Table of Content

28 March 2026, Volume 59 Issue 3

Previous Issue   

Key Technologies of Local Energy System Operation Under Electric-Carbon Coordination

Low-carbon economic dispatch model of multi-region interconnected power system considering load low-carbon response capability

WEI Zhenbo, JIN Wenjie, ZANG Tianlei, ZHENG Jiaoyu, LUO Chenhao, ZHANG Xinyuan

2026, 59(3):  1-13.  DOI: 10.11930/j.issn.1004-9649.202510009

Asbtract ( )   PDF (1429KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Current demand response capabilities are limited to electrical loads, with intermediate variables existing in carbon emission characterization and poor consistency in calculation results. This leads to the incomplete exploitation of the carbon reduction potential on the user side. To address this issue, this paper proposes a low-carbon economic dispatch strategy for multi-region interconnected power systems that accounts for the load low-carbon response capability. First, a user-side low-carbon energy-use incentive signal is established to quantify the user-side low-carbon regulation effect. Second, a bi-level optimization model incorporating load low-carbon response capability is constructed for multi-region interconnected systems. The upper-level model is a cooperative game model based on the Nash bargaining theory, aiming to achieve the overall balance of wind and solar energy accommodation while ensuring the independent revenue of each regional entity. The lower-level model is a user-side low-carbon demand response model guided by coupling carbon emission factors, which is designed to enhance the low-carbon interaction between internal sources and loads in each region. Finally, a carbon-energy contribution factor is introduced to realize the fair distribution of benefits among different entities, thus ensuring the fairness and rationality of the proposed model under the market environment. Case study results show that, compared with the traditional low-carbon economic dispatch method for multi-region interconnected systems driven by electrical demand response, the proposed model can further tap the user-side low-carbon potential, effectively reduce the system carbon emissions, decrease the system operation cost to a certain extent, and guarantee the rationality of benefit distribution among all entities.

Coordinated dispatch of virtual power plant and distribution network considering multi-time scale carbon emission factors

WANG Zesen, WANG Xuanyuan, KONG Shuaihao, SUN Bohao, JI Zhen, SUN Wei

2026, 59(3):  14-26.  DOI: 10.11930/j.issn.1004-9649.202508039

Asbtract ( )   PDF (2268KB) ( )  

Figures and Tables | References | Related Articles | Metrics

With the advancement of dual-carbon goals, the low-carbon operation of power systems has become a research focus. However, the coordinated dispatch between virtual power plants (VPPs) and distribution networks (DNs) faces challenges due to insufficient multi-time scale carbon emission quantification. To address this issue, this paper proposes a coordinated dispatch model for VPPs and DNs that incorporates multi-time scale carbon emission factors. First, the phenomenon of renewable energy curtailment is integrated into the carbon emission factor calculation, and a multi-time scale correction mechanism is introduced to enhance the spatiotemporal accuracy of the carbon emission factors. Second, a coarse-fine tuning multi-time scale coordinated dispatch framework is established: the day-ahead scheduling prioritizes economic efficiency and security, while the intraday scheduling adjusts carbon emission factors and optimizes operational strategies based on real-time data. Finally, the model is solved using the analytical target cascading method. Case study shows that the improved carbon emission factor can effectively differentiate the accommodation differences of wind and solar power during zero-carbon periods. Compared with traditional carbon emission factor calculation methods, it reduces the DNs' carbon emissions by 4.7 tons and cuts carbon emission costs by 17.5%. The multi-time scale coordination mechanism significantly enhances the renewable energy accommodation capacity and economic efficiency, providing strong support for low-carbon dispatch of the power system.

Multi-level carbon emission factor correction considering non-grid-connected electricity

CHENG Tao, YANG Fuli, SU Yu, CHEN Wenli, YANG Zhenhua, XIANG Yue

2026, 59(3):  27-36.  DOI: 10.11930/j.issn.1004-9649.202509030

Asbtract ( )   PDF (1367KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Accurate carbon emission factors serve as the core basis for realizing the low-carbon transition of power systems. Currently, the average carbon emission factor of the power grid has coarse spatiotemporal granularity, while the carbon flow tracing methods struggle to meet computational requirements of massive nodes in actual complex power grids. Moreover, both overlook regional non-grid-connected electricity quantity. To address this, a multi-level regional carbon emission factor correction method considering non-grid-connected electricity quantity is proposed. Based on the electrical partitioning theory, this method constructs a solution framework for carbon emission factors and divides the actual power grid into three hierarchical structures (provincial-level, prefecture-level, and end-user level) from top to bottom according to voltage levels. A hierarchical and progressive strategy is adopted in the calculation of each level, ultimately attributing the environmental benefits of non-grid-connected electricity quantity to the corresponding nodes and dynamically correcting the carbon emission factors of grid-connected electricity quantity. Case studies at three levels (provincial, prefecture, and end-user) verify the feasibility of the method, achieving refined spatiotemporal granularity and fully accounting for the environmental benefits of distributed resources. It provides an engineering-practical technical pathway for carbon accounting of regional power systems.

