Table of Content

28 August 2024, Volume 57 Issue 8

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Power System Flexibility Improvement Technology Based on Hydrogen Energy

Capacity Optimization Configuration of a Bidirectional Reversible Centralized Electrohydrogen Coupling System

Xing FENG, Wei YANG, Anan ZHANG, Xi ZHANG, Qian LI, Xianzhang LEI

2024, 57(8):  1-11.  DOI: 10.11930/j.issn.1004-9649.202312101

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In response to the problem of wind and light abandonment in large-scale new energy power plants in areas with abundant wind and solar energy, a bidirectional reversible centralized RSOC electric hydrogen coupling system capacity optimization configuration method is proposed by utilizing the reversible solid oxide fuel cell (RSOC) combined with the bidirectional conversion characteristics of hydrogen energy storage to absorb excess wind and solar resources. Firstly, construct a centralized RSOC electric hydrogen coupling system architecture, and establish models for power generation systems, electric hydrogen conversion systems, etc; Secondly, considering the characteristics of fuel cells, establish an RSOC performance degradation model, and generate typical scenarios considering the uncertainty of available transmission capacity of ultra-high voltage channels; Furthermore, a centralized RSOC double-layer capacity planning model is established. The upper layer optimizes the capacity configuration of RSOC and hydrogen storage with the goal of maximizing revenue during the operation period, while the lower layer optimizes the output of each equipment with the goal of minimizing comprehensive cost. The solution is solved by combining particle swarm optimization algorithm and CPLEX solver. Finally, through case analysis, it was verified that the addition of RSOC improved the system's economic and environmental benefits. At the same time, investment sensitivity analysis showed that the unit capacity cost of batteries is an important factor restricting the economic operation of the system.

Cluster Configuration of Electric-Hydrogen Coupled Distribution Network Considering Hydrogen Energy Transport Characteristics

Jie QIU, Caihao LIANG, Yongqiang ZHU, Ruihua XIA

2024, 57(8):  12-22.  DOI: 10.11930/j.issn.1004-9649.202312016

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The rational planning of integrated electricity-hydrogen system (IEHS) is of great significance to the transformation of energy structure. Making full use of the mobile characteristics of hydrogen energy storage may reduce the comprehensive cost of IEHS. Therefore, a distribution network cluster division and hydrogen energy system planning strategy considering the characteristics of hydrogen energy storage and transportation is proposed. Firstly, the hydrogen energy system is divided into multiple hydrogen energy subsystems (HES), and the transportation and storage cost model of gas-hydrogen trailer between HES is established. Secondly, based on the structure of power-transportation network and the distribution of new energy, the method of distribution network cluster division is proposed. Finally, according to the results of cluster division, the HES double-layer location capacity determination model is established. The model aims to minimize the annual comprehensive cost of IEHS, and solve the HES capacity allocation problem in a single cluster, the HES location capacity determination problem in each cluster and the gas-hydrogen trailer configuration problem in layers. The results show that the proposed strategy can reduce the pressure of hydrogen energy storage and transportation, reduce the comprehensive cost of IEHS, improve the absorption level of wind and light, and accelerate the iterative convergence rate of power flow calculation.

Two-Stage Stochastic Optimal Voltage Control of High-Proportional Photovoltaic Distribution Networks Considering Auxiliary Power to Hydrogen

Yajian ZHANG, Ci CHEN, Fei XUE, Li MA, Min ZHENG

2024, 57(8):  23-35.  DOI: 10.11930/j.issn.1004-9649.202307084

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To address the problems such as limited regulation resources, high regulation costs, and slow response speed in traditional distribution network voltage control methods, a two-stage stochastic optimal control strategy with participations of power-to-hydrogen (P2H) devices is investigated. Firstly, voltage regulation device operation constraints and distribution network line constraints are modeled. Then a two-stage day-ahead and intra-day voltage optimal control model is developed considering electrolytic gas production revenue. Secondly, to deal with the voltage fluctuations or even over-limitation problem caused by short-term disturbances of renewables and load demands, typical operation scenarios of distribution networks are constructed by adopting Latin hypercube sampling and Kantorovich distance reduction techniques. Then the voltage control strategy is solved by minimizing the expectation of intraday-stage objective functions under all scenarios. Finally, case studies have shown that compared with the traditional voltage methods without considering P2H participations, the voltage over-limitation can be effectively avoided and the total regulation costs can be reduced by over 26.43% by using the proposed method.

