Table of Content

28 June 2024, Volume 57 Issue 6

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Special Contribution

Trend of Manufacturing Transfer and Undertaking Between Regions in China Based on Electricity Consumption by Province and Industry

Xiang WANG, Guoqiang JI, Chenrui WU

2024, 57(6):  1-8.  DOI: 10.11930/j.issn.1004-9649.202311085

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Since 2008, the internal and external conditions of China's economic development have changed dramatically, and the government attaches great importance to the orderly transfer of industries and the optimization of productivity. In view of the existing situation that for a long time the technical means have not been enough to judge the trend of industrial transfer in China and relevant research conclusions are controversial, this paper establishes a method to evaluate the trend and scale of industrial transfer and undertaking by taking advantage of the electricity consumption statistics. Based on the calculation of power consumption by province and industry during 2010-2021, it is found that there is a certain scale of industrial transfer and undertaking between regions; environmental protection policies have a great impact on the industrial relocation in North China and Central China power grid; the scale of East China power grid's regional industrial transfer is less than expected, which may be due to the reason that the industrial transfer is mainly undertaken within the region; in addition to the increasing agglomeration trend of energy-consuming industries, textile, medicine, equipment manufacturing and other industries are transfering to the northwest power grid region; the regional industrial transfer types in China Southern power grid's region are more diverse and the scale is larger, mainly due to the influence of Guangdong Province. Combined with the research conclusions, relevant policy proposals are put forward.

Key Safety Technology of Lithium-Ion Battery Body for Energy Storage

Battery Cluster Inconsistency Detection Method and Intelligent O&M Scheme Based on Vector Error Correction Model

Yuan GUO, Xiangyang XIA, Jiahui YUE, Hui LI, Jinbo WU

2024, 57(6):  9-17, 44.  DOI: 10.11930/j.issn.1004-9649.202401040

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To solve the problems of incomplete battery data and fragmented data segments leading to inaccurate detection in the actual operation data of energy storage power stations, this paper proposes a battery cluster inconsistency detection method based on the vector error correction model. In this method, the vector error correction model of battery clusters and battery cells is constructed using random voltage fragment data, the impulse response function is calculated, the dynamic mechanism of battery cells on battery clusters is analyzed, and the inconsistency degree of battery clusters is assessed. Subsequently, the abnormal battery cells and subsequent operation and maintenance are identified by variance decomposition analysis. Finally, through the actual operation data of the energy storage power station, the feasibility and effectiveness of the battery cluster inconsistency detection method and operation and maintenance scheme are verified in an actual engineering test on a 100 kW/200 kW·h energy storage platform.

State of Charge Estimation of Energy Storage Battery Pack under Typical Peak/Frequency Modulation Conditions

Muyu ZHU, Hongzhong MA, Pengyu GUO, Wenjing XUAN

2024, 57(6):  18-26.  DOI: 10.11930/j.issn.1004-9649.202401003

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To address the issue of low estimation accuracy of the state of charge (SOC) for an energy storage battery pack under typical energy storage conditions of a power grid, this paper proposes a new SOC estimation model based on kernel principal component analysis (KPCA), pelican optimization algorithm (POA), and bidirectional gated recurrent unit (BiGRU). By designing the charge and discharge experiment of a battery pack under the condition of peak/frequency modulation, the paper extracts the fusion features of SOC change from the data as the model input. BiGRU networks are constructed under different working conditions, and POA is utilized to optimize its hyperparameters to improve the model's performance. The effectiveness of the model is further verified under mixed conditions. The results show that the proposed model has better SOC estimation performance and stronger robustness, which can improve the SOC estimation accuracy of energy storage battery packs under complex energy storage conditions.

Thermal Performance Analysis of Novel All-Climate Lithium-Ion Battery Thermal Management System Coupled with Heat Pipes and Phase Change Materials

Huimin XIONG, Yuezhong PENG, Lixue HE, Zhangmao HU, Wei WANG, Hong TIAN

2024, 57(6):  27-36.  DOI: 10.11930/j.issn.1004-9649.202401029

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The battery thermal management system is an essential approach to ensuring the safe and efficient operation of energy storage batteries under different operating conditions. Considering the high latent heat of phase change materials and the superior thermal conductivity of heat pipes, this paper designs a novel lithium-ion battery thermal management system for lithium-ion batteries coupled with heat pipes and phase change materials coupling that can realize the requirements of heat removal and heat preservation under all-climate conditions. The thermal performance of such a battery thermal management system is numerically investigated. Under low-temperature environments, the paper analyzes the influences of insulation material thickness and initial battery temperature on the duration of heat preservation by simulating the battery discharge process and the temperature drop after discharge. In contrast, at normal and high ambient temperatures, it proposes heat removal strategies based on single or coupled measures of phase change materials, heat pipes, and gas/liquid cooling channels for the safe operation of lithium-ion batteries, especially at 0.5C to 2.0C discharge rates. The current work could provide theoretical guidance for the efficient design of a lithium-ion battery thermal management system covering the whole climatic range.

