelligent charging equipment such as EV charging robots in China and abroad. However, there remains a notable absence of systematic investigation encompassing the categorization, synthesis, summarization, and standardization of technologies associated with charging robots. An all-encompassing exploration of the development status and technological trajectories of EV charging robots worldwide is embarked upon, covering facets such as structural design, recognition and localization, compliant control, and control systems. Moreover, a taxonomy is proposed that encapsulates prevailing robots, distilling their features and applicable contexts. Subsequently, an analysis of existing standards in the realm of EV charging robots is presented. This analysis gives rise to requisites for standards including terminologies, classifications, and general technologies, thus culminating in the formulation of a robotic standard framework. Finally, insights into the application and prospects of EV charging robots are unveiled across five dimensions: automation, intelligence, scalability, multi-functionality, and interconnectivity. This exploration extends to the potential utility of EV charging robots in realms such as autonomous driving, automated parking, and harmonious vehicle-grid interactions.

Day-Ahead Probabilistic Prediction Model for Photovoltaic Power Based on Combined Deep Learning

Yan GAO, Hanbin WU, Jixin ZHANG, Huaming ZHANG, Pei ZHANG

2024, 57(4):  100-110.  DOI: 10.11930/j.issn.1004-9649.202306080

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To accurately quantify the uncertainty in the predicted photovoltaic (PV) power in complex scenarios, a short-term probabilistic prediction method for PV power based on a combination of temporal convolutional networks-attention mechanism-long short-term memory networks is proposed in this paper. Firstly, mete-orological factors strongly correlated with PV power are selected based on multiple correlation analysis methods. Then, a combined deep learning prediction model is built based on the feature extraction capability of the temporal convolutional network and the temporal feature modeling capability of the long and short-term memory network, combined with the attention mechanism and quantile regression. Finally, a kernel density estimation method is used to generate a continuous probability density function. The cases of actual centralized and distributed PV plants are analyzed, and the results show that compared with long short-term memory networks, temporal convolutional networks, temporal convolutional networks-attention mechanism, and temporal convolutional networks-long short-term memory networks, the proposed method can improve the performance of probability density prediction while ensuring the optimal prediction interval.

Charging and Discharging Strategies of Independent Energy Storage for Distribution Grid Side Considering Distributed PV Carrying Capacity

Yu ZHANG, Xinchi WEI, Kaihui FENG, Shanshan SHI, Zihan MENG, Yuan LIANG

2024, 57(4):  111-117.  DOI: 10.11930/j.issn.1004-9649.202305016

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In the context of carbon peaking and carbon neutrality goals and new power system construction, China’s distributed photovoltaic (PV) development accelerates. Areas with a high proportion of distributed PV access are prone to grid voltage rise over the limit, reverse tide equipment overload, and other problems, affecting the distribution grid carrying capacity with the distributed PV access. This paper fully considers the regulating role of independent energy storage on the distribution grid side and proposes an optimal configuration of independent energy storage and charging/discharging strategy for improving the carrying capacity of the grid with distributed PV access. Specifically, the comprehensive cost effectiveness of the independent energy storage application of the distribution grid side based on the time-series tide and two-step iteration is considered, and the independent energy storage configuration capacity and charging/discharging control strategy are scientifically and reasonably determined based on the principle of the minimum system cost. The low-voltage distribution grid of a village is selected as a case study, and the effectiveness of the independent energy storage charging and discharging control strategy proposed in this paper is simulated and analyzed by the Distribution System Analysis and Optimization Platform (DSAP).

Power System

Static Voltage Stability Region Considering Limit Induced Bifurcation

Daobing LIU, Yue QI, Shichun LI, Miaosheng BAO, Yingying GUO, Juecen LI

2024, 57(4):  118-129.  DOI: 10.11930/j.issn.1004-9649.202304063

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With the widespread application of a high percentage of renewable energy in power systems, the volatility and randomness of renewable energy pose challenges for static voltage stability assessment of power systems. The static voltage stability region (SVSR) of power systems can comprehensively analyze and monitor the voltage stability of power systems. The key is to construct the stability region boundary quickly and accurately. To address the problems of large computational effort of the traditional continuous power flow method and nonlinear programming method, an SVSR boundary construction optimization model based on the topological properties of SVSR boundaries is proposed, in which the adjacent boundary points are directly calculated from known boundary points by a prediction-correction method based on the property that the boundaries are continuous and smooth. Based on this model, a limit induced bifurcation (LIB) identification method is proposed to construct the SVSR boundary considering LIB. Finally, the feasibility and accuracy of the proposed method are verified by case analysis.