System Dynamics Modeling of Green Hydrogen Steel Smelting to Improve Wind Power Consumption

Zhuan ZHOU, Shuai MIAO, Tiejiang YUAN

2024, 57(8):  36-45.  DOI: 10.11930/j.issn.1004-9649.202310099

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Rich wind power electrolysis of water to produce hydrogen, coupled with high-pollution steel smelting process, not only promotes the low-carbon transformation of the steel-making industry, but also effectively improves the wind power consumption capacity. In order to simulate the influence of green hydrogen steel smelting on wind power accommodation capacity, considering the reliability of steel smelting, the economy of hydrogen energy development and the environment of wind power generation, the internal interaction and feedback mechanism of green electricity-hydrogen energy-steel smelting coupling system are determined. Combined with the development trend of iron and steel industry and the potential of green hydrogen substitution, a dynamic model of green hydrogen iron and steel smelting system for improving wind power consumption is established. At the same time, considering the government support and the development of hydrogen production technology, a differentiated scenario is constructed to analyze the scale of hydrogen demand and the level of wind power consumption under different conditions. Based on the case of Xinjiang, it is shown that increasing the support of hydrogen metallurgy and improving the efficiency of hydrogen electrolysis can effectively improve the replacement rate of green hydrogen in the iron and steel industry and accelerate the reduction of green hydrogen cost, so as to realize the full consumption of wind power and effectively solve the problem of abandoned wind.

Probabilistic Modeling Method of Hydrogen Load of Hydrogen Refueling Station Based on Vehicle Behavior Simulation

Chunhao LU, Chunli ZHOU, Xiqiao LIN, Zhijun CHEN

2024, 57(8):  46-54, 66.  DOI: 10.11930/j.issn.1004-9649.202308106

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The hydrogen load of hydrogen refueling station is affected by the travel behavior of hydrogen fuel cell vehicles, and its spatio-temporal distribution is highly uncertain. In order to study the distribution characteristics of hydrogen load of hydrogen refueling station and accurately describe the travel law of vehicle users, a probabilistic modeling method of hydrogen load of hydrogen refueling station based on vehicle behavior simulation is proposed in this paper. Firstly, the probability distribution of behavioral features (such as travel time, travel time, destination, travel distance, etc.) during vehicle travel is fitted based on the American household travel survey data set. Secondly, based on Monte Carlo simulation method, samples are extracted several times to form a travel chain composed of vehicle travel behavior. Finally, based on the type of travel destination, the hydrogen load characteristics of different regional hydrogen stations in one day were simulated. Through rational use of actual travel data and Monte Carlo simulation method, this paper can accurately describe the vehicle behavior law, and infer the hydrogen load characteristics of different regional hydrogen refueling stations according to the type of travel destination.

New Energy

Suppression Strategy of Sub/Super-synchronous Oscillations in Doubly-Fed Wind Farm Based on SVG Additional Current Feedback Impedance Reshaping

Zejia WANG, Minxiao HAN, Yiwen FAN

2024, 57(8):  55-66.  DOI: 10.11930/j.issn.1004-9649.202308003

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Doubly-fed wind farm often interacts with the power grid, leading to sub/super-synchronous oscillations. To address the issue of limited adaptability in suppressing these oscillations using impedance reshaping methods, this paper proposes an impedance reshaping method based on a static var generator (SVG)-additional current feedback control. The virtual impedance established by this method is correlated with the impedance characteristics of the wind farm, providing greater flexibility compared with fixed virtual impedance obtained through modeling and analytical design. Initially, the virtual impedance formulation, incorporating the SVG and wind farm grid-connected impedance models, is derived. Subsequently, the effectiveness of the proposed method and the impact of impedance reshaping control parameters on the suppression performance are analyzed based on impedance frequency characteristics. Finally, based on the grid-connected model of a doubly-fed wind farm in Qinghai Province, an electromagnetic transient simulation model is developed in PSCAD/EMTDC. The simulation results demonstrate that the proposed method achieves impedance reshaping for the wind farm under different oscillation conditions, effectively suppressing sub/super-synchronous oscillations in the wind farm.

