Table of Content

28 May 2023, Volume 56 Issue 5

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Special Contribution

Analysis of Spatial and Temporal Variation Character of Climate Risks of Wind and Solar Resources in China

SUN Jingbo, WANG Yang, YANG Xiaofan, LU Zheng, HE Yuan, CHAO Qingchen

2023, 56(5):  1-10.  DOI: 10.11930/j.issn.1004-9649.202211009

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The proportion of renewable energy (represented by wind and solar energy) in the future energy structure of China should be substantially increased to achieve the goals of carbon peak and carbon neutrality. However, wind and solar power generation is largely affected by local climate conditions, with intermittent and volatile characteristics. In recent years, extreme weather and climate events have become more frequent and stronger and have shown concurrency, which seriously restricts the effective utilization of wind and solar resources. Therefore, the research on climate risks of wind and solar resources is of great theoretical and practical significance for improving the utilization of wind and solar resources and reducing the risks of renewable energy. This study quantitatively analyzes the spatial and temporal characteristics of scarce wind and light scenarios in China on the basis of a high-resolution database of wind and solar resources from 2007 to 2014. The analysis is based on aspects such as the degree, range, duration, and frequency of inefficient wind and solar output. The results show that the current distribution of scarce wind and light scenarios demonstrates prominent seasonal and regional differences. The climate risk of solar and wind resources mainly occurs in autumn and winter. The frequent scarce wind and light scenarios mainly occur in Xinjiang, Sichuan, and the middle reaches of the Yangtze River. This study could provide a scientific basis for future site selection of wind and solar power stations and regional renewable energy planning in China.

New Power Systems Under the Dual Carbon Target

Scheme Construction for Sending End DC Grids in Western China Under the Background of New Power System

LI Huiling, WANG Xi, GAO Jian, SONG Yunting

2023, 56(5):  12-21.  DOI: 10.11930/j.issn.1004-9649.202212102

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Under the background of new power system, China is facing the ‘West to East’ power transmission demand of large-scale renewable energy in the future, so it is necessary to plan the corresponding transmission modes. Based on the development scale of renewable energy in the west China after 2030, the installed capacities and geographical distribution of various types of power sources are determined, and the backbone structure of the ‘West to East’ transmission grid and road map are proposed, integrating the long-term sending end DC grids in western China and receiving end UVAC/UHVAC grids in central/eastern China. In order to meet the basic requirements of the new power system, such as safety, controllability, flexibility and efficiency, three VSC-HVDC based DC grid modes are constructed to realize the complementarity of multi-sources in western China and ensure the reliable supply of electric power. The quantity of main primary equipment under three modes is analyzed, and the overall reliability index of the sending end DC grids in western China is calculated. The three modes are comprehensively evaluated in terms of the quantity of equipment and the overall reliability index of the DC grids to determine the priority mode. Finally, referring to the Zhangbei flexible DC grid project, the technical and economic aspects of the optimal mode are analyzed to further verify the feasibility of the mode.

Research on Technical Standard System of New Distribution System Under Double-Carbon Strategy

WANG Jinli, LI Fengsheng, XIE Fang, ZHANG Yao, TIAN Ye

2023, 56(5):  22-31.  DOI: 10.11930/j.issn.1004-9649.202301023

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In the context of “carbon peaking and carbon neutrality”, the construction of a new type of clean and low-carbon power system with high penetration of renewable energies is moving forward at a fast pace, which has profoundly changed the behavior and functional roles of power distribution system. However, the current standard system is hardly capable of meeting the requirements of the development of distribution network due to the absence of corresponding critical supportive standard in addition to its lack of compatibility, coordination and integrity in the entire power distribution business. By taking the technical development and business needs into full consideration, this paper puts forward the principles of systematic, coordinated, dynamic and prospective standard system construction. Based on the theory of multidimensional model, the snowflake multidimensional structure model is established, which lays the foundation for the information management of standard system. With the power distribution as the main technical direction, a multi-level standard architecture covering the whole life cycle is also designed. Finally with regards to the key technical fields, this paper analyzes the requirements for standards and implements the planning and layout of key standards, so as to provide effective standards and direction guidance for the promotion of the green and low-carbon transformation of smart distribution network.