SOC Estimation of Large Capacity Lithium Batteries Based on LWOA-LSTM

Hongzhong MA, Wenjing XUAN, Muyu ZHU, Yuelin CHEN

2024, 57(6):  37-44.  DOI: 10.11930/j.issn.1004-9649.202312106

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Accurate prediction of the state of charge (SOC) of lithium batteries is crucial for their safe operation, and analyzing the SOC in different power grid modes is the basis for the comprehensive promotion of lithium batteries. This paper proposes a whale optimization algorithm based on Levy flight (LWOA) to optimize long short-term memory neural network (LSTM) for estimating the SOC of large capacity lithium-ion batteries in frequency modulation mode. Firstly, the LSTM neural network and LWOA algorithm are analyzed, and the LWOA-LSTM model is constructed to optimize the parameters. Then, the experimental data of the large capacity lithium-ion battery pack in frequency modulation mode are selected for data preprocessing and model training. Finally, SOC estimation of lithium batteries in frequency modulation mode is achieved. The experimental results show that the constructed model can accurately predict the SOC of lithium batteries. Compared with the WOA-LSTM model, the evaluation indicators RMSE and MAE are reduced by 25.55% and 28.71%, respectively, while R² increases by 0.76%.

Health State Equalization Control Strategy for Multi-battery Clusters in Energy Storage Systems

Hao PENG, Zhengjing LUO, Xiangyang XIA, Gang ZENG, Yujian OU, Guiquan CHEN, Jijun WANG, Lihong LIU

2024, 57(6):  45-52.  DOI: 10.11930/j.issn.1004-9649.202401124

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To address the issue of health state equalization among multiple battery clusters in energy storage systems, this paper designs a multi-battery cluster health state equalization control strategy for the energy storage system. This strategy sets the minimum grid-connected power limit for the storage converter according to the change rule of battery life and the grid connection requirements and determines the number of storage converter units involved in the operation of the system based on this limit. Furthermore, the hierarchical analysis method is combined to evaluate the health state of the various clusters of batteries involved in the operation and quantify the value to get the weight coefficients and corresponding power sizes of the storage converter to assume the grid-connected power command. The number of participating energy storage converters and the transmitted power are adjusted to ensure that the power of each energy storage converter does not exceed the limit. Compared with the equalization control strategy, the proposed control strategy can effectively equalize the health state of each battery cluster, extending the overall service life of the energy storage power plant by 40.6% and effectively improving the safety and economy of the energy storage power plant.

Key Technologies for Energy Storage Planning and Operation of New Power System

Review and Prospect of Modeling Method and Application Scenarios of Virtual Energy Storage under Integrated Energy System

Juan SU, Tuo LI, Junwei LIU, Yue XIA, Songhuai DU

2024, 57(6):  53-68.  DOI: 10.11930/j.issn.1004-9649.202311066

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In order to facilitate the complementary coupling of various forms of energy and achieve local consumption of renewable energy, integrated energy system (IES) has become a research hotspot across multiple disciplines. Considering the diversity and complexity of energy devices and networks, as well as the disparity in energy time scales, the source, grid and load with adjustable characteristics within the system are modeled as storage elements using energy balance principles, and a virtual energy storage system is constructed with them, which is incorporated into the optimization and scheduling of the IES. To accurately grasp the research focus of virtual energy storage, this paper firstly introduces the definition, logical structure and technical connotation of virtual energy storage, and summarizes four virtual energy storage modeling methods and characteristic indexes for the equipment or network on the source, grid and load side of integrated energy system, and then emphatically analyzes the specific application of virtual energy storage in four typical scenarios, and finally looks ahead to the future development direction of virtual energy storage.

