23 July 2025, Volume 44 Issue 7
    

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    Special Issues for New Energy
  • XIA Xiaotian, YE Hua, QIU Qingquan, ZHANG Jingye, YIN Zhihao, NIE Zipan, LI Shuwei, LI Haoyuan, WANG Su, XIAO Liye
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 1-12. https://doi.org/10.12067/ATEEE2403036
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    With the ongoing penetration of renewable energy (RE) in power systems, power systems need to face many challenges brought by a large number of random fluctuation power access. The deep peak regulation for thermal power plants inevitably increases carbon emissions and reduces the unit lifecycle. To solve these problems, it is urgent to configure energy storage power stations at the source end of RE power stations. This can make the RE power station coupled energy storage systems have flexible characteristics in general. This paper proposes a source-end energy storage configuration method of RE power stations. The wind-solar power stations coupled energy storage systems are approximately equivalent to the thermal power unit in power and electricity.Combined with the solar, wind and load data of different provinces in China, the installed capacity of wind and solar power stations required for equivalent thermal power is determined according to the principle of intraday energy balance. On this basis, this paper combines with the operation characteristics of different energy storage power systems and optimize the energy storage capacity for the RE to generate consistent power with thermal power. Meanwhile, for the comprehensive utilization of regional wind and solar power stations, this paper considers the spatial-temporal complementarity of solar energy and wind energy. To verify the effectiveness of the method, the wind-solar power and load demands across northern regions in China are used for case analysis. The results reveal that the wind-solar power stations coupled energy storage systems can flexibly respond to the power and energy balance needs with daily load changes. Additionally, fully utilizing the spatial-temporal complementarity of solar and wind energy resources can reduce the demands for energy storage capacity of the system.
  • XIE Qian, XU Haolan, DANG Jian, WANG Xiaowei, ZHANG Gang
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 13-27. https://doi.org/10.12067/ATEEE2410019
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    Aiming at the problem of large fluctuation of wind-solar energy access to power grid, this paper studies the power distribution strategy of electro-hydrogen energy storage system based on multi-type electrolytic cell to stabilize wind-solar fluctuation, and the key role of this strategy in capacity optimization configuration. First of all, an electro-hydrogen energy storage system model is constructed. In order to enhance the applicability of the existing decomposition methods, a multi-granularity wind-solar power decomposition method considering time-of-use electricity price is proposed. Then, based on the operation characteristics of two types of electrolytic cells, a high proportion of hydrogen storage power allocation strategy based on multi-type electrolytic cells is formulated, and on this basis, an optimal capacity configuration model of electro-hydrogen energy storage system to alleviate the impact of wind and solar fluctuations is constructed. Finally, several comparative examples are analyzed. The results show that compared with the traditional single hydrogen storage power allocation method, the strategy proposed in this paper can effectively reduce the capacity and power allocation of electrochemical energy storage while strengthening the fluctuation suppression ability, improve the overall economy of the system, and highlight the leading role of hydrogen energy storage in the process of regulation and consumption.
  • LIU Zifa, WANG Shiqin, CUI Wenjin
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 28-37. https://doi.org/10.12067/ATEEE2407013
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    In the context of the “dual carbon” goals, to enhance energy utilization efficiency and reduce carbon emissions during system operation, a low-carbon economic dispatch model based on the carbon-green certificate linked trading mechanism is proposed for hydrogen-integrated energy systems. Firstly, the heat loss and waste heat recovery in the process of electrolysis hydrogen production are considered on the source side, and a multi-link hydrogen operation process model is established for hydrogen production from electrolyzer, hydrogen to methane, and hydrogen to cogeneration; secondly, a green certificate trading model is introduced to consider the mutual recognition between the green certificates and the carbon quota, and the carbon-green certificate linked trading mechanism is proposed, and a comprehensive demand response model that can be shifted and reduced is considered on the load side; finally, a low carbon economic dispatching model is proposed based on the cost of purchasing energy, green certificate linkage transaction cost and demand response compensation cost and minimum as the objective function to establish the optimal scheduling model. By setting up different operation scenarios for comparative analysis, the effectiveness of the model proposed in this paper is verified to realize the low-carbon economic operation of the integrated energy system.
  • WANG Wenzhuo, LI Wenran, WANG Zhiwei, WANG Bin, SU Biao, ZHANG Qiwen, XIONG Linyun
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 38-50. https://doi.org/10.12067/ATEEE2312012
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    This paper proposes an hourly robust dispatch scheme for the hybrid renewable energy generation systems with energy storage, which considers the transient stability constraint of synchronous generators, and achieves intelligent resolution of the optimization problem via a multi-agent system. Firstly, a dynamic ramp rate limit of the hourly generation plan is proposed to reduce the deviation between the actual dispatch and the rolling dispatch scheme, and to maximize the power sold to the grid while minimizing the curtailment of renewable energy; subsequently, an optimal dispatch model for the hybrid renewable energy systems is constructed, whose objective function is the ratio of the arbitrage revenue to the generation cost, taking into account the synchronous generators’ transient stability margin constraints, the energy storage system operation constraints, and the hybrid renewable energy system’s energy backup constraints. Meanwhile, the corresponding multi-agent system is established for the individual units in this optimization scheme, and the accuracy of renewable energy generation forecasting is improved via a recursive neural network and the principle of generation units clustering. Finally, the intelligent resolution of the optimization problem is realized. The effectiveness and superiority of the proposed method are verified by numerical simulation case studies under different seasons and load conditions.