Robust Optimal Frequency Regulation Control Strategy for Pumped Storage in Grid-Connected Wind Power Systems

YOU Wenxia, LIU Bin, LI Shichun, LI Wenwu, ZHA Zijian, ZHANG Pengyu

2023, 56(5):  32-40.  DOI: 10.11930/j.issn.1004-9649.202303027

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To solve the primary frequency regulation problems of power system brought about by short-time wind power fluctuation and load fluctuation, a robust optimal frequency regulation control method is proposed for pumped storage units in the power system with integration of wind power. By establishing the overall state space equations of the power system with the pumped storage units as the primary frequency regulation power source, the general robust control problem is converted into an optimal robust control problem with the wind power output fluctuation and load fluctuation as the disturbance variables in the form of weight functions. The mutation harris hawks optimization grey wolf optimizer (MHHOGWO) is applied to select the optimal parameters of the weighting matrix reflecting the fluctuation characteristics of wind power output and load, and to solve the robust controller with the lowest frequency deviation of the system. The simulation results show that the proposed method can effectively reduce the frequency deviation of the whole power system caused by external disturbances, and the regulation response performance of pumped storage units to short-time external power fluctuations is also improved.

Hierarchical Progressive Optimization Algorithm for Day-Ahead Planning of Provincial Power Grid with Multiple Pumped Storage Power Stations

ZHOU Yunhai, ZHANG Zhiying, XU Fei, GUO Qi, LIU Liande, JIA Qian

2023, 56(5):  41-50.  DOI: 10.11930/j.issn.1004-9649.202212044

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The day-ahead planning of the provincial power grid considering the optimization of pumped-storage unit commitment can be expressed as a large-scale mixed-integer linear programming problem, which is difficult to solve directly. Hence, the main factors affecting the consumption of new energy, namely, network constraints and the system’s peak-shaving capacity constraints, are decoupled, and a hierarchical progressive model for day-ahead scheduling optimization is constructed. The model converts the original problem into large-scale linear programming and small-scale integer linear programming. The first layer of the model does not consider the optimization of the pumped-storage unit commitment. The output of the pumped storage power station is relaxed as a continuous variable, and the system network constraints are accurately modeled to minimize the sum of load shedding, wind and photovoltaic power discarding, and unit operating costs. Then, 96-point output curves of each unit in the system are preliminarily obtained. The second layer considers the optimization of the pumped-storage unit commitment. The maximum possible output of new energy units is based on the preliminary results of the first layer. The wind, photovoltaic, thermal power and conventional hydropower units are all equivalent to one unit separately. The optimized pumped-storage unit commitment is obtained without the consideration of network constraints. Finally, the determined pumped-storage unit commitment is brought back to the first layer for back substitution correction, and the 96-point output curve of each unit is calculated. The proposed model has been applied to a provincial power grid, and the correctness and practicability are verified by the actual operation data.

Bi-level Optimization Method for Bidding Strategy of Power Suppliers Considering Energy-Consuming Right

XUE Guiyuan, WU Yin, ZHU Xiaojun, TAN Jian, MING Hao

2023, 56(5):  51-61.  DOI: 10.11930/j.issn.1004-9649.202209087

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Energy-consuming right trading is an important way to control total energy consumption and improve energy utilization efficiency. With the promotion of the energy-consuming right market, power generation enterprises are not only influenced by the revenue of the electricity energy market, but also constrained by the total energy consumption when formulating their generation plans and bidding strategies. Aiming at the coupling mechanism of electricity market and energy-consuming right market, this paper proposes a bi-level optimization method for bidding strategy of power generation companies considering the constrains of energy-consuming right quotas according to the energy consumption intensity of different power generation companies. Firstly, the interaction between the electricity market and the energy-consuming right market is analyzed, and the relationship between power generation companies’ offers in the energy market and the energy-consuming right quota is constructed with the Stackelberg game and the Gounod model. Secondly, based on the constrains of energy-consuming right quotas and total energy consumption, a bi-level optimization model is established for bidding strategy of power generation companies considering the constrains of energy-consuming right quotas, in which the upper level takes maximizing power generation companies’ revenue as the objective, and the lower level consists of the model of electricity market clearing and energy-consuming right market clearing. The KKT (Karush-Kuhn-Tucker) condition is used to transform the bi-level optimization problem into a MPEC problem for solution. Finally, a case study is conducted, which shows that the proposed model can help to improve the revenue of power generation companies and encourage them to reduce energy consumption.

