Table of Content

28 September 2024, Volume 57 Issue 9

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Special Contribution

Analysis of Carbon Peaking in Power Sector and its Impact on Promoting Whole-Society Carbon Emissions Reduction

Yuanbing ZHOU, Shining ZHANG, Fangxin HOU, Hongtao REN, Pengfei XU

2024, 57(9):  1-9.  DOI: 10.11930/j.issn.1004-9649.202405093

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The carbon emissions from the power sector account for over 40% of the total carbon emissions in the energy sector, making it the primary battleground for emissions reduction in the energy sector. Against the backdrop of the whole society striving to achieve carbon peaking by 2030, the timing of power sector's carbon peaking is crucial for the end-use sectors and whole-society to achieve carbon peaking. Firstly, an analysis was conducted on the temporal relationship between the power sector's carbon peaking and the carbon peaking of the whole society and other sectors in countries that have already achieved carbon peaking. Secondly, theoretical derivations were made regarding the conditions that the power sector's carbon peaking needs to meet and the proportional requirements of non-fossil fuel power generation under different scenarios. Finally, a quantitative analysis was carried out on the impact of electricity substitution on emissions reduction in the end-use sectors and the whole society. The study indicates that the decline rate of carbon intensity in power production is a crucial constraint determining the power sector's carbon peaking. Under the baseline scenario that power generation reaches 13 TW•h in 2030, the proportion of non-fossil fuel power generation needs to reach 56.3%, which implies that the annual increase in newly installed capacity of wind and solar power should exceed 240 GW from 2023 to 2030 so that the power sector can achieve carbon peaking before 2030. The promotion of electricity substitution for emissions reduction in the whole society is influenced by the proportion of non-fossil fuel power generation in the total power generation. Only when the proportion exceeds a certain critical value can the synchronous emissions reduction in the end-use sectors and the whole society be achieved.

Cross Domain Attack Threats and Defense Against Power Infrastructure

Two-stage Detection Method for DC Microgrid False Data Injection Attack Based on Deep Learning

Lei TAO, Pingping LUO, Jikeng LIN

2024, 57(9):  11-19.  DOI: 10.11930/j.issn.1004-9649.202311112

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A direct current (DC) microgrid is a cyber-physical information system that is susceptible to network attacks in the process of information transmission. Attackers can impact the security of the microgrid system by injecting false data into the information channel. Detecting and correcting false data injection attacks can enhance the security of the microgrid system operation. To address this issue, a two-stage false data injection attack detection method is proposed based on convolutional neural network (CNN) and long short-term memory (LSTM) combined with maximum information coefficient (MIC). Firstly, the CNN is used to extract the temporal features from the time series data of the DC microgrid operation. And the LSTM model, combined with the temporal features extracted by CNN, is then used to predict the operating state of the DC microgrid. This predicted value is compared with the actual value to preliminarily determine the presence of false data in the system. Secondly, considering the potential false positive rate of the CNN-LSTM model, an MIC verifier is constructed to further determine the presence of false data in the system and restore the data. The rationality and feasibility of the proposed method were verified through Matlab simulation analysis of the DC microgrid.

FDIA Detection in Power Grid Based on Opposition-Based Whale Optimization Algorithm and Multi-layer Extreme Learning Machine

Lei XI, Yixiao WANG, Miao HE, Chen CHENG, Xilong TIAN

2024, 57(9):  20-31.  DOI: 10.11930/j.issn.1004-9649.202309029

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At present, the existing false data injection attack (FDIA) detection methods for cyber-physical power system can not precisely obtain the location of the attack due to its limited ability of feature expression. Therefore, this paper proposes a FDIA location detection method based on opposition-based learning whale optimization algorithm and multi-layer extreme learning machine (OWOA-ELM^ML). The proposed method not only extends the extreme learning machine into a multi-layer neural network to solve the problem of its limited ability of feature expression, but also introduces the whale optimization algorithm to optimize the number of neurons of the multi-layer extreme learning machine, and uses the opposition-based learning strategy to improve its convergence speed and detection accuracy so as to prevent the influence of randomly determining the number of neurons in each hidden layer on the generalization performance and location detection results of the detection method. Through a large number of simulation tests on IEEE-14 and 57-bus test systems under different scenarios, it is verified that the proposed method can automatically identify the exact position of the attacked system state through the historical data. Compared with other comparative methods, the proposed method has better precision, recall rate and F1 value.