  • LIU Ke, YANG Xingsen, YANG Miao, SHEN Haoning, DING Tao , YUAN Sen, ZHAO Zhonghua, ZHANG Limeng
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 51-61. https://doi.org/10.12067/ATEEE2310065
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    As the construction of the novel power system continues to advance, the cooperative development of source-grid-load-storage is inevitable. However, under the background of “dual-carbon”, the existing source-grid-load-storage cooperative optimization scheduling method does not take into account enough factors such as carbon emission. It is difficult to support the low-carbon development of the novel power system. In this paper, firstly, dynamic carbon emission factors are introduced to propose a low-carbon demand response mechanism driven by both benefits and low carbon, and a low-carbon demand response model is built to accommodate the economic cost and low carbon emission. Secondly, based on the theory of carbon emission flow, a source-grid-load-storage synergistic day-ahead economic dispatch model is constructed considering the carbon flow constraints, which helps the power system to operate with carbon reduction. Subsequently, in order to deal with the nonlinearities introduced by the consideration of carbon flow constraints, a decomposition method is used to deal with them, which is solved by alternating iterations of the two subproblems: low-carbon scheduling and carbon flow calculation. Finally, through the IEEE-14 node system, we implemented the cooperative optimization scheduling for source-grid-load-storage coordination considering low-carbon demand response. The results show that the proposed model and method can effectively balance the carbon and economy, and promote the cooperative development of each section of source-grid-load-storage in the context of the “dual-carbon”.
  • YI Derong, YAO Yiming, LIANG Jifeng, HU Bo, HOU Kaiwen, LI Chunyan
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 62-71. https://doi.org/10.12067/ATEEE2312045
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    Driven by the twin goals of carbon peak and carbon neutrality, the increasing penetration of renewable energy and the growing number of flexible loads introduce greater uncertainty into power system operation. How to generate accurate wind-solar-load scenarios to assist power system decision-making has become an urgent problem to be solved. However, at this stage, there lacks scenario generation method that fully considers the correlation between wind, solar, and load. In response to the above problems, this paper combines the bidirectional long short-term memory network (BiLSTM), multi-task learning (MTL) and Attention mechanism and a wind-solar-load scenario generation method is proposed. The data-driven method is used to mine the correlation between wind-solar-load historical data, extract common features, and retain differences, thereby improving the generalization ability of the model and improving the accuracy of scenario generation. The case study analysis shows that the scenario generation method proposed in this paper can greatly improve the accuracy of scenario generation, and can provide effective theoretical and method reference for medium and long-term planning of power systems.
  • SUN Yue, LUO Jinsong, LI Chen, HUANG Wei, XIANG Yao, WEI Yang, XU Jing, SHAO Changzheng
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 72-80. https://doi.org/10.12067/ATEEE2306024
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    This paper proposes a source-network-load collaborative planning model that considers source-load uncertainty. Firstly, an improved K-medoids method is proposed to extract typical scenarios of power grid source loads. Then, combined with the flexibility of demand response, a collaborative optimization configuration model of demand response and source network considering source-load uncertainty is constructed. Finally, a random two-level optimization algorithm based on Benders decomposition is proposed to realize the iterative solution of the optimal configuration model, so as to protect the privacy of information. Through the analysis of an improved IEEE 6-node system and IEEE 118-node system, it is proved that the proposed model can improve the system reliability and reduce the investment costs of transmission lines and conventional units.
  • LIU Yinqiao, ZHAO Haoran, LI Xiaomeng, TIAN Hang, HUANG Xiaoli, WANG Mengxue, WU Zengbin
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 81-89. https://doi.org/10.12067/ATEEE2408002
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    The district heating network is a crucial component of integrated energy systems. Its modeling and simulation process involves abstracting its actual structure and physical characteristics into appropriate mathematical models and solving them efficiently to simulate the operation of real systems and evaluate their performance. To address the inherent contradiction between error control and computational efficiency in traditional time-domain discretization methods, this paper focuses on the quality-regulated heating networks and innovatively proposes a semi-analytical modeling and simulation method based on time-space two-dimensional power series embedding, suitable for online applications. This method aims to meet the dual requirements of computational accuracy and efficiency for operational analysis. The case study results show that the proposed semi-analytical solution can significantly reduce analysis complexity and demonstrate remarkable advantages in accuracy and efficiency compared to conventional difference methods. Under similar computational costs, the simulation error of the semi-analytical solution is 0.55% (single pipeline scenario) or 0.004 2% (network scenario) of that of the difference method.