Low-carbon scheduling decision method for industrial park users considering production characteristics

KONG Xiangyu, YANG Zhenyu, LIU Ziyu, GAO Bixuan, ZHUANG Zhong, DUAN Meimei

2026, 59(3):  37-47.  DOI: 10.11930/j.issn.1004-9649.202503003

Asbtract ( )   PDF (2442KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Under the "dual-carbon" goals and the construction of new power systems, industrial parks-as concentrations of energy-intensive enterprises-face significant challenges in achieving low-carbon and clean operation, which is critical for China to meet its national carbon targets. To address the low-carbon regulation requirements of industrial park users, a low-carbon scheduling decision method for industrial park users considering production characteristics is proposed. Firstly, we establish typical demand response regulation scenarios and operational frameworks for industrial parks. Considering the production processes of different industrial sectors, we develop an industrial user classification and screening method for multi-timescale response regulation. Subsequently, incorporating carbon emission reduction benefits into the optimization objectives, we formulate a demand response low-carbon scheduling decision model aiming at maximizing load aggregators' revenues. The model is solved using a modified whale optimization algorithm. Case studies demonstrate that the proposed method can effectively support load aggregators in formulating response regulation incentive schemes for industrial parks, achieving approximately 10% carbon emission reduction while maintaining aggregators' profitability.

Optimal scheduling of integrated energy system in industrial parks considering oxy-fuel combustion technology and demand response

QIN Yuming, ZHU Yun

2026, 59(3):  48-63.  DOI: 10.11930/j.issn.1004-9649.202507026

Asbtract ( )   PDF (2697KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Under the background of carbon peaking and carbon neutrality, the integrated energy system (IES) in industrial parks has attracted widespread attention due to its high flexibility and low carbon emissions. To further reduce carbon emissions of the industrial park IES and improve its economic benefits, we develops an optimal scheduling model for the industrial park IES, considering the cooperation between oxy-fuel combustion capture technology and power-to-hydrogen (P2H) technology, and the demand response mechanism. Firstly, the model improves system flexibility and reduces carbon emissions of thermal power units by retrofitting them with oxy-fuel combustion. Secondly, the introduction of cooperation between P2H and oxy-fuel combustion power plants not only increases the absorption capacity of wind and solar energy but also reduces the oxygen supply pressure of oxy-fuel combustion power plants. Then, the hydrogen blending equipment reduces energy loss during the energy conversion process, realizing the high-value utilization of hydrogen. Finally, the introduction of demand response further improves the flexibility of the IES and reduces carbon emissions, based on which a minimum-cost optimal scheduling model for the industrial park IES is established. Through a case study, it is found that the actual carbon emissions are 29.60% lower than the carbon quota, verifying the effectiveness of the proposed model. Sensitivity analysis is conducted to examine the impact of key variables on the industrial park IES.

Bidding operation strategies for charging stations considering various vehicle-grid interactive scenarios

WANG Shiqian, HUA Yuanpeng, LI Qiuyan, LIU Bo, YANG Jianping, XIANG Yue

2026, 59(3):  64-73.  DOI: 10.11930/j.issn.1004-9649.202501061

Asbtract ( )   PDF (1177KB) ( )  

Figures and Tables | References | Related Articles | Metrics

With the large-scale development of electric vehicles, charging load has gradually become the largest distributed adjustable resource in the power system. Investigating operational optimization strategies for electric vehicle charging stations' participation in vehicle-grid integration has crucial implications for the synergistic development of both the electric vehicle industry and the power grids. Firstly, considering the differentiated charging demand and energy consumption characteristics of EV users, a charging load prediction model based on order data is constructed to provide the basis for charging stations' participation in responsive energy management. And then, based on engineering factors such as current tiered subsidies and baseline differentials, a physical model is developed, and a more practically-oriented bidding optimization strategy for charging stations is proposed, which is designed to adapt to different vehicle-grid interaction scenarios, including both invitation-based and market-based modes. Finally, simulation analyses of charging stations participating in demand response under various scenarios are conducted based on actual order data. The experimental results demonstrate that the proposed model can effectively ensure the interactive revenue for charging stations while actively guiding electric vehicles to respond to grid regulation demands.