Defense Methods for Adversarial Attacks Against Power CPS Data-Driven Algorithms

Weiping ZHU, Yi TANG, Xingshen WEI, Zengji LIU

2024, 57(9):  32-43.  DOI: 10.11930/j.issn.1004-9649.202312067

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The integration of large-scale power electronic devices has introduced a large number of strong nonlinear measurement/control nodes into the system, gradually transforming the traditional power system into a cyber physical system (CPS). Many system problems that were originally solved by model-driven methods have had to be analyzed using data-driven algorithms due to limitations such as dimensional disasters. However, the inherent flaws of data-driven algorithms introduce new risks to the safe and stable operation of the system, which attackers can exploit to launch adversarial attacks that may cause system power outages and even instability. In response to the potential adversarial attacks on data-driven algorithms in power CPS, this paper proposes corresponding defense methods from such three aspects as abnormal data filtering and recovery, algorithm vulnerability mining and optimization, and algorithm self interpretability improvement: abnormal data filter, GAN-based vulnerability mining and optimization method, data knowledge fusion model and its training method. The effectiveness of the proposed method is verified through case analysis.

A Moving Target Defense Strategy against Load Redistribution Attacks

Quanpeng HE, Wei LIU, Weiyong YANG, Xingshen WEI, Qi WANG

2024, 57(9):  44-52.  DOI: 10.11930/j.issn.1004-9649.202401005

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The load redistribution attack considers the actual equipment configuration and operation of the power system, and poses a threat to the safe and stable operation of the power system by tampering with load measurements. This paper proposes a moving target defense method based on topology control, which destroys the attacker's grasp of the power system information through transforming the system topology, thereby achieving the defense against load redistribution attacks and providing guarantees for the safe and reliable operation of the power system. Firstly, a bi-layer optimization model of load redistribution is established to analyze the attack strategy. Secondly, the optimization reconstruction mode of topology structure is analyzed to establish a network topology optimization model. Finally, the network topology optimization algorithm is combined with the state estimation to achieve moving target defense and testing of load redistribution attacks. The proposed method was tested in an IEEE 14 bus system, and it was proved that the proposed moving target defense method based on topological transformation can effectively defend load redistribution attacks and enhance the attack resistance of the power system.

A Non-intrusive Method for Enhancing the Security of Modbus TCP Protocol Based on Cloud-Edge Collaboration in Distributed Resources

Zheqiu HETU, Zidong XU, Xin CHE, Zhenyong ZHANG

2024, 57(9):  53-60.  DOI: 10.11930/j.issn.1004-9649.202401006

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The security problem of data transmission from smart edge devices in distributed resources (DR) brings hidden risks for power system. The Modbus TCP (transmission control protocol) is a commonly used communication method for edge devices, but its flawed security design makes the system vulnerable to cyber-attacks. In this paper, based on a review of the existing security methods, we analyzed their shortcomings under DR application scenarios, and proposed a non-intrusive Modbus TCP security enhancement method. The method adopts an architecture of cloud-edge collaboration, and uses the cloud platform of the power control center to manage access control principles, and deploys the actual access control module in the edge devices to restrict malicious behaviours through fine-grained access control combinations. Finally, based on the Modbus protocol reference guide, a DR application scenario was built for penetration testing. It was proved that the proposed method can effectively defend against the replay attacks and man-in-the-middle attacks in this scenario, and the time cost is within a hundred microseconds.