Voltage Optimal Control Strategy for Distribution Networks with Multiple Integrated Photovoltaic and Energy Storage Machines

Jinglin HAN, Ping HU, Ruosong HOU, Zhiyong CHEN, Hongtao LI, Yuanyuan CHAI

2024, 57(6):  69-77, 152.  DOI: 10.11930/j.issn.1004-9649.202312030

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The access of large-scale distributed photovoltaic (PV) into distribution networks (DNs) can easily cause voltage violation problem, posing a threat to the safe and stable operation of DNs. Therefore, a voltage optimal control strategy that combines the centralized optimization and distributed real-time control is presented for DNs with multiple integrated PV and energy storage (ES) machines. Firstly, a centralized rolling optimization model is established to formulate the voltage and power references of PV-ES machine in the next period. Then, a distributed voltage real-time control method is proposed using the voltage sensitivity coefficients to develop the local reactive power droop curve, distributed reactive power support and local active power control logic. Finally, the IEEE 33-node system is used to verify the feasibility and effectiveness of the proposed control strategy. The proposed voltage control strategy can effectively solve the voltage violation problem, and possess the adaptive voltage regulation ability under real-time fluctuations of source-load power.

MMC Based Super Capacitor and Battery Hybrid Energy Storage System and Hybrid Synchronous Control Strategy

Yu CAO, Pengfei HU, Wanqi CAI, Xi WANG, Daozhuo JIANG, Yiqiao LIANG

2024, 57(6):  78-89.  DOI: 10.11930/j.issn.1004-9649.202311047

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To meet the requirements of energy storage system to provide inertia and primary frequency regulation for centralized configuration and optimal control of multiple energy storage media, an overall hybrid synchronous control (HSC) strategy is proposed for modular multilevel converter (MMC) based hybrid energy storage system (HESS). The modular design method is adopted for MMC-HESS, where the super capacitors (SC) and batteries are placed in the DC bus side and in the sub-module (SM) respectively, which has advantages of high power density and high energy density. The topology and working principle of HESS are analyzed, and the HSC strategy is used to provide system inertia and primary frequency regulation, as well as the synchronization capability and isolation control function for fault current limiting. The filter is employed for distributing power of energy storage, and the state of charge (SOC) balancing control is used for battery energy regulation. Finally, based on the hardware-in-the-loop experimentation platform, the MMC-HESS topology and control strategy proposed in this paper are verified. The experimental results indicate that the proposed HSC-MMC-HESS is able to provide inertia and frequency support capability, and switch flexibly between fault current-limiting, normal grid-connection and island operation, giving a full play to the comprehensive advantages of hybrid energy storage. The application of HSC-MMC-HESS has good prospects in medium-voltage distribution network.

Optimal Allocation of Hybrid Energy Storage in Low-Voltage Distribution Networks with Incentive-based Demand Response

Fengliang XU, Keqian WANG, Wenhao WANG, Peng WANG, Wenye WANG, Shuai ZHANG, Fengzhan ZHAO

2024, 57(6):  90-101.  DOI: 10.11930/j.issn.1004-9649.202312032

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With the high penetration rate of distributed photovoltaic access and the promotion of re-electrification and electrical energy substitution, the volatility of the system source and load is intensified, and the traditional distribution network planning methods are difficult to adapt to the requirements of the new power system development. To address this problem, an optimal allocation model for hybrid energy storage in low-voltage distribution networks considering incentive-based demand response is firstly established. Then, based on the characteristics of energy storage devices and incentive-based demand-side response resources at different time scales, it is proposed to use the improved VMD algorithm to make a multi-scale decomposition and combined reconstruction of the net load curves, and the improved whale optimization algorithm is used to solve the optimal allocation model with the objective of the minimum sum of the total system cost and active power fluctuation value. Finally, the effectiveness of the proposed scheme is verified with practical examples.

Power System

Distribution Optimization Method for Power Environment-Friendly Mixed Insulation Gas

Jie DONG, Bo YANG, Guoxin YI, Haichuan HE, Le MA

2024, 57(6):  102-109.  DOI: 10.11930/j.issn.1004-9649.202312056

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The state-of-art cost of environmental-friendly SF₆/CF₄ mixed insulating gas of GIS equipment in the power system is relatively high. In order to ensure its insulation and arc extinguishing performance, SF₆ gas is overfilled on site, which is not in line with the purpose of using the mixed gas to achieve environmental protection and prevent liquefaction. Therefore, an optimized method of timed alternate gas blending for environmental-friendly SF₆/CF₄ mixed insulating gas based on a single mass flow controller is proposed. Through the timed alternate gas blending and instant mixing technology, the gas blending error caused by residual gas in the shared gas pipeline is analyzed and optimized. The SF₆ gas output time correction technology and the time reallocation method for the last period are studied, further reducing the error in the mixing ratio of the filled gas. Simulation experiments show that the deviation of the instantaneous mixing ratio and the mixing ratio after 24 hours from the target value is less than ±0.5%, which meets the requirements of DL/T 2243—2021 standard.