Power Market

The design of government-driven renewable energy contracts for difference in the UK electricity market and their implications for China

CUI Changjiang, LI Yupeng, DENG Wenli, LI Shimin, QIN Lijuan, JING Zhaoxia

2026, 59(3):  74-83.  DOI: 10.11930/j.issn.1004-9649.202409001

Asbtract ( )   PDF (2051KB) ( )  

Figures and Tables | References | Related Articles | Metrics

With the simultaneous advancement of new power systems and electricity spot markets, a critical challenge lies in ensuring the secure and orderly integration of new energy into the electricity market while establishing mechanisms that underpin its sustainable development. The UK's experience with contracts for difference (CfD) offers valuable insights in this context. This paper elucidates the key participants, primary processes, and fundamental concepts of the UK's CfD mechanism. Methodologies related to unit classification, administrative strike price calculation, contract allocation, and reference price determination are systematically summarized and analyzed. Building on this analysis, a government-driven CfD framework tailored to China's new energy development is proposed. Key recommendations emphasize the categorization of contracts into two types based on policy objectives, including transitional contracts to align with existing new energy support policies and proactive contracts to address new energy externalities. The objectives of contracts should focus on market power mitigation and the coordination of diverse market modes during the settlement trial phase. Reference price design is recommended to account for China's spot market structure and regulatory realities in medium and long-term transaction, while contract volumes are suggested to adopt ex-ante allocation modes.

Annual power purchase strategy considering multi-period sequential trading risks

LIN Guoxin, ZHANG Chao, FENG Kai, MA Jiahao, ZHANG Ning

2026, 59(3):  84-93.  DOI: 10.11930/j.issn.1004-9649.202508012

Asbtract ( )   PDF (1039KB) ( )  

Figures and Tables | References | Related Articles | Metrics

As a result of the sequential trading process, the decision-making of power purchasers is intercoupled across different trading periods. Therefore, power purchasers need to consider the trading risks in each period comprehensively and make power purchase decisions sequentially. However, the current power purchase strategies fail to consider the differences in the risks of power purchase costs across multiple trading periods, nor do they consider the intercoupling of multi-period power purchase decisions in the sequential trading process. To address this issue, this paper proposes an annual power purchase strategy considering the risks of multi-period sequential trading for power purchasers with a certain capacity for flexible regulation. Firstly, a set of multi-period scenarios is constructed, and the multi-period sequential trading risks are characterized based on the coupling relationships of multi-period sequential trading. Then, in accordance with the relevant provisions of the Shanxi electricity market, an annual electricity purchase decision-making model considering the risks of multi-period sequential trading is established. Finally, a case study is conducted to investigate the role of flexible resources in reducing electricity purchase costs and avoiding risks under the multi-period trading mechanism, as well as to analyze the impact of the scale of flexible resources on the allocation of electricity volume in each trading period.The results show that, compared with the strategy of allocating power volume among trading periods at a fixed ratio, the proposed strategy can reduce the annual power purchase cost by 1.65% and the annual power purchase risk by 1.41%.

Virtual power plant market trading strategy based on hybrid game reinforcement learning

ZHENG Feng, SUN Dian, HUANG Lili, YANG Feng, NI Yun

2026, 59(3):  94-102.  DOI: 10.11930/j.issn.1004-9649.202506047

Asbtract ( )   PDF (1121KB) ( )  

Figures and Tables | References | Related Articles | Metrics

With the rapid development of regional distributed energy, the issues of small installed capacity and strong output variability have become increasingly prominent, resulting in insufficient competitiveness when distributed energy participates in market transactions independently. To enhance its market participation capabilities, integrating distributed energy resources into virtual power plant has emerged as an effective approach. Therefore, this study investigates market trading strategies for virtual power plant incorporating distributed energy resources and proposes a trading strategy based on hybrid game-based reinforcement learning. First, establish revenue models for energy suppliers and load aggregators based on the operational characteristics of internal units within the virtual power plant. Then, to ensure the overall profitability of operators within the virtual power plant, a social welfare maximization model is established. Finally, the transaction model is solved using a hybrid game-based reinforcement learning algorithm combining Stackelberg and evolutionary game theory. Case studies demonstrate that the two-layer model based on hybrid game-theoretic reinforcement learning algorithms outperforms traditional intelligent algorithms, reducing computation time by nearly 50%. Furthermore, when virtual power plants participate in both energy markets and ancillary service markets, they can achieve higher returns.