Defense Method for Smart Grid GPS Spoofing Attack Based on BiLSTM and Self-attention Mechanism Generative Adversarial Network

Hui WU, Ziwei ZOU, Fengming XIAO, Jie LIU, Chenpeng MIN, Zhuoqun XIA

2024, 57(9):  61-70.  DOI: 10.11930/j.issn.1004-9649.202311025

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Phasor measurement unit (PMU) plays a crucial role in smart grids, enabling precise synchronized acquisition of electric power data. Due to the use of the global positioning system (GPS) for time synchronization, the PMU is vulnerable to GPS spoofing attack (GSA), which impacts the normal data acquisition. The existing GSA defense methods have low restoration accuracy and require additional hardware costs. To address the aforementioned issues, this paper proposes a GSA defense method based on bidirectional long short-term memory (BiLSTM) network and self-attention mechanism generative adversarial network. Firstly, an improved WGAN-GP model is proposed to redesign the network architecture of the generator and discriminator, and the BiLSTM network and self-attention mechanism are incorporated into the generator and discriminator to enhance the model's generative performance and discriminative ability. Secondly, based on the proposed WGAN-GP model, a GSA defense model is constructed, which includes two crucial modules: an attack detection network and a data restoration network that are employed to detect the smart grid GSA and repair the compromised PMU measurement data, respectively. Finally, We simulated GSA attacks in the IEEE-39 bus system and validated the effectiveness of the proposed method on the corresponding dataset. The results show that compared to existing methods, the proposed approach outperforms in most performance indicators.

Design and Implementation of Cyber Range Testbed for E1 Channel of Power Stability Control System

Heqin TONG, Jianbing XU, Shizhe LIANG, Cheng MAI, Haibo XU

2024, 57(9):  71-79.  DOI: 10.11930/j.issn.1004-9649.202312098

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With the development of smart grid and trans-region stability control technology, the information communication and the power system is being coupled more closely, and the security risk caused by cyber-attack is becoming higher and higher. As a key measurement and control channel, the E1 channel of the stability control system plays an important role for the security of stability control system. Thus, it is of significance to conduct the attack and defense drills on a hardware-in-the-loop simulation platform to find the security risk of E1 channel of the stability control system. Firstly, a cyber range testbed was designed for the E1 channel of the stability control system based on the hardware-in-the-loop simulation technology, and the scheme of attack and defense drills on the designed testbed was briefly introduced. Then, through the testbed, we simulated a case of a cyber-attack on the E1 channel of an operating power stability control system to test its security risk and validate effectiveness of the designed testbed. Finally, we proposed several solutions to improve the security of the E1 channel, and made a perspective of the future application of the designed testbed.

Technical Economy, Planning and Operation, and Policy Mechanisms of Offshore Wind Power Hydrogen Production

Development & Thinking of Offshore Wind Power Based on Life Cycle Economic Evaluation

Li FENG, Lianmei ZHANG, Jiajia WEI, Changhong DENG, Guo LI, Jiayue YIN

2024, 57(9):  80-93.  DOI: 10.11930/j.issn.1004-9649.202308096

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At present, the research on economic evaluation of offshore wind power (OWP) is poor, while OWP urgently needs economic evaluation as the basis for its large-scale application. Based on the economy of OWP projects, this article firstly reviews the composition and development of offshore wind farms and analyzes 3 types and 6 development models of current OWP projects. Then the whole life cycle of OWP projects are divided into 3 stages, including initial investment, operation maintenance and retirement recovery, and the cost of each stage is analyzed and its respective mathematical model is established. Then, 6 economic indicators such as NPV are introduced to evaluate an OWP project for case study. Finally, the current progress and research deficiencies of OWP projects are summed up, which can provide a direction for future research and a support and reference for the more economical development of OWP.