Characteristics and Commissioning of the Collaboration Between the Min-Yue Back-to-Back HVDC Transmission System and SVG/HAPF

Xiao LEI, Ruiwen XU, Ningmin ZHENG, Decai LI, Shicheng LIU

2024, 57(4):  130-138.  DOI: 10.11930/j.issn.1004-9649.202306033

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HAPF (high voltage active power filter) and SVG (static var generator), which are specially used for filtering in large-capacity HVDC projects, are configured in the Min-Yue back-to-back HVDC transmission project to meet the filtering requirements and reactive power support on both sides of the converter station respectively. In this paper, according to the characteristics of the Min-Yue project, a complete live commissioning scheme of the HVDC system and a collaborative operation test scheme of HAPF, SVG and HVDC are proposed, which have verified the availability of the equipment and its compatibility with the HVDC system. In view of the SVG fault events in actual operation, the complex problems caused by multiple factors in the process of high voltage transient response of SVG are analyzed in depth, and according to the targeted optimization control strategy, a high voltage/low voltage/three-phase unbalanced transient control test scheme of single SVG equipment is proposed. And a system test scheme is also proposed to verify the overall control strategy of the whole process of SVG and HVDC system under SVG fault. The correctness and effectiveness of the optimization strategy are verified through field implementation.

Startup Method and Strategy for Bipolar LCC-HVDC System Used as Black-Start Power Source

Qingwei WANG, Zhibin LIU, Bingqi CHEN, Jikeng LIN

2024, 57(4):  139-150.  DOI: 10.11930/j.issn.1004-9649.202307082

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The scientific and reasonable black-start scheme is the most effective measure to cope with the power grid blackout, which can greatly accelerate the system recovery process, thus significantly reducing the losses of power system due to power failure. The bipolar LCC-HVDC system has the advantages of flexible regulation and large transmission capacity, while it has some difficulties as a black start source. This paper presents a new black start method for bipolar LCC-HVDC system used as the black start power source to restore the power supply of the passive receiving-end network, so as to speed up the the recovery process. Firstly, the problems for using bipolar LCC-HVDC system as a black start source and the corresponding addressing measures are presented. And then, the implementation processes for using the bipolar LCC-HVDC system as a black start power source to restore the power supply of the passive receiving-end network are presented in detail. The process includes two stages: the first stage realizes the pseudo-deicer mode startup of the bipolar LCC-HVDC system; the second stage realizes the transition from the pseudo-deicer mode to the restoration of power supply of the passive receiving-end network. The case study verified the effectiveness and validity of the proposed method. This method makes the bipolar LCC-HVDC system have the black-start capability, and utilizes the DC system to provide voltage and frequency support for system restoration of the receiving-end power grid.

Distribution Network Topology Identification Based on Finite Key Nodes and Wasserstein Distance

Yao ZHAO, Yongjiang CHEN, Kunhua JI, Yun WANG

2024, 57(4):  151-161.  DOI: 10.11930/j.issn.1004-9649.202303122

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Defining the distribution network structure is the basis for optimal power flow, safety assessment, network reconstruction and fault location of the distribution network. Aiming at the problem that the existing distribution network topology identification methods are poor in efficiency due to their topology identification achieved only through measurement data without combination of existing network structure parameters and power flow information, a distribution network topology identification method based on finite key nodes and Wasserstein distance is proposed. Firstly, the finite key nodes can be used to identify the topology when the subspace perturbation model is used to prove the topology change of the distribution network, and the concept of influence degree is introduced through the entropy method based hybrid K-Shell algorithm and the importance of nodes is obtained by the influence degree and the electrical distance between the nodes, thus determining the key nodes in the distribution network topology. Secondly, the nodes are clustered with the density-based noise application clustering algorithm through four characteristics of voltage, current, active and reactive power, and other nodes and key nodes are classified into nodes and key nodes. And then, the connection relationship between nodes is obtained with the Wasserstein distance, consequently obtaining the topology of distribution network. Finally, a case study of the IEEE 33 node and a residential area has verified the effectiveness of the proposed method. This method greatly improves the identification efficiency and accuracy of distribution network topology, and realizes the dynamic identification of distribution network topology.

