Electric Power

Analysis of the development experience of virtual power plants in Germany and its implications

WU Xiaoyu, CAO Yuchen, MENG Heli, LIU Lin

2026, 59(1): 1-9. DOI: 10.11930/j.issn.1004-9649.202408065

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With the rapid increase in new energy penetration, the power system faces difficulties in integrating new energy during off-peak load periods and challenges in ensuring power supply during peak load periods. As an emerging means for developing and utilizing demand-side resources, virtual power plants (VPPs) have attracted significant attention. German's VPPs have been in commercial operation for many years. In order to learn from its advanced experience, this paper analyzes the basic situation of Germany's VPPs development, including its background, development history, construction and operation entities, and main profit models; On this basis, the paper investigates the promoting effects of Germany's legal norms, market mechanisms, and electricity pricing policies. By comparing the current situation of China and Germany and summarizing the experience, relevant implications and suggestions for the development of VPPs in China are put forward.

Power-carbon-green certificate distributed cooperative optimization method based on flexibility support mechanism of active distribution networks

CAI Muliang, LAI Xinhui, LI Yingzheng, TIAN Ye, YU Jie, CHENG Minjun, XU Yinliang, LIN Chenhui

2026, 59(1): 10-19. DOI: 10.11930/j.issn.1004-9649.202505069

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The widespread integration of distributed renewable energy sources and virtual energy storage, such as electric vehicles, exacerbates the inherent uncertainty and low-inertia characteristics of power systems, thereby heightening frequency violation risks. Concurrently, the increasing flexibility and diversity of supply-demand dynamics within active distribution networks (ADNs) further complicate their interactions with transmission grids. To address these challenges, this paper proposes a novel power-carbon-green certificate distributed cooperative optimization framework based on the flexibility support mechanism of ADNs, with the objective of maximizing the utilization of distributed regulation resources and enhancing carbon reduction potential within integrated transmission-distribution (ITD) systems. Firstly, the dynamic frequency security constraints tailored to ITD systems and a flexibility support mechanism for ADNs based on interactive regulation modeling are established, forming a comprehensive ITD electricity-carbon-green certificate cooperation framework. To effectively address the uncertainty inherent in subsystems, joint chance constraints (JCCs) are employed to model the probabilistic nature of the problem. The Alternating direction of multipliers algorithm (ADMM) algorithm is adopted for the distributed cooperation of the transmission and distribution system. Case studies demonstrate the effectiveness of the proposed method in fully leveraging distributed resources and enhancing system frequency security. The framework also exhibits the ability to flexibly reflect the external support capacity or supported demand of ADNs. Compared to the transmission-grid independent dispatch model, the total operation cost is reduced by 13.42%, while renewable energy curtailment is decreased by 16.76% relative to the model that ignores multi-market coupling. These results demonstrate significant improvements in both the operational economy and low-carbon performance of the system. Furthermore, the proposed method achieves a reduction of approximately 98% in computational time compared to the traditional sample-average approximation (SAA)-based approach, thereby facilitating rapid distributed coordination within ITD systems.

Economic analysis of virtual power plants incorporating distributed energy storage in carbon-green certificate trading mechanisms

ZHANG Min, GUO Xiangyu, CHANG Xiao, YAO Hongmin, ZHANG Shifeng, WU Yingjun

2026, 59(1): 20-32. DOI: 10.11930/j.issn.1004-9649.202505072

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Under the dual-carbon goals, achieving the synergistic optimization of economic and environmental benefits in virtual power plants is crucial for the green transformation of the energy system. However, current research still faces two major challenges: the optimization models struggle to balance economic and environmental benefits simultaneously, and the solution methods tend to be conservative with poor convergence. To address these issues, a low-carbon economic dispatch model for virtual power plants incorporating distributed energy storage under a carbon-green certificate trading mechanism is proposed. First, moving beyond the limitations of single trading mechanisms, a risk-aware carbon-green certificate synergistic trading mechanism is constructed to maximize emission reduction revenue and economic benefits. Second, leveraging the advantages of distributed energy storage in enhancing economic efficiency and renewable energy consumption rates, the potential of the carbon-green certificate mechanism is further exploited by establishing a diversified source virtual power plant optimization model that includes distributed storage. Finally, to overcome the conservativeness and poor convergence of traditional solution methods, the black-winged kite algorithm is introduced to improve solving efficiency. Simulation results demonstrate that the proposed model significantly increases the renewable energy consumption rate and net system profit while effectively reducing carbon emissions. Compared to a single carbon trading mechanism, it achieves up to a 33.9% increase in net profit and a 16.6% reduction in carbon emissions, with faster iteration speed and stronger convergence stability, validating the algorithm's effectiveness in handling high-dimensional nonlinear constrained problems.