Economic Analysis of Energy Transmission for Energy Island Based on Deep-Sea Offshore Wind Farms

Zhongqi LIU, Yao LIU, Jinming HOU

2024, 57(9):  94-102.  DOI: 10.11930/j.issn.1004-9649.202401031

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Deep-sea wind power has the advantages of rich resources, high utilization hours, and no occupation of land onshore, which is of great significance for promoting the realization of the "double carbon" goal. The offshore energy island with deep-sea wind power as the core can, through the integrated development model of "offshore wind power +", improve the comprehensive utilization rate of sea areas, enhance overall efficiency, and reduce development costs. Construction of the offshore energy island involves energy development technologies such as floating offshore wind power, energy comprehensive utilization technologies such as AWE, energy transmission technologies such as VSC-HVDC transmission and hydrogen pipeline transmission. This paper first introduces the overall composition of the energy island with the deep-sea wind power as the core, and then analyzes the transmission technologies applicable to large-scale energy transmission of the energy island. The cost of the energy island with 1000 MW floating offshore wind power through VSC-HVDC power transmission and the cost of hydrogen transmission through pipeline are calculated respectively, and the power transmission cost is compared with the cost of hydrogen transport. As the comparative analysis indicates, both the VSC-HVDC technology and the hydrogen pipeline transmission technology can be used as the energy transmission solutions for the offshore energy island. An innovative research is carried out on the economics of energy delivery for energy island. According to calculations, in 2023, 2030, and 2050, when the transmission distance is 100 km to 200 km, the economic performance of the VSC-HVDC solution is better than that of the hydrogen transmission solution. The cost and absorption capacity of the landing area need to be comprehensively considered before choosing the power transmission solution or the hydrogen transmission solution. It is predicted that in 2050, the comprehensive cost of different proportions of mixed power and hydrogen transmission for a distance of 100 km to 200 km offshore is between 0.18 yuan/kW·h and 0.27 yuan/kW·h, which is competitive compared with the cost of power transmission from new energy bases in the western and northern regions to the eastern region.

Optimal Allocation of Offshore Wind Power-Multiple Energy Storage System Considering Gas-Solid Two-Phase Hydrogen Storage Characteristics

Wenjin JIANG, Qiaomei LIU, Xiaodong YANG, Dingfei QUE, Yu SHEN, Xianan HUANG, Zhenhua LAI

2024, 57(9):  103-112.  DOI: 10.11930/j.issn.1004-9649.202308048

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Under the background of the implementation of "dual carbon" policy, the importance of developing renewable energy such as offshore wind power has been increasing. However, the volatility of wind power brings about safety problems to the system operation. Therefore, this paper proposes an offshore wind power-multiple energy storage system that takes into account gas-solid two-phase hydrogen storage in combination with various energy storage technologies, and the requirements of safe operation of offshore wind power system are met through allocation of energy storage capacity. Firstly, the model of offshore wind power-multiple energy storage system is constructed, and the system structure and the energy flow are described. Secondly, the hydrogen storage system, which includes gas-solid two-phase hydrogen storage, is introduced, and the principle of solid-phase hydrogen storage is expounded. Then, an optimal allocation model of offshore wind power-multiple energy storage system is developed. Finally, a simulation is carried out with typical weekly operation data, and the results show that the proposed system can improve the safety and economy of the offshore wind power systems.

Site Selection of Offshore Wind Power-Hydrogen Production and Refueling Ports Based on Empirical Mining and Hybrid Linguistic Approach

Ningbo HUANG, Jianwei GAO, Chuanbo XU, Xuanhua XU, Shutong ZHAO, Xunjie GOU, Xiaojing JIANG

2024, 57(9):  113-123.  DOI: 10.11930/j.issn.1004-9649.202403015

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To support the decision-making for site selection of offshore wind power-hydrogen production and refueling ports (OWP-HPRP), we propose a multi-attribute decision-making method using experience mining algorithm and hybrid linguistic terminologies. Initially, the crawler algorithm, TextRank algorithm, Word2Vec algorithm, and Louvain algorithm are used to facilitate the mining, ranking, word pairs construction, and clustering of historical empirical documents, and an experience mining based attribute set is thereby obtained. Secondly, the linguistic terminologies such as the duality-confidence linguistics, cloud models and real numbers are introduced to enable the accommodation of quantitative and qualitative data expressions and to solve the distortion problem in transformation of data set. Finally, a standardized formula is introduced to process the indicator data, and a comprehensive ranking result is thus obtained. The effectiveness of the proposed method was verified through a case study of site selection for an offshore wind power-hydrogen production and refueling port. The results show that according to both the qualitative and quantitative assessments, the site scheme A5 based on the technical scheme of centralized hydrogen production + liquid hydrogen + purchase/lease of ships is comprehensively optimal. The sensitivity analysis indicates that the technical scheme of gas hydrogen storage and transportation technology combined with shipping transportation has a good performance in technical maturity and economy.