Multi-feature Short-term Prediction of Power Load Components Based on VMD-SE

Bilin SHAO, Danyang JI

2024, 57(4):  162-170.  DOI: 10.11930/j.issn.1004-9649.202303085

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To improve the accuracy of power load prediction, a multi-feature short-term prediction method based on VMD-SE for power load components is proposed. Firstly, the variational modal decomposition (VMD) is used to decompose the original load into a series of modal components and residuals, and the decomposition level of VMD is determined by sample entropy (SE). Then the SE values of the original load and modal components are compared, and the original load series are reconstructed into stationary and fluctuating components to reduce the computational scale. At the same time, the Pearson correlation coefficient is used to screen feature variables and delete feature redundancy, and a support vector regression model (GWO-SVR) optimized by gray wolf algorithm and a long short term memory neural network are established to predict the stationary component and fluctuation component respectively. Finally, an experiment was conducted using the electricity load of an area in Xi'an from 2018 to 2020 as an example. The experiment proves that the accuracy of this model is as high as 94.7%, and the MAPE error is reduced to 2.98%, indicating good accuracy and applicability.

DC Overvoltage Suppression Strategy for MMC-MTDC Based on Bridge Arm Modulated Wave Adjustment

Maolan PENG, Lei FENG, Yu WANG, Liqing XU, Wei ZHAO, Chunyi GUO

2024, 57(4):  171-181.  DOI: 10.11930/j.issn.1004-9649.202311116

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Modular multilevel converter based multi-terminal DC transmission (MMC-MTDC) system can realize multi-source power supplies and multi-terminal power-receiving. Flexible in operation modes, it is thus an effective technical means to solve the problem of grid-access and accommodation of clean energy. However, when AC fault occurs at the AC side of the receiving-end system, the created surplus power of the system will lead to serious DC overvoltage. In view of this, this paper proposes a DC overvoltage suppression strategy for multi-terminal flexible HVDC system based on bridge arm modulated wave dynamic adjustment. The proposed strategy introduces DC voltage deviation control into the modulation wave of the converter valve bridge arm, dynamically adjusting the DC voltage reference value of the bridge arm modulation wave during transient periods, thereby reducing the number of sub modules invested in the bridge arm, and ultimately achieving the goal of suppressing DC overvoltage. In order to verify the effectiveness of the proposed control strategy, a four-terminal flexible HVDC transmission system for photovoltaic and hydropower transmission is built in PSCAD/EMTDC, and the parameter design method of the proposed control strategy is given. Finally, by setting different operating conditions for the receiving-end AC system, a comparative study is made on the DC overvoltage characteristics of the system after implementation of the proposed control strategy. The results show that the proposed control strategy can effectively suppress the DC overvoltage of the MMC-HVDC transmission system caused by the receiving-end AC-side fault.

A Competitive Trading Mechanism for Microgrid Group Considering Congestion Cost Allocation and Fair Distribution

Shanshan SHI, Ran FENG, Chen FANG, Shu LIU, Lirong DENG, Haojing WANG, Pu CHEN

2024, 57(4):  182-189.  DOI: 10.11930/j.issn.1004-9649.202306011

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As the locational marginal pricing mechanism is hard to guarantee the real bidding of productive microgrids, the market efficiency may be decreased as a result. Considering the frequent occurence of transmission line conges-tion, this paper proposes a competitive trading mechanism for microgrid group considering congestion cost allo-cation and fair distribution. Based on the Vickrey-Clarke-Groves (VCG) theory, a payment model that promotes the real bidding of microgrids is proposed. Since the inherent problem of the VCG mechanism is the budget im-balance, and the existence of congestion in the system worsens this imbalance, this paper proposes a method to deal with the system budget imbalance based on the responsibility sharing method, in which the congestion cost is shared according to the impact of microgrid on the congestion, and the remaining system budget imbalance excluding the congestion cost is shared among consumption-oriented microgrids. The simulation results have ful-ly verified the effectiveness of the proposed mechanism.

Design and Application of Smart Distribution Station Area Based on Intelligent Fusion Terminal with Cloud-Edge Coordination

Weiming CHEN, Jinyu CHEN, Yuanliang FAN, Han WU, Zewen LI, Guangda WANG, Yiran LI

2024, 57(4):  190-199.  DOI: 10.11930/j.issn.1004-9649.202303110

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Intelligent fusion terminal is the core management unit and edge computing tie of smart distribution station area in power distribution Internet of Things (IoT). In order to enhance the practical application of the intelligent fusion terminal in smart distribution station areas, a design method for practical application of smart distribution station area is proposed based on the cloud-edge coordination of the intelligent fusion terminal. Three application cases of low-voltage topology automatic generation, power transmission topology verification, and available capacity analysis are introduced in theory and practice, and the design and its application of the three cases in three levels, including intelligent fusion terminals, distribution station master areas, and mobile devices are elaborated to enhance the intelligence and practicality of distribution station areas. The design and its application can provide a reference for the practical application of the intelligent fusion terminals in distribution IoT with cloud-edge coordination.