Optimized Dispatch of Park Integrated Energy System with Thermoelectric Flexible Response under Green Certificate-Carbon Trading Mechanism

Xinglong CHEN, Ximin CAO, Jie CHEN, Jun LIU, Yuchao ZHANG, Hongyin BAO

2024, 57(6):  110-120.  DOI: 10.11930/j.issn.1004-9649.202308061

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In order to further improve the consumption rate of renewable energy and the low carbon and economy of the park integrated energy system (PIES), this paper proposes a low-carbon economic scheduling strategy for PIES, which considers the green certificate-carbon trading mechanism and the thermoelectric flexible response of combined heat and power (CHP) units. Firstly, a green certificate-carbon trading mechanism is established using the green certificate trading model and the stepped carbon trading model to improve the consumption of renewable energy within the system and decrease carbon emissions. Secondly, a thermoelectric flexible response model for CHP units is established by introducing the organic Rankine cycle into the system in combination with the conventional CHP units and electric boilers, thereby optimizing the system operations and providing greater application scope for the green certificate-carbon trading mechanism. Finally, with the goal of minimizing the total cost of the system, an optimization model of the PIES is constructed with consideration of the green certificate-carbon trading mechanism and the thermoelectric flexible response of the CHP units. The results show that the proposed strategy can improve the consumption rate of renewable energy, and reduce the carbon emissions and the total cost of the system.

Short-term Load Forecasting Based on DTW K-medoids and VMD Multi-branch Neural Network for Multiple Users

Yufei WANG, Tong DU, Weiguo BIAN, Zhao ZHANG, Huiting LIU, Lijun YANG

2024, 57(6):  121-130.  DOI: 10.11930/j.issn.1004-9649.202306104

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Multi-user power load forecasting refers to the power load forecasting of multiple users or regions based on historical loads data, which can make the grid companies understand the power demands of different users or regions, so as to better carry out the planning and scheduling optimization of the power system. However, different users have complex and diverse power consumption behaviors, so it is difficult to use traditional methods to universally model different power users' loads and achieve accurate prediction. Therefore, a new multi-user short-term load prediction model based on DTW K-medoids and VMD-multi-branch neural network is established. Firstly, in order to improve the clustering performance of traditional clustering methods, the DTW K-medoids method is used to cluster users' load data, and the distance between loads data is calculated using the dynamic time warping (DTW) instead of the traditional Euclidean distance measurement method in K-medoids to improve the clustering effects of multiple users' load. Secondly, in order to fully characterize the long short-term time series-dependent characteristics of load history data, a parallel load forecasting method based on VMD-multi-branch neutral network model is established for multi-user short-term load forecasting. Finally, the 365-day load data of 20 users in a region is used for clustering, training and experiment, and the results show that the MAE and RMSE indexes of the proposed model significantly decrease compared with that of the comparative models, indicating that the proposed method can effectively characterize the power consumption behaviors of multiple users and improve the prediction efficiency and accuracy of multi-user loads.

Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model

Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

2024, 57(6):  131-140.  DOI: 10.11930/j.issn.1004-9649.202306094

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To improve the prediction accuracy of multi-region power load, an ultra-short-term multi-region power load forecasting model based on Spearman-GCN-GRU is proposed with focus on the spatial-temporal correlation analysis of multi-region power data. Firstly, the Spearman correlation coefficient is used to analyze the spatial-temporal correlation of power load in different regions and construct the Spearman adjacency matrix. And then, the graph convolutional network (GCN) and gated recurrent unit (GRU) are used to respectively extract the spatial and temporal features from the data. Finally, the multilayer perceptron (MLP) is used to decode and output the prediction results. Through comparison with the distance adjacency matrix-based models, the Spearman-GCN-GRU model is proved to be feasible. In terms of prediction accuracy, the Spearman-GCN-GRU model are optimal in common evaluation indexes compared with traditional statistical models and neural network models. Specifically, in terms of the root mean square error (RMSE), the Spearman-GCN-GRU model exhibits a respective decrease of 13.90%, 11.66%, and 8.36% compared to the GRU, GCN and deep neural network (DNN) models, demonstrating its superior predictive performance.