Functional Orientation and Development Prospect of Natural Gas Power Generation in New Power System

Guanjun FU, Fuqiang ZHANG, Peng XIA, Junshu FENG, Jinfang ZHANG

2024, 57(8):  67-74.  DOI: 10.11930/j.issn.1004-9649.202401112

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Natural gas power generation has the advantages of low emissions, high efficiency, and flexibility. It is an important component and effective power source for building a new power system under the dual carbon goals of reaching carbon emission peak and carbon neutrality. However, there are still problems in China's natural gas power generation development, such as the relatively low gas source guarantee, high fuel costs, and limited key core technologies. At present, disputes about the development of natural gas power generation in the dual carbon process still exist. It is urgent to have a unified understanding and clarify its development orientation and direction. This paper takes the integrated development of natural gas power generation and new energy generation into consideration in the overall planning of the power system. It uses self-developed carbon emission peak and carbon neutrality power planning software packages for optimization analysis and constructs a low-carbon transformation scenario for the power industry with zero carbon as the goal. It analyzes the future development scale and layout of natural gas power generation under the carbon neutrality goal and conducts sensitivity analysis on the uncertainty factors affecting the future scale of natural gas power generation. Based on the model calculation results, the paper establishes quantitative indicators to evaluate the functional role of gas-fired electricity in new power systems and analyzes its functional role in clean electricity supply, power balance, and peak shaving balance in the future. Natural gas power generation still needs moderate development in the future, with new layouts mainly concentrated in the southeast coastal areas and gradually increasing in the central and western regions. In the future, the focus must be on strengthening the coordination of natural gas production, transportation, storage, and sales, improving the pricing mechanism of natural gas and gas-fired electricity, and accelerating the development of core technologies, to give full play to the positive role of natural gas power generation in the construction of new power system.

LVRT Measurement Model and Transient Parameter Identification of Wind Turbine Based on Chaotic Particle Swarm

Dan LI, Shiyao QIN, Shaolin LI, Jing HE

2024, 57(8):  75-84.  DOI: 10.11930/j.issn.1004-9649.202310040

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The high-accuracy simulation model is the basis for transient stability analysis of large-scale wind power integration. However, the control strategies and parameters of doubly-fed wind turbines are technical secrets that are difficult to obtain, and the accuracy of model simulation is difficult to guarantee. In order to address the fault transient modeling problems of doubly-fed wind turbines, a measured data-based modeling and parameter identification method of doubly-fed wind turbines is proposed. Firstly, based on the DFIG model and control structure of the Power System Integrated Stability Program (PSASP), a low voltage ride through (LVRT) control mathematical model is established to analyze the fault transient process, and the LVRT transient control core parameters are clarified. Secondly, based on part of the field measured LVRT data of doubly-fed wind turbines, the fault transient parameters are identified with the chaotic particle swarm optimization algorithm. Finally, the accuracy of the identification parameters are analyzed and verified based on the remaining measured data. The simulation results have verified the effectiveness and accuracy of the proposed parameter identification method. The proposed method has strong generalization ability and high accuracy of identification results, and is of great engineering application value.

Coordinated Control Strategy of Modular Multi-level Converter-Based Multi-terminal Direct Current System for Onshore Wind Power Faults

Ping ZHAO, Haosen JIA, Hengxiao GAO, Zhenxing LI

2024, 57(8):  85-95.  DOI: 10.11930/j.issn.1004-9649.202308031

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This paper proposed a coordinated control strategy of multiple wind farm modular multilevel converters (WFMMCs) and wind turbines using energy control to address the issue of surplus power during faults in the onshore alternating current (AC) power grid of a modular multilevel converter based multi-terminal direct current (MMC-MTDC) system for offshore wind power. During the fault period, some WFMMCs first initiate energy control, raising the energy reference value based on changes in direct current (DC) voltage to absorb surplus power in the DC system. The remaining WFMMCs predict the DC voltage, and when the predicted DC voltage exceeds the limit, the remaining WFMMCs activate energy control to absorb surplus power. The WFMMCs adopt voltage reduction control on the wind turbine while absorbing surplus power and reduce the reference value of the AC voltage on the wind turbine side based on the increase in energy storage at the WFMMC. The grid side converter of the wind turbine adjusts the reference value of the d-axis current based on changes in AC voltage, reducing the active power transmitted to the MMC-MTDC system and avoiding the DC voltage exceeding the limit of the MMC-MTDC system. Finally, different types of faults were simulated in PSCAD/EMTDC to verify the effectiveness of the proposed coordinated control strategy.