Optimization Strategy of Multi-microgrid Cooperative Operation Considering Carbon Trading and Renewable Energy Uncertainties

ZHAO Jun, ZHANG Min, ZHANG Shifeng, YANG Qi

2023, 56(5):  62-71.  DOI: 10.11930/j.issn.1004-9649.202209050

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Vigorously developing renewable energy and continuously promoting carbon emission reduction have become important development directions of the power system. Since the current power system under the carbon trading mechanism does not fully consider the interest interaction between multiple entities and renewable energy uncertainties, this paper proposes a multi-microgrid cooperative operation optimization strategy considering carbon trading and renewable energy uncertainties. Firstly, the carbon quota and carbon trading mechanism are considered, and the microgrid model is established. The chance constraint method is adopted to consider renewable energy uncertainties. Then, according to the energy interaction mechanism between microgrids, the multi-microgrid cooperative operation model is established by using Nash bargaining theory and further decomposed into two sub problems that can be easily solved, namely, the multi-microgrid system revenue maximization and the profit distribution. The alternating direction multiplier method is used for distributed solutions to fully protect the privacy of each entity. Finally, the simulation results show that the proposed strategy can effectively reduce the carbon emissions of the system and improve the operating efficiency of each entity and have certain robustness.

Electric Vehicle Charging Demand Low Carbon Optimization in Traffic-Grid Coupling Networks Towards “Dual Carbon” Goal

YE Yujian, YUAN Quan, TANG Yi

2023, 56(5):  72-79.  DOI: 10.11930/j.issn.1004-9649.202209038

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The transportation and electricity systems are two major parts of global fossil energy consumption, and are also the important targets for optimization under the “dual carbon” goal. Electric vehicles (EV) have the nature of both transportation and electricity-use, and feature zero on-road carbon emissions, while the upstream generation carbon emissions associated with EV charging demand are still accountable. It is therefore urgently needed to reduce the carbon emissions of the whole system through optimizing the EV charging loads. In this context, this paper proposes an EV charging demand low carbon optimization method in traffic-grid coupling networks towards the “dual carbon” goal. Firstly, the EV driving flows and their charging behavior in the coupling networks are modeled to obtain the aggregated EV charging loads. Then the carbon emissions flow is traced according to the optimal power flow results of grid. Given the above-mentioned model, the optimization problem is solved based on the simulated annealing algorithm. Under the circumstance of not sacrificing the charging demand of EV users, part of the charging power supported by thermal units will be transferred to renewable energy resources through temporal-spatial redistribution of charging loads, subsequently reducing the total carbon emissions of the coupling networks while improving the local consumption of renewable energy resources. Finally, case studies have demonstrated the effectiveness of the proposed low carbon scheduling method.

Optimal Scheduling Strategy for Micro Energy Internet Under Electric Vehicles Aggregation

AN Jiakun, YANG Shuqiang, WANG Tao, HE Chunguang, ZHANG Jing, YUAN Chao, DOU Chunxia

2023, 56(5):  80-88.  DOI: 10.11930/j.issn.1004-9649.202211034

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With the continuous access of renewable energy to the power grid, more energy storage equipment is required to reduce the peak-to-valley difference, which greatly increases the power generation cost. Since electric vehicles aggregation has similar load characteristics to that of energy storage, its active participation in energy optimization scheduling of energy Internet will reduce the cost of energy storage equipment, subsequently improving the economic benefits of micro energy Internet. To this end, a micro energy Internet optimization scheduling strategy under electric vehicles aggregation is proposed. Firstly, based on the electric vehicles load clustering analysis with affinity propagation (AP) data mining technology, a short-term prediction method for electric vehicles is proposed based on the extreme learning machine prediction model. Furthermore, an optimal scheduling strategy for micro energy Internet under electric vehicles aggregation is proposed. The electricity tariff is used to incentivize the orderly charging of electric vehicles to reduce the peak-to-valley load difference, which in turn reduces the system generation cost. Finally, simulations are conducted to verify the effectiveness of the proposed optimal dispatching strategy.