  • CHEN Wanzhi, DU Chao, WANG Tianyuan
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 90-98. https://doi.org/10.12067/ATEEE2501033
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    In response to the problem of low-accuracy short-term wind power prediction caused by the nonlinear and non-stationary characteristics of wind power time-series data, a short-term wind power network prediction model based on the Enhanced Multivariate Variational Mode Decomposition and the Good Periodic Snow Ablation Optimizer (EMVMD-GPSAO) was proposed. Firstly, the EMVMD is employed to decompose and screen key modal features from the original wind power and meteorological data, thus improving the quality of training data. Secondly, a network model integrating the Bidirectional Temporal Convolutional Network (BiTCN) and the Bidirectional Gated Recurrent Unit (BiGRU) are constructed. The GPSAO is used to optimize the hyperparameters of the model, and the Multi-Head Attention mechanism (MHA) is adopted to achieve adaptive weighting of time-series features. Finally, the predicted sequence output by the model is inverse-normalized to obtain the prediction results. Experimental results on scenario datasets demonstrate that the proposed model achieves a reduction of over 58.02% in MAE, over 4.52% in MAPE, and over 46.59% in RMSE, with R2 remaining above 0.99 across datasets. The four evaluation indicators all outperform those of comparative models, indicating higher prediction accuracy and generalization ability.
  • LEI Jinyong, LI Qinghui, YU Fengyuan, LI Chuang, OU Dingrong, TANG Yuan, DAI Peng, WANG Zesong, ZHANG Xiaoyan, LI Jiarong, LIU Feng
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 99-107. https://doi.org/10.12067/ATEEE2407017
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    Off-grid hydrogen production using offshore wind power is an economically effective way to utilize offshore wind energy. In offshore wind power off-grid hydrogen production projects, multiple alkaline electrolyzers often form clusters to absorb the wind turbine power. The power distribution strategy can significantly affect the energy efficiency and overall system lifespan. This paper proposes an adaptive power distribution strategy for offshore wind hydrogen production clusters, considering the degradation of individual units. This strategy broadens the operating power range of the hydrogen production cluster by flexibly managing the start and stop of units. It achieves optimal system energy efficiency by ensuring equal marginal output across units. The priority queue method, weighted by the number of starts and stops, determines which units to start or stop, ensuring consistency in the degradation levels across the hydrogen production cluster, thereby improving the overall system lifespan. Simulation examples with five 1 000 Nm3/h alkaline electrolyzers demonstrate that the proposed adaptive power distribution strategy can increase total hydrogen production by 2.1% and 4.2%, compared to average and stepwise power distribution strategies, respectively. Additionally, the number of starts and stops for each unit in the cluster is the same, effectively reducing the inconsistency in degradation levels caused by frequent power fluctuations in traditional power strategies.
  • ZHANG Zhaohui, XIE Zhiyuan, FU Hui, YANG Jinggang, XU Yang, GUO Jun, LI Hongtao
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 108-115. https://doi.org/10.12067/ATEEE2403025
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    In offshore wind power via VSC-HVDC systems, the surplus power generated after an AC grid fault can lead to overvoltage in DC cables. In order to prevent the generation of DC overvoltage, a DC Chopper is generally configured at the side of the receiver converter station, which is put into consumption of surplus power under fault conditions to realize the balance of the system’s power at the sending and receiving ends. In this paper, three DC energy consumption programs, namely, switching valve section series centralized resistor, distributed resistor, and sub-module series centralized resistor, were simulated and compared, and the topologies and working principles of the three types of DC Choppers were introduced. Based on the actual parameters of the Rudong offshore wind power via VSC-HVDC project, a system model was constructed under PSCAD/EMTDC to realize the working process of the above three DC Choppers. The characteristics and FRT performance during the operation of the three DC Choppers were compared, and the advantages and disadvantages of the three DC Choppers were analyzed. The research results show that the distributed energy consumption resistor scheme provides the best control effect but at the highest cost; the series-connected centralized energy consumption resistor for switch valve sections offers the worst control effect but at the lowest cost; the submodule series-connected centralized energy consumption resistor scheme falls between the two in terms of various indicators. This study can provide a reference for the selection of DC energy consumption devices in offshore wind farm VSC-HVDC grid-connected systems.
  • MIAO Yuesen, WANG Qianggang, LI Yun, SHEN Qianqian, XIAO Leiming, TANG Yunjin, LIAO Jianquan
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(7): 116-128. https://doi.org/10.12067/ATEEE2407016
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    The high proportion of distributed photovoltaic access to the distribution network brings uncertainty risks to the operation of the distribution network. A reasonable assessment of the accessible capacity of distributed photovoltaic systems in the distribution network has become an important research topic. Therefore, this paper first proposes a method for generating scenarios of joint source-load output based on an improved generative adversarial network. After generating a large number of scenarios based on the improved generative adversarial network model, the generated scenarios are reduced through the k-medoids clustering algorithm. Then, considering the flexible resources in the distribution network, an optimal power flow model for flexible distribution networks is established and linearized. Finally, a distributed photovoltaic capacity region solving method based on multi-parameter programming is proposed to characterize the accessible capacity range of distributed photovoltaic systems at different buses. Taking the improved PG&E 69 node distribution network system as an example for verification, the research results show that the proposed method can effectively characterize the distributed photovoltaic capacity region of flexible distribution networks considering flexible resources.