Multi index fusion reliability evaluation method for virtual power plants considering the dynamic characteristics of energy storage

WANG Huidong, NI Linna, LU Pengfei, CHENG Ying, WU Yingjun

2026, 59(1): 33-43. DOI: 10.11930/j.issn.1004-9649.202505077

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As a core hub for aggregating multi-source "generation-storage-load" resources, the reliability assessment of Virtual Power Plants (VPPs) is crucial for the stable operation of power systems and the absorption of renewable energy. Current assessment methods have two limitations: first, they adopt static energy storage models, which struggle to reflect the dynamic characteristics of devices; second, the evaluation indicators fail to quantify the power output stability during the power supply process. To address this, a multi-indicator integrated reliability assessment method for virtual power plants considering the dynamic characteristics of energy storage is proposed. Firstly, a dynamic energy storage model is constructed based on the capacity degradation and efficiency deterioration characteristics of energy storage devices during charging and discharging processes. Secondly, multiple energy sources such as wind power, photovoltaic power, adjustable loads, and grid transactions are integrated to build a virtual power plant model that reflects the collaborative operation of "generation-storage-load". Finally, focusing on power supply stability and renewable energy absorption efficiency, two indicators—Mean VPP Export Power Stability (MVPPE) and Expected Renewable Energy Not Used (ERENU)—are proposed. Combined with traditional indicators including Loss of Load Probability (LOLP) and Expected Energy Not Supplied (EENS), a reliability assessment system for virtual power plants considering the dynamic characteristics of energy storage is established. Simulation results show that compared with the traditional static energy storage model, this method increases MVPPE by 14.5% and reduces ERENU by 88.7%, which can more truly reflect the reliability level of VPPs and provide a scientific basis for their planning, operation, and optimization.

Probabilistic assessment of supply-demand balance capability in new power systems for extreme high temperature scenarios

ZHENG Haifeng, LIU Qing, YAO Li, ZHANG Yu, ZOU Yichao, HU Zhenda, WANG Yang, DAI Tanlong

2026, 59(1): 44-56. DOI: 10.11930/j.issn.1004-9649.202504041

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Under the background of global warming, the frequency, intensity and impact range of extreme high temperature weather continue to expand. Coupled with the continuous increase in the number of air conditioners and the increasing proportion of installed capacity of wind and solar power, the impact of extreme high temperature on the power supply-demand of new power systems is becoming increasingly significant. A probabilistic assessment method for supply-demand balance capacity of new power systems is proposed and applied to the medium and long-term power system production simulation. Firstly, a set of joint wind-solar-load scenarios is constructed based on a three-dimensional Gaussian Copula function to characterize the relationship between variables. Then, integrated with a power system production simulation model, the dispatch strategies of generation units and the utilization of demand-side resources are optimized aiming at minimizing the operational costs. Finally, an assessment index system for supply-demand balance capability is established, encompassing the dimensions of security & adequacy, flexibility & controllability, cleanliness & low-carbon, and economic efficiency.The analytic hierarchy process (AHP) is employed to set the weights for these indicators, and the kernel density estimation (KDE) is adopted to generate the probability density curve of the supply-demand balance capability, which reveals its probabilistic distribution characteristics and quantifies the likelihood of occurrence for different levels of balance capability. This method is applied to a province in South China to conduct studies for the years 2030, 2040, and 2050. The results indicate an overall enhancement in the supply-demand balance capability of the new power systems, primarily driven by improvements in the flexibility & controllability and cleanliness & low-carbon dimensions. The specific outcomes of the province by 2050 include an increase in the utilization rate of pumped storage to 34.6% and a reduction in the carbon emission intensity per unit of electricity to 0.27 kg/(kW·h). Conversely, a decline is observed in the security & adequacy and economic efficiency dimensions. By 2050, the average reserve margin is projected to decrease to 7.1%, while the average levelized cost of electricity is expected to rise to 0.56 RMB yuan/(kW·h)