Modeling and Robust Optimal Dispatch of Rural Integrated Energy System Considering PV-Hydrogen-Methane Energy Storage Characteristics

WANG Ruiqi, WANG Xinli, GUO Guanghua, ZHANG Yuhang, ZHOU Haini, ZHOU Qi

2023, 56(5):  89-98.  DOI: 10.11930/j.issn.1004-9649.202208024

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This paper aims to investigate the dispatch role played by renewable energy hydrogen production and biogas fermentation in the rural integrated energy system. Firstly, based on the biogas fermentation kinetics model and thermal load characteristics, we constructed an electricity-heat-cold-gas integrated energy system model, which consists of PV hydrogen production, combined heat and power generation, biogas fermentation and energy storage. Then, we established a two stage robust optimization based day-ahead dispatch model with the goal of minimizing daily operation cost, and obtained the day-ahead dispatch plan under the worst scenario by solving the model with column-and-constraint generation (C&CG) algorithm. Moreover, we finished the intra-day dispatch in light of short-term forecasting value of PV power and electric load, realizing the stable and economic operation of the integrated energy system. Finally, a case study was conducted on a rural agricultural park integrated energy system, which indicates that the PV hydrogen production and biogas fermentation have energy storage characteristics and can make contributions to alleviate “source-load” uncertainty, and are proved to have a certain economic value.

Power System

Heat Pump Temperature Trajectory Planning Algorithm for Bus Voltage Sag Suppression

ZHAO Yangyang, LIU Lan, ZHAO Wei, ZENG Shuang, LIANG Anqi, WANG Hanqiu, MA Kai

2023, 56(5):  99-107.  DOI: 10.11930/j.issn.1004-9649.202210013

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The PEDF (photovoltaics, energy storage, direct current and flexibility) micro-gird can make full use of the building’s own photovoltaic energy and thermal inertia storage system. However, excessive heat pump load will lead to a serious voltage sag at the DC bus, causing a great challenge to the stable operation of the DC micro-grid system. Therefore, this paper proposes a temperature trajectory planning algorithm that can suppress transient dc bus voltage sag. Based on the heat pump’s own load management in the process of its temperature regulation, a joint model is firstly constructed to analyze the mechanism of bus voltage sag, with consideration of the temperature rise process of buildings, the cooling/heating efficiency of heat pump and the electromagnetic performance of drive motors. And then, a Chebyshev polynomial-based thermal transition strategy is proposed, which integrates the thermodynamics, human comfort and heat pump performance constraints. Finally, the gradient optimization method is introduced to solve the optimal temperature trajectory planning curve, and comparative simulation is conducted. The simulation results show that the proposed algorithm can significantly suppress the transient sag of DC bus voltage in the process of heat pump temperature regulation, which are well suited to the smooth control and improving stability of building’s DC microgrid system.

Phase Identification of Low Voltage Distribution Network Based on t-SNE Dimension Reduction and Affinity Propagation Clustering Algorithm

LIU Shoucheng, WANG Chun, ZOU Zhihui, CHEN Jiahui, ZHOU Han, LIU Wei, ZHANG Xu

2023, 56(5):  108-117.  DOI: 10.11930/j.issn.1004-9649.202211004

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The widespread popularity of smart meters and the establishment of advanced measurement infrastructure (AMI) provide a large amount of monitoring information and measurement data for the analysis of the operation of distribution networks, while the change of phase information of users in the station area brings difficulties to the accurate understand of the operation of the station area. Aiming at the problem of phase recognition of users in the station area, a phase recognition method is proposed based on t-distributed stochastic neighbor embedding (t-SNE) feature extraction and affinity propagation (AP) clustering algorithm of user voltage data. Firstly, the extracted user’s voltage data is processed by Z-score data standardization, and the data features are extracted by t-SNE dimensionality reduction. And then phase identification for the user is made with radial propagation clustering algorithm. Two districts in a city are selected for case study. The recognition effects of different recognition methods are compared using evaluation indicators, and the effects of different acquisition frequencies and different measurement errors on the recognition effects are analyzed. The accuracy of the proposed method is verified by the actual cases, which shows that the proposed method can effectively solve the problem of user phase identification in the station area.