Key Technologies of Urban Power Grid for New Power System

Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks

Chouwei NI, Yang CHEN, Xuesong ZHANG, Da LIN, Kaijian DU, Jian CHEN

2024, 57(9):  124-135.  DOI: 10.11930/j.issn.1004-9649.202311031

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The electric-thermo-hydrogen system (ETHS), a highly efficient and integrated energy supply system, has attracted widespread attentions. However, the explosive characteristics of hydrogen poses unique safety challenges. To ensure the safe and economical operation of ETHS, this paper proposes an optimal configuration method considering safety risks. Firstly, the safety of the ETHS is analyzed, and the working range and temperature of the electrolysis cells and fuel cell are constrained. Then, the pressure of the hydrogen storage tank is more accurately constrained using the non-ideal gas pressure formula of hydrogen, and the safety risk of the hydrogen storage tank is quantified using the TNT equivalent method. Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. The case study results demonstrate that with consideration of safety risks, the economy of the system can be improved through reasonable capacity design while effectively reducing system safety risks, which verifies the effectiveness of the optimization design method proposed in this paper.

Optimal Dispatching of Electric-Heat-Hydrogen Integrated Energy System Based on Stackelberg Game

Lingling TAN, Wei TANG, Dongqing CHU, Jingrui LI, Yumin ZHANG, Xingquan JI

2024, 57(9):  136-145.  DOI: 10.11930/j.issn.1004-9649.202310058

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The conflict of interest among entities in the integrated energy system (IES) is a challenge about operation decisions. An optimal scheduling model of electric-heat-hydrogen integrated energy system based on Stackelberg game is proposed. Firstly, an energy producer (EP) model is formulated which considers the full utilization of hydrogen energy. Secondly, the interaction of price information among EP, energy system operator (ESO) and load aggregator (LA) is analyzed. Considering the resource integration utility of load aggregators under demand response mechanisms, the payoff model of each entity in IES is established. Finally, a Stackelberg game model with ESO as the dominator, EP and LA as the followers is introduced. Genetic and quadratic programming algorithms (GA-QP) are used to solve the model. Taking a park-level IES in Northern China as an example, the effectiveness of this model in promoting the balance of interests among various entities is verified.

Polyhedral Uncertainty Set Based Power System Flexibility Quantitative Assessment

Donglei SUN, Xian WANG, Yi SUN, Xiangfei MENG, Yongchen ZHANG, Yumin ZHANG

2024, 57(9):  146-155.  DOI: 10.11930/j.issn.1004-9649.202404123

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With the continuous increase in the proportion of renewable energy sources such as wind and solar PV integrated into the power system, the rise in source-load uncertainty has exacerbated the demand for operational flexibility within the grid. To accurately quantify this flexibility demand and devise an optimization scheme that balances both flexibility and economy, a quantification and assessment methodology for power system flexibility is proposed, based on polyhedral uncertainty sets. Firstly, the volatility, uncertainty, and correlation characteristics of multiple photovoltaic power stations' outputs are quantified using polyhedral uncertainty sets. Subsequently, the net load fluctuation interval is analyzed, and a quantification model for power system flexibility demand is constructed. Secondly, an affine adjustable robust optimization model that incorporates flexibility demands is established based on affine strategies. This robust optimization model is then transformed into a mixed-integer linear programming (MILP) model for solution. Finally, the optimization results of the proposed model are compared under different uncertainty scenarios using a 6-node system and the IEEE 57-bus system, verifying the effectiveness of the proposed methodology in quantifying and assessing system flexibility demands.