Multi-level Interval Rolling Warning Method for Distributed Photovoltaic Fluctuation Events

Caiqi ZHOU, Jingli LIU, Pengkai SUN, Yumin ZHANG

2024, 57(8):  96-107.  DOI: 10.11930/j.issn.1004-9649.202402058

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Under the influence of large-area extreme weather conditions, the impact of distributed photovoltaic fluctuations on power system balance is significant and may lead to risks such as curtailment of solar power and load shedding. In response to these issues, this paper proposes a multi-level rolling warning method for distributed photovoltaic fluctuations based on interval analysis theory, aiming to provide a rolling warning of the potential harm of distributed photovoltaic fluctuations. Firstly, the power control mechanism for handling distributed photovoltaic fluctuations in the power system is clarified, and warning levels are established to determine the range of fluctuations that can be controlled by different power control measures, i.e., the warning thresholds corresponding to different warning levels. Secondly, based on the probability density of distributed photovoltaic fluctuations, the probabilities of each warning level are calculated by integrating the probability densities within each warning range. Finally, the differences in forecasting accuracy of photovoltaic fluctuations at different time scales are analyzed, and the rolling warning of distributed photovoltaic fluctuations is achieved by periodically adjusting the warning results. Case study results demonstrate that the proposed method can determine the thresholds for each warning range while providing warning results for different system operating conditions and photovoltaic fluctuation events. Moreover, the root mean square error of the warning results obtained with our method compared to those of the Monte Carlo method is only 1.6718%, thus verifying the effectiveness and applicability of the proposed method.

Maximum Accommodation Capacity Decomposition of Distributed Renewable Power Generation Considering Multi-Level Distribution Network

Donglei SUN, Yi SUN, Rui LIU, Pengkai SUN, Yumin ZHANG

2024, 57(8):  108-116.  DOI: 10.11930/j.issn.1004-9649.202404020

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With the integration of distributed renewable energy sources (RES) into various levels of distribution networks characterized by their "numerous and widely distributed" nature, the power grid exhibits a multi-level access and integrated consumption pattern for renewable energy. To facilitate the full consumption and efficient utilization of renewable energy, a model for calculating the maximum consumption capacity of RES in multi-level distribution networks is proposed. This approach transforms the complex task of estimating the maximum RES consumption capacity in the entire system into sub-problems focused on individual distribution network levels, thereby enabling precise measurements of the maximum RES consumption space at each level. Firstly, with the objective of maximizing the RES penetration within the multi-level distribution network, a consumption space calculation model is established based on the Distflow power flow model. Secondly, to address the issues of non-convexity and low solution efficiency inherent in the model, a second-order cone relaxation technique is applied to transform the model into a mixed-integer second-order cone programming (MISOCP) model. Subsequently, the alternating direction method of multipliers (ADMM) is employed to decompose the overall RES consumption space estimation problem into sub-problems focused on individual distribution network levels, effectively transforming the consumption space model into a decomposed calculation model for the maximum RES consumption capacity across the multi-level distribution network. Finally, the effectiveness of this methodology is demonstrated through simulations on the IEEE 6, 7, 9, 10, 12, and 15 test systems.

Power System

Coordinated Planning of Medium-Voltage and Low-Voltage Flexible Interconnection for Distribution Networks with High Proportion of Distributed Generation

Hanmei PENG, Tang YIN, Qianhao XIAO, Mao TAN, Yongxin SU, Hui LI

2024, 57(8):  117-129.  DOI: 10.11930/j.issn.1004-9649.202309007

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Flexible interconnection technology is one of the effective means to solve numerous problems faced by distribution networks with high proportion of distributed generations (DGs). A multi-layer optimization based coordinated planning method for medium-voltage and low voltage flexible interconnection of distribution networks is proposed. Firstly, a power flow model for distribution network with medium-voltage and low-voltage flexible interconnection based on power electronics flexible interconnected devices (FID) is built. Then, a three-layer coordinated planning model is constructed. With the upper layer aiming to minimize the annual operating cost of low-voltage FIDs and the annual variance of transformer load rate in substation areas, and the middle layer aiming to minimize the annual operating cost of medium voltage FIDs and the annual electricity purchasing cost from the higher-level power grid, they respectively determine the installation location and capacity of low-voltage and medium-voltage FIDs. The lower layer optimizes the system operation with the goal of minimizing the electricity purchasing cost from the higher-level power grid in each scenario. A hybrid algorithm based on adaptive particle swarm optimization and second-order cone programming is adopted for solution. Finally, an IEEE-33 node distribution network with a high proportion of DGs is used for case study, and the results indicate that through flexible interconnection planning, the annual comprehensive operating cost of the example system is reduced by 19.01% and the annual variance of transformer load rate in substation areas is reduced by 82.59%, showing the effectiveness of the proposed planning model.