Review and prospect of key technologies for anti/de-icing technologies of wind turbine blades

YAN Xinrong, TONG Yueping, MA Kuichao, ZHU Chunling, TAN Liping, ZHU Feihuan, XU Sida, SONG Shengnan

2026, 59(3):  103-113.  DOI: 10.11930/j.issn.1004-9649.202509033

Asbtract ( )   PDF (1923KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Ice accumulation on wind turbine blades can lead to power loss, affecting the safety of the units and the stability of the power grid. Through ice accumulation prediction on blades and ice prevention and removal measures, the impact of icy climatic environments on wind turbines can be reduced, which helps ensure the safe and stable operation of wind turbines. This paper reviews the key issues, research status, and development trends of icing prediction and anti/de-icing technologies for wind turbine blades, expounds on the mechanism and hazards of ice formation, summarizes the mechanism model method and data-driven method for ice accumulation prediction, analyzes the characteristics of passive ice prevention and removal technologies, active ice removal technologies, and collaborative ice prevention and removal technologies, and compares the advantages, disadvantages, and risks of various technologies. It provides an important reference for the further development of ice prevention and removal technologies for wind turbine blades.

New-Type Power Grid

Key parameter selection method for allocation of allowable harmonic current values

TAO Shun, CHEN Huilin, XU Yonghai, ZHOU Shengjun, XIAO Xiangning

2026, 59(3):  114-124.  DOI: 10.11930/j.issn.1004-9649.202506024

Asbtract ( )   PDF (1029KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Since its promulgation and implementation, GB/T 14549 has effectively regulated the harmonic issues in power grids and ensured the power quality. However, with the development of new power systems, the harmonics in power grids have exhibited new characteristics, making GB/T 14549 hardly fully adaptable to the current needs of power grid development and modern management. Therefore, aiming at the harmonic characteristics in new power systems, and based on allocation method for allowable harmonic current values specified in GB/T 14549, this paper focuses on the constraint index for total harmonic current, the selection method for power supply capacity, and the superposition method, respectively, and proposes the selection methods for key parameters. Its rationality and effectiveness are validated through the case studies, which effectively restricts harmonic injection and provides a reference for the revision of the national harmonic standards.

Clustering of substation load characteristics based on improved ISODATA algorithm

JIANG Dafei, AI Hongke, MENG Qiao, DONG Biao, WENG Yifan, ZHANG Qian

2026, 59(3):  125-133.  DOI: 10.11930/j.issn.1004-9649.202505079

Asbtract ( )   PDF (2387KB) ( )  

Figures and Tables | References | Related Articles | Metrics

The new power system's high-voltage distribution grid faces challenges posed by the large-scale and diversified connection of loads. Substation load clustering is a core method for accurately identifying user electricity consumption patterns and optimizing grid resource allocation. Its analysis results can directly support grid planning, demand-side management, and the formulation of renewable energy integration strategies. Therefore, it is urgent to conduct substation load curve clustering analysis to precisely analyze differentiated load patterns and their dynamic evolution patterns, thereby providing data support for intelligent distribution grid operation decisions. Addressing the limitations of the iterative self-organizing data analysis techniques algorithm (ISODATA), such as slow convergence speed and difficulty in capturing high-dimensional data features—particularly the insufficient capture of load data's dynamic characteristics—this study enhances the algorithm's ability to analyze high-dimensional features of substation load curves by optimizing the initial cluster center selection strategy and introducing a kernel function mapping mechanism. After completing missing value filling and data standardization preprocessing, this algorithm first optimizes the selection of initial clustering centers based on the maximum distance criterion to maximize the heterogeneity between initial centers and improve clustering stability. Second, it introduces a kernel function mapping mechanism to map load curves to high-dimensional space clustering, achieving explicit decoupling and clustering analysis of high-dimensional features. Simulation results indicate that in terms of feature extraction capability, the principal component analysis (PCA) feature space generated by the improved algorithm exhibits significant differences in the seasonal load characteristics of substations, enabling better capture of high-dimensional load features; In terms of algorithm performance, the improved algorithm reduces execution time by 32.8%, lowers the Davies-Bouldin Index (DBI) by 29.1%, and increases the Dunn Index (DI) by 42.9%, validating the effectiveness and superiority of the proposed algorithm.