Enhanced Kernel Ridge Regression and Ensemble Empirical Mode Decomposition Based Distribution Network State Estimation

Yumin ZHANG, Yongchen ZHANG, Pingfeng YE, Xingquan JI, Chunyou SHI, Fudong CAI, Yichen LI

2024, 57(9):  156-168.  DOI: 10.11930/j.issn.1004-9649.202401110

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Addressing the significant interference in the filtering accuracy of deep learning-based state estimation models caused by strong non-Gaussian noise in distribution network measurement information, an enhanced kernel ridge regression state estimation method based on ensemble empirical mode decomposition is proposed. Firstly, the ensemble empirical mode decomposition is utilized to filter out most of the noise data in the measurement information, ensuring the reliability of data for subsequent filtering. Subsequently, an enhanced kernel ridge regression state estimation model is constructed to establish a mapping relationship between measurement information and estimation residuals. By inputting the measurement information, the estimation results and estimation residuals can be obtained. Finally, numerical simulations are conducted on the standard IEEE 33-node system and a city-level 78-node system, demonstrating that the proposed method exhibits high accuracy and robustness under the interference of strong non-Gaussian noise.

Distribution Network Coordinate Operation Considering Net Load Uncertainty

Dongli JIA, Xiaoyu YANG, Keyan LIU, Xueshun YE, Zhao LI

2024, 57(9):  169-180.  DOI: 10.11930/j.issn.1004-9649.202402011

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Maximizing the consumption of renewable energy while ensuring the safe and economic operation of distribution networks has become an urgent issue. Firstly, the renewable energy output and load on the nodes are aggregated into net loads, and their uncertainties are described in the form of intervals. Meanwhile, the mapping of the regulation capacity in the system onto the nodes is described as intervals with optimizable endpoints, and the common part between the regulation capacity intervals and the net load disturbance intervals reflects the acceptable domain for net load disturbances at that node. Then, based on priority goal planning, a three-tier optimization model is constructed, aiming to maximize the acceptable domain of net load disturbances, minimize the total operational cost of the distribution network, and minimize voltage deviations, while considering the uncertainty of net loads. This results in an optimized solution that comprehensively considers the maximization of renewable energy consumption, reasonable operational costs, and minimal node voltage fluctuations, ensuring the safety, reliability, and economy of distribution network operation. Finally, the effectiveness of the proposed model and method is verified through a case study based on a modified IEEE 33-node distribution network.

Multiple Characteristics Criterion Based Incipient Fault Detection of Distribution Systems

Anning WANG, Rongqi FAN, Yang ZHANG, Jiachao LIU, Wei HU, Shimin ZHONG, Ke JIA

2024, 57(9):  181-193.  DOI: 10.11930/j.issn.1004-9649.202309031

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The fault characteristics of the new distribution system have changed significantly under the high proportion of new energy access, with variable operation modes and limited short-circuit currents. In this regard, arc-type early faults are the signs of short-circuit in the power system.The effective identification of early faults in advance can avoid the problem of short-circuit faults, which is difficult to jump off. Based on the equivalent model of early faults, the paper analyses the electrical quantity characteristics and temperature characteristics of the fault arc, and proposes an arcing high-resistance fault detection method that combines the current and temperature characteristics at the same time. The method integrates the speed of electrical signals and the high sensitivity and reliability of thermal signals, and then based on the composite characteristic quantity fault parameter identification criteria to detect the early faults. The effectiveness of the proposed method is verified comprehensively by simulation in PSCAD, field data and fault test in labs.