The machine-recognition technology path of standard digital transformation in the field of smart energy

LI Wenwen, LIYAN Ruoyue

2026, 59(1): 57-65. DOI: 10.11930/j.issn.1004-9649.202506055

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Smart energy is one of the most important directions of energy revolution and transformation. Its standardization can provide strong support for technology advancement and industrial development in energy field. In the context of the overarching trend of digital development, the digital transformation of standards has also become an inevitable trend. This paper conducted research on machine-recognition technology pathways for the digital transformation of standards in the field of smart energy. A pathway was established, which includes the development of a general standard information model, the creation of extensible label set mapping rules, standard format conversion, verification and evaluation using the verification tool, and standard optimization feedback. Four international standards of smart energy were selected for practical implementation. The transformation and validation of the identifiable levels of these four standards were completed, and the maturity and applicability of the identifiable levels were evaluated. The results show that the maturity and applicability of the identifiable levels of the four standards are high. This study provides a feasible technology pathway for the initial stage of digital transformation of standards in the smart energy field and serves as an important reference for standard digitalization research and practice in related fields.

Diffusion model-based background traffic generation for power grid digital systems

SUN Xuan, QIAO Mengyan, LI Jun, SHEN Liyan, DAI Haiying, HAO Nan, CHANG Qicheng, ZHOU Hao

2026, 59(1): 66-75. DOI: 10.11930/j.issn.1004-9649.202507021

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To address the limitations of current background traffic generation methods in power communication—particularly in modeling protocol behaviors, capturing temporal dependencies, and controlling traffic category distributions—this paper proposes a background traffic generation approach based on diffusion models and bidirectional flow (DMBF). By employing transforms basic flow data into an intuitive picture (FlowPic), we extract bidirectional session images featuring directionality, temporality, and packet-length coupling characteristics. This is combined with a Transformer for temporal modeling. A conditional control mechanism is introduced to adjust the generation ratios of different traffic types, enabling the diffusion model to generate background flows under guided conditions. To evaluate the practicality and generalizability of the proposed method, experiments are conducted on datasets comprising both publicly available traffic samples and real-world network communication data, covering a range of typical business scenarios and interaction patterns. Experimental results show that DMBF outperforms traditional generative adversarial network approaches in terms of generation accuracy and distributional consistency. JSD decreased to 28.89%, with MAE and RMSE at 26.24% and 30.91%, respectively.

Revenue calculation for 630 MW supercritical steam-supply combined heat and power unit

DING Yi, WANG Chunliang, XI Yuewei, HU Wenyan, YANG Zhiping, GUO Xiyan

2026, 59(1): 76-83. DOI: 10.11930/j.issn.1004-9649.202505035

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This study investigates the industrial steam extraction heating benefits of 630 MW supercritical combined heat and power (CHP) units. Combined with the electricity spot market, it proposes a heating benefit analysis framework coupled with electricity market prices. Using the power generation loss compensation method, a heating revenue calculation model is established that comprehensively considers steam sales revenue, power generation loss, makeup water cost, and fixed asset depreciation of heating systems. Electricity price sensitivity analysis is introduced to accommodate spot market volatility. Validated through EBSILON software modeling (error ＜ 1%), the study analyzes the heating revenue patterns under different extraction steam flows (97.2~561.6 t/h). The results demonstrate that the heating economics exhibit dynamic response characteristics in electricity market environments, with main steam flow, extraction steam flow, electricity price fluctuations, and thermal pricing policies forming a four-dimensional influencing factor system. Analysis of typical spot market scenarios indicates that when day-ahead market clearing prices exceed 0.4283 CNY/(kW·h), the units shall prioritize switching to pure condensation mode. During low-price periods in real-time markets, heating load can be increased up to 1950 t/h main steam flow conditions, achieving unit heating revenue of 35.80 CNY/t-steam. Sensitivity analysis reveals asymmetric price transmission mechanisms. The proposed model provides a quantitative decision-making tool for CHP units participating in day-ahead and real-time bidding and formulating heat-electricity coordinated pricing strategies in spot market environments.