Home Load Optimization Scheduling Strategy Based on Improved Binary Particle Swarm Optimization Algorithm

ZHANG Li, LIU Qinglei, ZHANG Hongwei

2023, 56(5):  118-128.  DOI: 10.11930/j.issn.1004-9649.202207079

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In order to reduce the cost of household electricity consumption and improve the local consumption rate of residential photovoltaic power generation, a home load scheduling strategy is proposed based on real-time control of energy storage charging and discharging behavior. Firstly, the household loads are classified and a scheduling model is established with the objectives of lowest electricity cost, smallest carbon emission and largest comfort; secondly, based on the real-time photovoltaic output and peak-valley time-of-use electricity price, a scheduling strategy is proposed to meet the household load electricity demand through controlling the charging and discharging of energy storage; finally, the proposed model is simulated and solved using the scenario analysis method and hierarchical multi-strategy learning improved binary particle swarm optimization algorithm (HLSBPSO). The results show that the proposed strategy and algorithm can reduce the user's electricity bill by 49.2% and increase the comfort by 67.9%, which can provide a new theoretical support for the safe and economical operation of household photovoltaic power generation.

Online Self-Healing Scheme of Distribution Network Based on Mixed Integer Linear Programming

LI Tiecheng, ZHANG Weiming, ZANG Qian, WANG Xianzhi, REN Jiangbo, ZHOU Kun

2023, 56(5):  129-136.  DOI: 10.11930/j.issn.1004-9649.202212002

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The existing distribution network self-healing schemes cannot meet the online requirements. In this regard, an online distribution network self-healing scheme based on mixed integer linear programming is proposed. First, we build a centralized 5G communication network architecture to solve the communication obstacles implemented by the self-healing solution. Secondly, a fault location model and a power supply recovery model based on mixed integer linear programming are respectively constructed to effectively solve the problem that the self-healing calculation time is too long when the scale of the distribution network is large. Finally, the fault location and power supply restoration are integrated into a self-healing model. After a fault occurs, only one self-healing operation is required to issue fault isolation and power supply restoration commands at the same time. The distribution network example shows that the solution speed of the fault location model and power supply recovery model based on mixed integer linear programming is significantly improved. Under the proposed 5G communication architecture, the proposed distribution network self-healing scheme can meet the online self-healing requirements.

Review on Failure Mode and Mechanism of Press-Pack IGBT and Thyristor Devices

LUO Haoze, CHEN Zhong, YANG Wei, XIE Jia, HU Di, GUAN Weiping

2023, 56(5):  137-152.  DOI: 10.11930/j.issn.1004-9649.202210121

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High voltage and large capacity press-pack insulated gate bipolar transistor (IGBT) devices and thyristor devices are the core devices in high-voltage DC transmission projects, which are of great significance for the efficient use of energy. The reliability of IGBT and thyristor has become a key problem for the stable and reliable operation of electrical equipment and even the entire power system. Firstly, starting from the traditional packaging structure of press-pack devices, this paper introduces the spring multi-chip packaging and convex multi-chip/single-chip packaging of press-pack devices, and compares the performance of three packaging structures. Then, the package-level failure mode and mechanism of press-pack devices are investigated, and the results show that the mismatch of the thermal expansion coefficient is the main reason for package-level failure. At the same time, the chip-level failures of IGBT and thyristor are also investigated, and it is found that electrical overstress is the main reason for chip-level failures. Thirdly, the new packaging structure and technology of press-pack devices are briefly introduced. Finally, future research focus on press-pack devices are discussed.