Power System

Evolution of Functional Investment Structure of Power Grid Infrastructure Suitable for New Power System

Rui ZHU, Qihe LOU, Xiaoling JIN, Chang LIU

2024, 57(9):  194-204.  DOI: 10.11930/j.issn.1004-9649.202309072

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The construction of new power systems involves the change in both physical form and production organization relationships. With a large amount of investment, how to ensure investment efficiency will be one of the key problems in the construction of new power systems. At present, great changes have taken place in the form of the power grid side, power supply side, and load side. Clarifying the change in investment structure from the perspective of functionalization is the key to discovering the change law of investment, guiding the efficient investment of funds, exploring and improving the investment efficiency of power grid infrastructure, especially unveiling the evolution law of functional investment structure. First of all, the key factors affecting the power grid infrastructure investment were identified through the system dynamics model, and the interrelation, mutual influence, and dynamic change relationship among the factors were further studied. On this basis, the system simulated the evolution trend of each investment function in the power grid infrastructure investment structure under key scenarios, so as to provide suggestions and data support for the medium-term and long-term power grid investment decision-making of enterprises, promote the optimization and upgrading of power grid infrastructure, and build new power systems with higher quality.

Coordinated Optimization and Operational Strategy for Multi-type Energy Storage in Regional Integrated Energy Systems

Mingfei GAO, Zhonghe HAN, Bin ZHAO, Peng LI, Di WU

2024, 57(9):  205-216.  DOI: 10.11930/j.issn.1004-9649.202311024

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To address the operational optimization issues of multiple heterogeneous energy in regional integrated energy systems, a coordinated operational optimization method for multi-energy storage systems aimed at multi-energy synergistic supply is proposed. Firstly, a coordinated operational optimization model based on multi-objective optimization was established for multi-energy storage systems by combining the architectural features of integrated energy systems with their operational requirements. And then, by taking into account three objectives of economy, environment, and energy efficiency, the model was used to optimize the operational parameters of systems by utilizing the improved multi-objective particle swarm optimization (MOPSO) algorithm in conjunction with the TOPSIS method. Finally, a case study was conducted using an actual regional integrated energy system in China, to explore the impact of different energy storage strategies on the system's operational performance and coordinated optimization effects. The research found that implementation of the coordinated optimization strategy for multi-energy storage systems can significantly enhance the system's performance in terms of economy, environmental protection, and energy efficiency. This study offers a viable solution for coordinated optimization of the multi-energy storage systems and synergistic supply of the multiple energies within regional integrated energy systems.

3D Reconstruction of Power Grid Facilities Based on Keyframe Extraction and Image Recognition

Zhiyong CHEN, Jinglin HAN, Yang LIU, Guangyi LI, Yu JIANG, Ruitian CAI

2024, 57(9):  217-223.  DOI: 10.11930/j.issn.1004-9649.202306018

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A digital reconstruction scheme for power grid facilities based on video keyframe extraction and image recognition is proposed. Shoot a video sequence of the facility to be reconstructed through a mobile homework terminal, extract key frames from the video, and use YOLOv5 network to recognize and extract anchor frames of power facilities to remove environmental background, constructing an image set; Then, based on the principle of motion recovery structure, 3D reconstruction is carried out, and an improved directional fast rotation algorithm is proposed to improve the accuracy of camera pose calculation. Thereby achieving the reconstruction of 3D models of power grid facilities; Finally, taking common transformers in the power grid as an example, it is verified that the proposed method can effectively complete the 3D model reconstruction of power facilities.

A Restoration Method for Distribution System Based on Projection of Multiple Microgrids

Shiyan ZHU, Yin XU, Jinghan HE, Ying WANG

2024, 57(9):  224-230.  DOI: 10.11930/j.issn.1004-9649.202405103

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The participation of microgrids in distribution system restoration can improve the restoration effects and thereby enhance the system resilience. A restoration method for distribution system with multiple microgrids is proposed, which considers the microgrids' privacy and restoration preferences, and can coordinate the power generation resources of the distribution network and microgrids. Firstly, a coordination mechanism for multiple microgrids to participate in distribution network restoration based on virtual nodes and virtual flow decomposition is established to effectively protect the privacy of microgrids. Subsequently, a projection-based critical restoration information-sharing method is proposed to solve the restoration problem, and the vertex search is used to quickly obtain the projection domain and realize critical information interaction. And then, a two-layer coordinated restoration framework for the distribution network and microgrid is proposed, in which the lower microgrid provides limited information including restoration preferences and feasible domain to the distribution network; the upper distribution network makes overall decisions and sends the tie-line power obtained by the decision to the microgrid, and the lower microgrid uses the tie-line power as the constraints to determine the internal load restoration. Finally, based on the constructed power distribution system with multiple microgrids, the effectiveness and advantages of the proposed method is verified.