Network Security Risk Assessment Index System and Calculation for Virtual Power Plant

Ke YANG, Dong WANG, Da LI, Wangjun ZHANG, Ga XIANG, Jun LI

2024, 57(8):  130-137.  DOI: 10.11930/j.issn.1004-9649.202311036

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In this paper, we propose a multidimensional dynamic risk assessment index system for the new system of virtual power plants. Firstly, based on the characteristics of the virtual power plant, a static risk assessment index system is built; a dynamic risk assessment index system is constructed, based on the evolution mechanism of attack paths, and collects data from information, physical and the information physical sides. Then, we propose a quantitative assessment method. Finally, the simulation experiment is carried out to validate the multi-dimensional dynamic risk assessment index system proposed in this paper, which can assess the network risk of the virtual power plant, identify potential risks, and propose valid enhancement measures.

Distributed Reactive Power Control Strategy of Distribution Network Considering Massive Distributed Energy Access

Suwei ZHAI, Yinyin LI, Fan DU, Wenyun LI, Kaiyan PAN, Junkai LIANG

2024, 57(8):  138-144.  DOI: 10.11930/j.issn.1004-9649.202403107

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In view of the influence of unconventional safety risks on new power systems, a two-layer cooperative reactive power control strategy considering the uncertainty of source load was proposed. The reactive power optimization model of distribution network was established with the aim of minimizing the loss of distribution network and considering various regulation equipment constraints. The distribution network distributed reactive power optimization solution framework was constructed. The outer layer adopted the adaptive overrelaxation penalty parameter alternating direction method of multipliers (ADMM) for global update iterative solution. In the inner layer, the column-and-constraint generation (C&CG) algorithm was used to solve the two-stage distributionally robust reactive power optimization model for each region. The proposed strategy can effectively improve the solving efficiency of distributed reactive power optimization model, reduce network losses, and improve the stability of the new power system.

Dynamic Optimization Model of AGC Units Considering TCPS Assessment Constraints

Sheng CHEN, Honglue ZHANG, Tian XIA, Xue YANG, Wenjun ZHANG, Wei YAN

2024, 57(8):  145-151.  DOI: 10.11930/j.issn.1004-9649.202304103

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In recent years, power grid has begun to use the transformational control performance standard (TCPS) to assess the level of automatic generation control (AGC) in various regions. However, existing researches only consider the assessment of control performance standard (CPS). In view of this, a dynamic optimization model of AGC units considering TCPS is proposed, which takes the minimum comprehensive adjustment cost of secondary frequency regulation as the objective and the system power balance and TCPS assessment as the constraints. The piecewise functions of the TCPS assessment constraints in the new model are linearized to achieve the efficient solution of the model. Based on a modified IEEE example, an AGC hysteresis control strategy in engineering and CPS, the effectiveness of the model is verified through simulation.

Automatic Connection of Virtual Circuits in Smart Substations Based on Chaotic Two-Dimensional Mapping Sine and Cosine Algorithm

Guofeng JIN, Shifeng YANG, Lingling LIU, Kai WANG, Qiang WANG, Lei WANG

2024, 57(8):  152-158.  DOI: 10.11930/j.issn.1004-9649.202403026

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In this paper, a virtual loop automatic connection technology based on two-dimensional chaotic sine-cosine algorithm is proposed. Firstly, a virtual terminal matching model involving distance weight vector is constructed by using Jaro-Winkler distance. Then, on the basis of the historical data of virtual connection, the optimal distance weight vector is solved by using the two-dimensional chaotic sine-cosine algorithm. Finally, a 66 kV substation in eastern Mongolia is taken as an example to match virtual terminals with the proposed method. The results show that the virtual terminal connection results obtained by the proposed method are more accurate and more efficient than those obtained by the prior art.