Transmission Line Connection Fittings and Corrosion Detection Method Based on PCSA-YOLOv7 Former

Zhiwei SONG, Xinbo HUANG, Chao JI, Fan ZHANG, Ye ZHANG

2024, 57(6):  141-152.  DOI: 10.11930/j.issn.1004-9649.202305035

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The transmission lines are complex in distribution and it is difficult to effectively detect their faults. Among them, the connecting fittings are susceptible to corrosion and other faults due to their long exposure to complex environments. Aiming at the problem that the transmission line connection fitting components are varied in scale and have poor accuracy in detecting their corrosion faults, a detection method is proposed for transmission line connection fittings and their corrosion faults based on dual attention embedding reconstruction and Swin Transformer, i.e., PCSA-YOLOv7 Former. The experimental results show that the proposed method is superior to 12 existing state-of-the-art object detection algorithms in comprehensive detection performance of the constructed TLCF dataset, with the mAP_0.5 of the test set reaching 94.9 %. Compared with the baseline model YOLOv7, the proposed method improves the indexes F1 and mAP_0.5 by 2.6 percentage points and 2.2 percentage points, respectively, indicating that the proposed method can more comprehensively understand the multi-scale semantic information in the images of transmission line connection fittings and learn their subtle details that are difficult to distinguish.

Review of Icing Prediction Model and Algorithm for Overhead Transmission Lines Considering Time Cumulative Effects

Chuanqi WANG, Liwen WU, Zhibin DENG, Weifeng DENG, Bin YANG

2024, 57(6):  153-164, 234.  DOI: 10.11930/j.issn.1004-9649.202309061

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Under the meteorological factors of icing, the changes of icing thickness, shape and distribution on transmission conductor with time cumulation affect the safety operation of power grid system. Based on prediction models, this paper analyzes the association between various stages from icing growth to conductor deicing, and discusses the advantages of models and the possibility of mutual combination. The changes of icing from micro to macro in the whole icing circle affect the growth process of conductor icing. The prediction models can be combined based on the whole cycle. Firstly, the initial data is denoised to solve the data divergence, and the dimensionality reduction by the principal component analysis method can improve the prediction accuracy. Secondly, the combination and intercrossing mode of support vector machine, hybrid swarm intelligence optimization algorithm, genetic algorithm in the model focus on the identification and modeling of icing process. Thirdly, the application of thermal deicing techniques such as AC ice melting and eddy self-heating ring in the de-icing stage helps to form a dynamic closed-loop system for icing monitoring. Finally, an outlook is made on the research direction of icing prediction for transmission lines.

Integration of Digital Twin Model System for Ultra-high Voltage Converter Transformer Valve-Side Bushing

Yongsheng HE, Dan LUO, Zongxiang LU

2024, 57(6):  165-173.  DOI: 10.11930/j.issn.1004-9649.202402076

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An integrated design method of digital twin system is proposed to meet the practical application under real working conditions in this paper. Firstly, the functional requirements of the valve-side bushing digital twin system are analyzed. Based on these requirements, the framework of digital twin system is constructed. Secondly, the implementation methods corresponding to the digital twin system framework are designed and developed. Finally, the application of a valve-side bushing digital twin system is used to demonstrate and validate the proposed method. This method provides a design concept for the practical application of digital twin systems and can offer practical and effective solutions for the digital transformation of power grids.

Impact of Large Scale Distributed New Energy Access on Provincial Power Grid Stability

Jiawei LI, Guanyu ZHANG

2024, 57(6):  174-180.  DOI: 10.11930/j.issn.1004-9649.202405028

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Based on the transient characteristics of different types of distributed new energy, typical models are established and aggregated into active comprehensive load models, which can be used for safety and stability analysis of provincial power grids. The results show that the proposed method can effectively reflect the complex impact of the low voltage ride through and wave sealing characteristics of new energy on the stability of provincial power grids. Among them, the direct withdrawal of thermal power units from distributed new energy consumption operation will lead to a decrease in the stability of the power grid. When thermal power units are in peak shaving state, the impact on the transient stability of the power grid is relatively small.