Steady state modeling and loss suppression of urban transmission system based on improved multi conductor theory

DUAN Xiaoli, LIU Sanwei, YU Ting, FAN Xiangyu, SUN Ding, LI Huaqiang

2026, 59(3):  134-141.  DOI: 10.11930/j.issn.1004-9649.202509059

Asbtract ( )   PDF (1166KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Aiming at the problems of high grounding loss and sheath current risk in urban underground power transmission system, an improved multi-conductor modeling and intelligent impedance compensation strategy are proposed. In the modeling aspect, the transmission line is discretized into micro-element segments, and the node admittance matrix is constructed based on telegrapher's equation, and the matrix-level cascade algorithm with grounding nodes is introduced to solve the problem of diagonalization failure of the conventional propagation matrix in the of repeated eigenvalues, and the high-precision solution of the voltage and current distribution in the whole system is realized. The simulation results show that the proposed method can control the calculation error sheath induced voltage and circulating current within 1%, and provide technical support for real-time optimization and intelligent control in the operation and maintenance of power transmission system.

Hierarchical progressive identification strategy for DFIG parameters based on multi-timescale fault process partitioning

WANG Yu, WANG Tong, WANG Xiaotong

2026, 59(3):  142-155.  DOI: 10.11930/j.issn.1004-9649.202507006

Asbtract ( )   PDF (2285KB) ( )  

Figures and Tables | References | Related Articles | Metrics

To address the parameter identification problem of black-box models for doubly-fed induction generator (DFIG) wind turbines under multiple operating conditions, this paper proposes a hierarchical progressive parameter identification strategy based on the partitioning of multi-timescale fault process. Firstly, the model structure and parameters to be identified are determined according to the dynamic response characteristics of the black-box model. Subsequently, the sensitivity of parameters across different time scales is quantitatively analyzed using perturbation theory, and a hierarchical progressive identification method is established according to the dominant parameter response characteristics in different operational stages. Furthermore, by leveraging the differential response characteristics of parameters across hierarchical levels, the differential evolution method is adopted to realize adaptive identification of multiple parameters. Finally, a white-box model parameter identification method applicable to various manufacturers and models is developed. Comparative results show that the proposed hierarchical progressive identification strategy has good applicability and robustness under different operating conditions and for different models. Additionally, comparisons results with traditional parameter identification methods also demonstrate that the proposed approach exhibits superior rapidity and accuracy.

Performance analysis of a novel combined water bath dust collector with impingement water bath and spray string grid

CHENG Wei, ZHANG Yingmin, NIU Chao, YE Zaixian, ZHENG Yonggang, FANG Lijun

2026, 59(3):  156-164.  DOI: 10.11930/j.issn.1004-9649.202507044

Asbtract ( )   PDF (1758KB) ( )  

Figures and Tables | References | Related Articles | Metrics

Coal-fired power plants' coal handling systems generate substantial dust during operation. Improper purification treatment will cause severe environmental pollution. On the basis of research on water bath dust removal technology and spray string grid dust removal technology, this paper proposes a novel combined water bath dust collector integrating impingement water bath and spray string grid. The factors influencing the dust removal efficiency are analyzed by conducting numerical simulations on each dust removal stage. The results indicate that for the cross-section of the impingement water bath section, the higher the wind speeds and the deeper the initial immersion water depth of the air duct, the more intense the liquid fluctuation, correspondingly increasing dust removal resistance. In terms of spraying, the particle size of the ejected liquid droplets decreases with the increase of atomization pressure; however, an excessively high pressure leads to droplet agglomeration and an increase in particle size, resulting in a decline in dust removal efficiency. For the string grid, a local double-row string grid model is established to simulate the velocity and pressure field. The resistance loss is concentrated in the front and rear areas of the double-row string grids, and the high and low wind speed areas of the airflow are alternately distributed, forming a negative pressure zone. With the increase of wind speed, the negative pressure range expands accordingly, which is conducive to the formation of a water film on the string grids but also causes an increase in dust removal resistance at the same time. The combined design proposed in this paper integrates multiple purification mechanisms such as impingement water bath and spray string grid, and features high efficiency, low energy consumption and easy maintenance. It is particularly suitable for the dust environment with high-concentration and multi-particle size in the coal handling system, solving the problem of low removal efficiency of micron-sized dust by traditional mechanical dust collectors, and providing a modular solution for dust removal in coal handling system.