Discharge Phenomenon of a 500 kV Double Tension Porcelain Insulator String

Yang CHENG, Lingzhi XIA, Lei NIU, Wei RUAN, Hao SUN, Xuanhe CAO, Shimin ZHANG

2024, 57(9):  231-237.  DOI: 10.11930/j.issn.1004-9649.202309036

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The mechanism of this phenomenon was studied with a double tension porcelain insulator strings in a 500 kV converter station. Experiments including resistance testing and cross-sectional staining were conducted, and a simulation model of double insulator strings was established to obtain the distribution pattern of the space electric field. The result shows that water vapor intrusion into the cement adhesive gap resulted in the resistance decrease of several insulators and the formation of 24 zero-value insulators (20 on the west side and 4 on the east side). The 122kV voltage difference between the strings was the main cause of the inter string discharge.

New Energy

Balanced Control Strategy of Distributed Energy Storage SOC Considering Line Impedance

Zhongran YAO, Liying SUN

2024, 57(9):  238-246.  DOI: 10.11930/j.issn.1004-9649.202311060

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Due to the uncertainty of distributed generation (DG) in islanding DC microgrids, it is necessary to add an energy storage unit for a supplement. In traditional droop control, the output current cannot be accurately distributed due to line impedance difference, which affects the balancing effect of the energy storage unit's state of charge (SOC). Besides, the convergence rate slows down as SOC decreases. Also, the influence of DG fluctuation on bus voltage is not considered. Therefore, an improved droop control strategy is proposed. By calculating the output current deviation, the authors introduce an integrator for the current deviation to eliminate the influence of the line impedance difference. Acceleration term and adaptive acceleration factor are also designed to increase the SOC balancing speed. When the DG fluctuates, the output current increment is adjusted to meet the load power balance and keep the voltage stable. The simulation results show that the SOC convergence error of the proposed control strategy is less than 0.1% when considering the line impedance. Convergence speed increases by 20% compared with the method referred, and the voltage drop is less than 3%.

Power Distribution Strategy of Multi-functional Energy Storage Power Station in Wind Farm

Gangling TIAN, Hongxin WU, Juan LI, Liuli ZHANG, Jia XIE, Aikui LI

2024, 57(9):  247-256.  DOI: 10.11930/j.issn.1004-9649.202308036

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With the increase in the proportion of new energy installed capacity, the modulation capacity of new energy stations such as frequency modulation and voltage modulation has been paid more and more attention. In view of the problems of primary frequency modulation, power smoothing, and coordinated control of voltage modulation for new energy stations equipped with energy storage, this paper used a clustering algorithm to obtain the energy storage to suppress fluctuating power requirements and set the standby power of frequency modulation for wind storage and voltage modulation for energy storage stations. Secondly, the residual active power for energy storage and the state of charge (SOC) were used to correct the active power of primary frequency modulation for energy storage. Then, based on the reactive power margin for energy storage and the emergency degree of voltage deviation, the reactive power-voltage sag coefficient was modified. Finally, to ensure the frequency modulation effect, the multi-function coordinated operation strategy of energy storage was proposed, involving fluctuation suppression by energy storage, primary frequency modulation, and voltage modulation. Based on Matlab/Simulink, simulation verification was carried out, and the simulation conditions of fluctuation suppression by energy storage and primary frequency modulation, fluctuation suppression by energy storage and voltage modulation, as well as the coordinated operation of the three functions were analyzed, respectively. The results show that the multi-function coordinated operation strategy proposed in this paper can promote the grid frequency, voltage, and SOC recovery under the condition of fluctuation suppression of wind power by energy storage.