Technology and Economics

Investment Decision Model of Rural Power Grid Projects Considering Contribution of Rural Revitalization

Huiru ZHAO, Manyu YAO, Bingkang LI, Guanglong XIE, Zhihua DING, Zhenda HU

2024, 57(6):  181-192.  DOI: 10.11930/j.issn.1004-9649.202306125

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Deepening the rural revitalization strategy puts forward higher requirements for rural grid development, quantifying the contribution of rural grid projects in the new era and assisting rural grids to achieve accurate investment become key. Based on the new requirements of the rural revitalization strategy for the development of modern rural power grids, a rural power grid contribution evaluation index system comprising four dimensions, including safety and relia-bility, precise service, green and low-carbon, and digital intelligence, is constructed, and the minimum cross-entropy model is used to combine the FUCOM-variance coefficient method to assign weights to the indexes and quantify the contribution of rural power grids by applying the weighted Marxian distance TOPSIS. With the objective of optimising the contribution of rural grid units and maximising financial benefits, a rural grid investment decision model was con-structed and solved based on the c-DPEA algorithm. The simulation results of a batch of 20 rural grid projects in a county show that the proposed quantitative model can scientifically evaluate the contribution of rural grid projects, and the investment decision model can provide an effective reference for precise investment in rural grid.

An Evaluation Method for Distribution Network Operation Based on Multi-source Data Deep Fusion

Junfeng QIAO, Aihua ZHOU, Lin PENG, Yiqing WANG, Xiaofeng SHEN, Sen PAN, Pei YANG, Chenhong HUANG

2024, 57(6):  193-203.  DOI: 10.11930/j.issn.1004-9649.202306073

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As the last link in the power supply process, the distribution network determines the quality of power supply services by its operational level. Scientific evaluation of the distribution network’s operational level is thus an important task for power supply companies. However, the existing evaluation methods are difficult to implement and apply due to the fact that the multi-source data are hard to be fused and the evaluation indicators are poor in reflecting the actual operation status of the distribution network. To address above-said problem, this paper proposes an evaluation method for distribution network operation based on multi-source data deep fusion. Firstly, the regional distribution network is divided into multiple grids, and then the address gradation based matching algorithm is used to fuse multi-source heterogeneous data. Based on the results, the distribution network operation evaluation index system is designed and a distribution network operation comprehensive evaluation model based on multi-layer weight constraints is constructed to obtain the distribution network comprehensive evaluation results. Finally, a distribution network operation evaluation system is developed to support the unified access of multi-source heterogeneous data from various business systems of the distribution network, achieving the visualization and intelligent application of distribution network evaluation functions. The proposed distribution network operation evaluation system is connected to the data center of a provincial power grid company for verification, and the accuracy and applicability of the proposed method have been verified with actual operation data.

Construction Experience of German Electricity Market Adapting to Energy Transition

Zhengnan GAO, Nan JIANG, Qixin CHEN, Jiang XU, Haili WANG, Li XIN, Qinggui XU

2024, 57(6):  204-214.  DOI: 10.11930/j.issn.1004-9649.202309049

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China is moving towards a cleaner energy structure. How to promote the high proportion of renewable energy consumption through market construction is the focus of energy structure adjustment. Many electricity markets of other countries have relatively rich experience in supporting the energy transition. Taking the German electricity market as a reference object, this paper summarized the process and effects of Germany's promoting the consumption of renewable energy, so as to provide useful reference for the construction of Inner Mongolia electricity market. Firstly, this paper compared the gap between Inner Mongolia and Germany in supply and total consumption of energy, and in installed capacity and consumption of renewable energy. Secondly, the paper introduced the German electricity price system and electricity market system, and analyzed the operation results of the German electricity market in adapting to the high proportion of renewable energy through the average absolute error index of the reference factors. Finally, it summarized the experience of German electricity market construction in policy and market connection, transnational market construction and regional self-balance mechanism, and put forward some construction suggestions that are adaptable to Inner Mongolia electricity market.