Prediction Method for Carbon Storage in Substation Based on Uncertain Parameters

Siyang CHEN, Li HAN, Jizhong FANG, Wuhang DING, Cheng CHENG, Wen LI, Yuan ZHANG, Yong QIAN

2024, 57(4):  200-210.  DOI: 10.11930/j.issn.1004-9649.202311078

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The SF₆ gas volume data from the PMS system is incomplete and contains significant errors, rendering it inadequate for power grid enterprises to calculate carbon reserves and formulate carbon planning for future substations. To address this problem, this paper studies the carbon storage accounting method for substations, taking into account buses and circuit breakers. The input parameters of the neural network are selected using the MIC method based on the field measured data in Ningxia grid, and three neural network models (GA-BP, PSO-BP, and HPO-BP) with six input parameters are developed. The verification results indicate that the HPO-BP neural network model outperforms the other two models in evaluation index and prediction results with a relative error of 6.28%, and it can accurately calculate the SF₆ gas volume of circuit breakers. Additionally, considering the parameter uncertainties, the linear relationship between different parameters is analyzed using the PCCs method, and a three-input-parameter HPO-BP neural network model is constructed, yielding a relative error of 7.69% for the prediction results. Concurrently, the ergodic output mode is examined to generate estimated SF₆ gas volume data for multiple groups of circuit breakers under uncertain parameter conditions. The total SF₆ gas volume of the substation is determined using the cumulative sum method, consequently quantifying the total carbon storage of the substation, thereby offering data support for power grid enterprises to accomplish the objective of "double carbon".

Calculation of Transient Stability Limit Based on Convolutional Neural Network

Qihe LOU, Rongsheng LI, Jie TAN, Tiejiang YUAN

2024, 57(4):  211-219.  DOI: 10.11930/j.issn.1004-9649.202301008

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Current procedures to calculate transient stability limit of interface tie line power transfer, using either time domain simulation method or direct method based on Lyapunov stability theory, are very time-consuming and complex. In view of this problem, a new method to compute transient stability limit of interface power transmission is proposed based on convolutional neural network. Firstly, the system operation data and the experimental simulation data are combined together to formulate the characteristic attributes of the transmission interface. Then certain key features of the transmission interface are selected as the input layer vector of the neural network. And next the nonlinear mapping relationship between the key features of the system and the transient stability limit of interface power transmission is constructed after multiple rounds of training processes. Finally, the reliability and effectiveness of the proposed calculation method are verified by case studies of IEEE14 bus system.

Refined Diagnosis Method for Disconnected High-Resistance Grounding Faults in Medium-Voltage Distribution Lines

Peng ZHENG, Pengcheng HAN, Guodong WANG, Ying LOU

2024, 57(4):  220-228.  DOI: 10.11930/j.issn.1004-9649.202306046

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Multiple voltage drops or abnormal currents may occur in the power system, resulting in significant deformation and fluctuation of fault signal characteristics related to the medium voltage DC distribution network, exceeding the normal fluctuation range, leading to a decrease in the refinement of fault diagnosis. A refined diagnosis method for high resistance grounding faults in medium voltage distribution lines has been proposed. On the basis of constructing a high resistance grounding resistance model, the wavelet energy moment algorithm is used to obtain the characteristics of high resistance grounding faults in medium voltage distribution lines. The extracted fault features are input into the least squares multi-level support vector machine to achieve precise diagnosis of high resistance grounding faults in medium voltage distribution lines. The simulation results indicate that the difference in fault phase voltage waveform obtained by the proposed method is less than 2.3%; The similarity of fault phase current waveform is higher than 98%; The diagnosis time is relatively short, and the highest recognition rate during fault diagnosis can reach 98%, with an average recognition accuracy of 95%; The convergence value reaches 0.97. From this, it can be seen that the proposed method has strong anti-interference performance and can accurately identify high resistance grounding faults when photovoltaic energy is connected to medium voltage distribution lines, ensuring stable operation after photovoltaic energy is connected to medium voltage distribution lines.