Fault Simulation of High-Voltage Circuit Breaker in Low-Temperature Environment

ZHANG Jian, ZHANG Peng, XU Hui, GONG Mingchen, WANG Yue, ZHANG Jing

2023, 56(5):  153-162.  DOI: 10.11930/j.issn.1004-9649.202211047

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High-voltage circuit breaker is important for power system, whose failure will affect the safe and stable operation. Low-temperature environment would impact the breaking performance of circuit breakers. In order to study the influence of low temperature on circuit breaker fault detection, the hydraulic spring mechanism and opening/closing coil model were established. The effects of low-temperature and opening/closing coil faults on opening/closing time and coil current were simulated and analyzed. The fault simulation experiment platform in low-temperature environment was set up. A large number of fault simulation experiments were carried out under different low-temperature levels. The opening/closing time, opening/closing coil current and marginal spectral energy of vibration signal were taken as characteristic parameters. The variation laws of the characteristic parameters were analyzed. It is revealed that the low-temperature environment affects the breaking performance of the circuit breaker. The opening/closing time of the circuit breaker increases with the decrease of temperature. The temperature has little effect on the coil current. Meanwhile, the marginal spectral energy of vibration signal barely changes below –10 ℃. The results of this paper provide references for the fault diagnosis of circuit breakers in low-temperature environment.

Study on Using Distributed Wind-Storage Integrated System to Improve Frequency Stability of Offshore Oilfield Power Systems

SU Kaiyuan, DONG Wenkai, QIU Yinfeng, WEI Che, XIE Xiaorong

2023, 56(5):  163-171.  DOI: 10.11930/j.issn.1004-9649.202205103

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Aiming at the frequency stability problem of the offshore oilfield power systems (OOPSs) caused by the integration of offshore wind power, this paper proposes a solution based on the distributed wind-storage integrated system (DWSIS). Firstly, based on a real OOPS, the model of DWSIS is constructed as well as the grid it integrated into. Then, the principle and analysis method are proposed of DWSIS to improve the frequency stability of the grid. Finally, the effectiveness of the DWSIS is verified via electromagnetic transient simulation. The DWSIS proposed can be expected to improve the frequency stability of the OOPSs with high penetration of wind power and promote the low-carbon development of offshore platform production.

Research on High Reliability Three-Phase Multi-function Grid-Connected Converter

LI Yan, CHENG Xin, HUANG Zuliang, YANG Zhuo

2023, 56(5):  172-181.  DOI: 10.11930/j.issn.1004-9649.202206056

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The three-phase multi-functional grid-connected converter (TMGC) combines the power quality control function while realizing the connection with microgrid, which also has an important application prospect. In order to improve the operation reliability of TMGC, the reconstruction technology and fault tolerant control strategy of TMGC are proposed in this paper. Firstly, a fault diagnosis method for the open circuit fault of the converter is adopted. The fault diagnosis method is carried out according to the characteristics of midpoint voltage deviation before and after fault and the real-time switching state. Secondly, a TMGC reconstruction topology is proposed to realize the reconstruction of TMGC when secondary faults occur, which can enlarge the fault tolerance space. Then, the fault-tolerant control strategy of TMGC is proposed, which combines harmonic suppression control, PQ control and pulse reset method, so that TMGC can continue to realize power control and harmonic suppression functions of grid-connected microgrid after failure. Thus, a high reliability three-phase multi-functional grid-connected converter (HRTMGC) is formed. Finally, the Matlab/Simulink simulation results prove the effectiveness of the proposed reconstruction technology and its fault-tolerant control strategy.