Research and Modelling of Bus Marginal Carbon Intensity for Power Systems Considering Network Losses

Jing WU, Xuanyu LIU, Xiang LI, Xiaoyan QI, Chengjun LI, Zhong ZHANG

2024, 57(6):  215-224.  DOI: 10.11930/j.issn.1004-9649.202305075

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Network losses and congestion have not been considered in the current macro carbon calculation method and carbon flow analysis method for power systems. To achieve precise analysis of carbon emission indicators for power systems, this paper proposes a model to calculate the bus marginal carbon intensity (MCI) of power system considering network losses. A MCI model is established based on coal consumption characteristics of thermal power units. Based on AC power flow model, a sensitivity model of network losses is established, and a calculation method is proposed to calculate the bus MCI of power systems. The method is further improved with consideration of network constraints. The IEEE 14-bus test system and a real 500 kV system are used to verify the correctness and applicability of the proposed model. The characteristics of MCI is analyzed under low carbon and non-low carbon dispatch modes. It is found that the positive and negative MCI of a bus is different when considering the network losses. The network factor also causes the differences of MCI of each bus. The model considering network losses can provide more accurate bus MCI information, which can be used to conduct more accurate real-time carbon emission analysis.

Generation Technology

Design and Operating Performance of Mechanical Draft Dry Cooling Tower Pre-cooled with Wet Medium

Mingwei WANG, Tiantian LIU, Qi GAO, Chunwei WANG, Jiyong SHEN, Shoufu LIU, Suoying HE

2024, 57(6):  225-234.  DOI: 10.11930/j.issn.1004-9649.202306029

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In order to solve the problem of insufficient output of mechanical draft dry cooling tower which can’t meet the cooling demand in summer, a mechanical draft dry cooling tower with wet medium pre-cooling inlet air system is designed in this paper. The influence of wet medium thickness, ambient temperature and humidity on the operating performance of the designed dry cooling tower and water-saving performance are carried out by using Matlab program. The results show that 300 mm CELdek7060 medium pre-cooling inlet air system has the best pre-cooling effect and the heat rejection rate of the cooling tower increases by 20.57% at the ambient temperature of 26 ℃ and humidity of 57%; the heat rejection performance of the dry cooling tower decreases with the increases of ambient temperature, and there is a critical temperature of 13.5 ℃; the wet medium pre-cooling system could improve the heat rejection rate of dry cooling tower by 96.96%, and further reduce the outlet water temperature by 2.80 ℃ at the ambient temperature of 35 ℃ and humidity of 57%; the wet medium pre-cooling system could improve the heat rejection rate of dry cooling tower by 81.14%, and reduce the outlet water temperature by 6.81 ℃ at the ambient temperature of 26 ℃ and humidity of 0%. The total annual energy-saving benefit of a single tower is about 138 400 yuan, which has good economic benefits.

Energy Conservation and Environmental Protection

Analysis on SO₃ Generation, Migration and Control Technology of Coal-fired Units

Dongxu LIU, Xiaoyuan ZHANG, Qing MA, Qianwei FENG, Zhen DU

2024, 57(6):  235-242.  DOI: 10.11930/j.issn.1004-9649.202304053

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In order to analyze the SO₃ emission characteristics of coal-fired units, testing the generation and removal of SO₃ for the 58 units, analyze the generation of SO₃ from combustion in the furnace, the conversion of SO₂/SO₃ from denitration system, and the removal effect of SO₃ for dry dust remover, wet desulfurization system, and wet dust remover, so as to obtain the rule of generation, migration, and removal of SO₃ in coal-fired units. The results show that the generation of SO₃ in coal-fired units is mainly composed of the combustion of coal sulfur and the conversion of SO₂ in the denitration system. The generation rate of SO₃ during furnace combustion is approximately 1% of the total amount of SO₂ generated during furnace combustion, and the conversion rate of SO₂/SO₃ in the denitration system is also at 1%. The electrostatic precipitator, electrostatic bag precipitator and wet desulfurization system have limited removal effect on SO₃. The removal efficiency of electrostatic precipitator, electrostatic bag precipitator and wet desulfurization system is 15%~25%, 20%~40% and 40%~60%. The low temperature dust remover and wet dust remover have high SO₃ removal efficiency. The SO₃ removal efficiency of low temperature dust remover is 50%~80%, and that of wet dust remover is 70%~90%. Therefore, the generation of SO₃ can be effectively controlled by controlling the sulfur content of coal combustion or the SO₂/SO₃ conversion rate of the catalyst in the denitration system. At the same time, low temperature dust collectors and wet dust collectors can be used to control the emission of SO₃, and SO₃ can be controlled below 10mg/m³ through the dry dust collectors, wet desulfurization system, and wet dust collectors.