Secondary System Fault Detection Method Based on Association Rules and Reconstruction Error

Yang WANG, Weidong MA, Jiming LIU, Boshi WANG, Kai YAO, Wei HAN, Juan YU

2024, 57(8):  159-167.  DOI: 10.11930/j.issn.1004-9649.202308131

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The reliability of the secondary system directly affects the safe and reliable operation of the entire substation and even the power grid. With the high proportion of renewable energy sources integrated into power systems, it is increasingly important to effectively detect the secondary system faults. However, existing research faces two challenges: on the one hand, the existing fault detection methods for logic circuits have high requirements for data completeness and are difficult to apply in practice; on the other hand, the existing fault detection methods for secondary equipment are difficult to identify the small differences between normal and fault data, and the computational accuracy is difficult to guarantee. Therefore this paper proposes a secondary system fault detection method based on association rules and reconstruction errors. Firstly, the Apriori algorithm is used to derive the association rules between fault alarm information and fault devices in the logic circuit, achieving rapid diagnosis of logic circuit faults. Then, the individual discriminator is trained using the operational data of normal secondary equipment, and the operating status of the secondary equipment is determined by measuring the reconstruction error of the data to be discriminated. The ensemble learning model is used to quantify the current fault detection probability of the equipment. Finally, the ensemble learning model is optimized to improve the accuracy of secondary equipment anomaly warning. The effectiveness and accuracy of the proposed method was verified by simulating the dataset from a substation in Henan Province.

Online Assessment of Control-Based System Security and Stability Service Quality for New Power System

Bijun LI, Wei LI, Xijian DONG

2024, 57(8):  168-181.  DOI: 10.11930/j.issn.1004-9649.202401131

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In the context of new power system, the safe and stable operation of power system is more dependent on the control-based system security and stability service. The ex-post and ex-ante entire-process evaluation of service response is an essential technical support to realize the effective management and control of the control-based system security and stability service quality. To address the common problems in assessing the control-based system security and stability service quality, this paper analyzes the characteristics of the control-based system security and stability service, and determines the connotation and factors for assessing the control-based system security and stability service quality, including service equipment quality and service resource quality before service response, as well as the service response quality after service response. The criteria, index system, methodology and basic data for assessing the control-based system security and stability service quality are described. Finally, an online assessment framework for control-based system security and stability service quality is proposed, including collecting basic data from power plants and substations, determining the assessment criteria and indexes for quality elements, evaluating the indexes and levels for stability services quality, which has universal applicability to the quality assessment of various control-based system security and stability services, including entire key links and complete functional information.

Large-Scale Power Grid ADPSS Electromagnetic Transient Modeling Method and Software Implementation Based on PSD-BPA Data

Shuwen XU, Guying ZHUO, Zhuang LI, Min LIU, Qing MU

2024, 57(8):  182-189.  DOI: 10.11930/j.issn.1004-9649.202309070

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With the increasing scale of new energy, flexible DC, FACTS and other new power electronic equipment connecting to the power grid, the operational characteristics of the new large-scale power grid have undergone significant changes, and electromagnetic transient refined simulation has become an important means of future power system simulation. However, the difficulty of electromagnetic transient modeling seriously restricts the widespread application of electromagnetic transient simulation. To address this challenge, a technical solution for quickly converting BPA data into ADPSS (advanced digital power system simulator) electromagnetic transient models was proposed, and corresponding software was developed. Through technical means such as modeling control by group, mapping modeling, user defined modeling, topology optimization layout, etc., the rapid automated conversion modeling from BPA data to ADPSS data was achieved. Finally, based on the BPA regional power grid data, a full electromagnetic transient modeling of a provincial power grid was completed using this software with the example scale exceeding 5000 three-phase nodes, and the modeling efficiency was greatly improved. The simulation results verified the effectiveness of the conversion modeling program.

Attribution and Quantitative Analysis Method for Regional Power Load Growth Based on Feature Construction

Min QIU, Ying ZHOU, Weibo ZHAO, Yang WANG, Songsong CHEN, Yaoyang GUO, Bo ZHAO

2024, 57(8):  190-205.  DOI: 10.11930/j.issn.1004-9649.202310056

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The power load is affected by various factors such as temperature, economy, special events, and multi-factor coupling, which makes the quantitative analysis of the causes of the power load growth difficult. At the same time, current load analysis is mostly focused on prediction, and it is uncommon to analyze the causes of load growth.Therefore, based on a study on the construction method of power load data characteristics, a power load growth attribution analysis method is proposed. Firstly, the meteorological correlation indicators, the economic development-based natural load growth indicators, the electrical quantity correction-based industrial structure change indicators, and the event trend consistency evaluation indicators are constructed. And then, the meteorological load, natural economic load, industrial expansion load and random load are respectively extracted, and the contribution rate is used to quantify the influence degree of each factor on the load growth. Finally, the power consumption data of two northwestern provinces are used to verify the proposed method, which indicates that the proposed method is effectively quantify the causes of load growth.