New Energy

Frequency Stability Analysis Based on Full State Model in Autonomous-Synchronization Voltage Source Interfaced Power System

LI Zhenyao, GAN Deqiang, LUAN Moude, HE Guoqing

2023, 56(5):  182-192.  DOI: 10.11930/j.issn.1004-9649.202212063

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The application of new energy controlled by autonomous-synchronization voltage source is an important measure to enhance the frequency stability of high penetration renewable energy power system. For autonomous-synchronization voltage source grid-connected system, the quantitative relationship between the frequency-related characteristic quantities of the system and the system parameters is obtained through the analytical solution to the time-domain response of the state variables based on the approximate full-state model. First, the frequency stability problem is transformed into a quadratic eigenvalue problem (QEP), which proves that the reduction of the system inertia will reduce the disturbance-rejection capability of the system frequency in the inertial response stage. Then, the parameters of the autonomous-synchronization voltage source model are compared with those of the synchronous machine model, and it is proved that the function of the governor is equivalent to increasing the system damping, which can reduce the steady-state error of the system frequency after being disturbed. Based on the above conclusions, a method for estimating the virtual inertia and droop coefficient of renewable energy with the autonomous-synchronization voltage source that meets the preset frequency dynamic safety requirements is proposed. Finally, the correctness and effectiveness of the above conclusions and methods are verified by a system with 10 machines and 39 nodes.

Research on Typical Scenarios Based on Fusion Density Peak Value and Entropy Weight Method of Pearson’s Correlation Coefficient

ZHAO Yuanshang, LIN Weifang

2023, 56(5):  193-202.  DOI: 10.11930/j.issn.1004-9649.202212032

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The volatility and randomness of new energy output make it one of the key problems that need to be solved urgently to obtain typical output scenarios in the planning and operation analysis of new power systems. In this paper, a typical scenario clustering center determination method based on fusion density peak value and entropy weight method of Pearson’s correlation coefficient is proposed. The method first selects the initial clustering center by the density peak value method and then selects the subsequent clustering center based on the entropy weight method. Then, it obtains the final typical scenario by using the backward scenario reduction method. Therefore, this paper takes this method as the core to construct an overall scheme for determining the typical output scenarios of new energy. Finally, this paper uses the daily output scenario of wind power and photovoltaic power in North China in 2021 to carry out an analysis of examples and verification through comparison, which proves the accuracy and effectiveness of the proposed method. The research results will provide more accurate data support for power system planning and operation.

Information and Communication

Research on Electric Power Data Verification and Traceability Method Based on Blockchain Technology

LI Da, GUO Qinglei, WANG Dong, WANG Weixian, ZHOU Dongxu

2023, 56(5):  203-208.  DOI: 10.11930/j.issn.1004-9649.202210051

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A blockchain-based energy and power data verification and traceability model is designed, which uses access control and identity authentication to store the data on the chain, and uses smart contracts to automatically authorize the data to be opened to users with specific permissions, so as to realize the information exchange between relevant participants, and make the uplink data traceable effectively. Meanwhile, the on-chain data scoring card mechanism is introduced to conduct online evaluation and supervision on the data on-chain operation of relevant personnel, solve the adverse impact of untimely archiving, and propose to add a cross-chain real-time verification method to ensure the cross-chain effective verification of the file data content on the chain, thus solving the problem of the correlation between the model mechanism of data access verification and traceability that is common in energy and power scenarios.

A Cross-Domain Identity Control Model for Electric Blockchain

YANG Ke, WANG Dong, LI Da, QIAN Xiaoyu, LI Jun

2023, 56(5):  209-216.  DOI: 10.11930/j.issn.1004-9649.202209017

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There would be serious cross-domain authentication issue when business terminals access different trust domain nodes in various scenarios. In this regard, a supervisable and trusted identity management blockchain model is proposed in this paper, so as to support flexible cross-domain authentication of terminals by combining blockchain and identity authentication technology. Firstly, a novel blockchain-based trusted identity authentication infrastructure is established, and the authentication is completed by means of hash value verification, where the problem of trusted and efficient access to terminals in the outer domain could be solved. Secondly, to avoid malicious terminals accessing synchronous node data, the authentication mechanism and transaction strategy of terminals are designed based on the hierarchical classification of the certificate the energy and electricity blockchain network. Then credible and dynamic access of terminals and the separation of authority management of read and write transactions could be accomplished. Finally, while ensuring security and certificate validity, the efficiency of terminal cross-domain authentication could be improved compared with existing blockchain cross-domain authentication solutions.