Numerical Recognition Algorithm for Power Equipment Monitoring Based on Light-Resnet Convolutional Neural Network

Zhiheng KONG, Chong TAN, Peiyao TANG, Chengbo HU, Min ZHENG

2024, 57(8):  206-213.  DOI: 10.11930/j.issn.1004-9649.202310020

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In the smart grid, precise monitoring of the operational status of critical equipment for transmission, distribution and power supply is essential for effective online maintenance. Faced with the inefficiencies of manual recording and inspection, as well as the challenges associated with the complex installation, high cost and lengthy periods required for digital upgrades of monitoring devices, a novel approach that integrates image capture devices with image processing technology has been developed. This approach, leveraging the allocation of computational resources for task distribution, introduces a Light-Resnet-based numerical recognition algorithm, which enhances network training through the optimization of the D-Add loss function, enabling remote reading of electrical equipment monitoring data. Experiments have demonstrated that Light-Resnet achieves a rigorous accuracy rate of 98.8% on the MNIST dataset with only 6090 parameters. When combined with edge computing collaboration mechanisms, it resulted in a 20.73% reduction in power consumption on the terminal side. The proposed algorithm not only proves its adaptability and efficiency in resource-constrained environments but also significantly improves the network's accuracy with design of the D-Add loss function.

Integrated Energy System Optimization

Multi-time Scale Optimal Scheduling of Integrated Energy System Coupling Power-to-Gas and Carbon Capture System

Hui WANG, Kerui ZHOU, Zuohui WU, Zhichao ZOU, Xin LI

2024, 57(8):  214-226.  DOI: 10.11930/j.issn.1004-9649.202312011

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To improve the renewable energy consumption and low-carbon economic benefits of the integrated energy system (IES), this paper proposes a multi-time scale coordinated optimal scheduling model for IES that combines power-to-gas (P2G) and carbon capture system (CCS). Firstly, a coupling model of P2G and CCS based on a tiered carbon trading mechanism is established, and an electric-thermal-cooling IES is constructed using multiple energy conversion and storage devices. Secondly, based on the multi-time scale optimization scheduling strategy, an optimal scheduling model is established respectively for three stages including day-ahead, intra-day rolling, and real-time adjustment with energy purchasing costs, operation and maintenance cost, carbon trading cost, and wind and solar curtailment cost as objective function. Finally, a simulation was conducted using a case study of an industrial park in Sichuan. The results demonstrate that the proposed model effectively improves the low-carbon economic benefits, energy utilization efficiency, and system stability of the IES.

Integrated Energy System Optimal Dispatch Considering Oxy-Fuel Combustion Carbon Capture Technology and Source-Load Bilateral Response

Haizhu YANG, Yanan BAI, Peng ZHANG, Zhongwen LI

2024, 57(8):  227-240.  DOI: 10.11930/j.issn.1004-9649.202311046

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In order to reduce the carbon emission level of gas turbines and improve their flexibility, this paper proposes a low-carbon economic optimization strategy for the integrated energy system that takes into account oxy-fuel combustion carbon capture technology and source-load bilateral response. Firstly, the operating principle and energy flow characteristics of oxy-fuel combustion technology were studied, and a coupling model of air separation oxygen production equipment and carbon capture equipment was constructed. Secondly, the adjustable heat-to-power ratio was introduced as a supply-side response strategy, and a comprehensive trade-off was made for the demand-side between the characteristics of electricity, heat energy and gas load, and a demand-side response mechanism was formed with the guidance of energy prices and considering their substitutable attributes with each other. Finally, through constraining the carbon emissions by tiered carbon trading with consideration of carbon emissions of gas load, the units output in each period was optimized with the system operating cost as the objective. Multiple scenarios were set up for simulation analysis, and the results show that the oxy-fuel combustion carbon capture technology can effectively reduce the carbon emissions of the system, and the source-load bilateral response can flexibly adjust the energy supply relationship between the supply side and the demand side, and effectively reduce the operating cost of the system.