Fault current calculation method for multi-terminal DC distribution networks considering multiple distributed generation

JIA Dongli, REN Zhaoying, LIU Keyan, YE Xueshun, LI Yuetao, XU Limei

2026, 59(1): 84-96. DOI: 10.11930/j.issn.1004-9649.202508038

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In DC distribution networks, short-circuit faults can cause the current to rise to several times the normal operating level in an extremely short period, posing severe challenges to system protection and safe operation. The presence of multiple distributed generators (DGs) in DC distribution networks and the diversity of their grid-connected converters as well as the complex coupling relationships make it difficult to analyze fault characteristics and accurately calculate fault currents, which is unfavorable to the design of protection strategies. To address this issue, this paper proposes a fault current calculation model for DC distribution networks with multiple DGs. First, a fault equivalent circuit of the voltage source converter (VSC) is established, and the fault response characteristics of PV Boost converters, distributed wind power machine-side converters (MSC), energy storage dual active bridge (DAB) converters and VSCs are analyzed to construct multi-scenario fault equivalent circuits. Second, proceeding from the multi-stage transient response process of fault current, a fault current calculation model is built, covering the initial steady-state stage before fault, DC bus discharge stage, diode freewheeling stage and steady-state stage after fault. Then, based on the established multi-stage fault current calculation model, the key factors affecting the peak fault current are analyzed. Finally, taking a multi-terminal DC distribution network with multiple DGs as an example, the theoretical calculation results are compared with the Matlab/Simulink simulation results to verify the accuracy of the proposed model.

Security defense strategy for distribution-microgrids based on dynamic programming

XI Zeli, CHEN Cong, YANG Xinsen, ZHAN Ximei, GUO Guowei, ZHANG Qian

2026, 59(1): 97-104. DOI: 10.11930/j.issn.1004-9649.202507101

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The new distribution system based on the information-physical fusion structure provides a new technical path for the optimization and dispatch of multi-energy complementary energy, the strong uncertainty of multi-energy output and unknown disturbances make it difficult for power generation to be precisely regulated, which seriously threatens the safe and stable operation of the system. address this challenge, an optimal security defense strategy with dynamic programming is proposed by integrating asymmetric structure modeling. The unknown uncertainty disturbance and the asymmetric structure problem on the defense side are unified into non-cooperative game framework and are solved by using an adaptive evaluation learning network, which implements the optimal allocation of defense resources. Simulation results show that the proposed strategy can effectively the uncertainty security risk under asymmetric structure.

Improved fault protection strategy for active distribution networks adapting to high proportion photovoltaic access

WANG Shuai, JIA Dongli, LIU Keyan, YE Xueshun, SHENG Wanxing

2026, 59(1): 105-114. DOI: 10.11930/j.issn.1004-9649.202506057

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With a large number of photovoltaic (PV) access, the traditional distribution network has changed from a single power source to a multi- source structure. There is intermittence and uncertainty in PV, and it is easy to have the problem of false tripping in current protection when using traditional setting strategy. By the output characteristics of PV and actual measurement data, typical scenario data sets are generated based on the generative adversarial network (GAN) algorithm, and different fault scenarios are constructed. An improved current protection strategy is proposed to adjust the current protection setting coefficient in real time. The active distribution network model is built and compared with the traditional current protection strategy under 3 working conditions It can be seen from the example simulation: The overall false tripping rate of the proposed strategy is reduced by 25%, which is more advantageous than the traditional current protection.

Active damping strategy based on current feedback for LCL-type grid-connected inverters with PV-storage systems

RAN Chengke, TAN Lu, CAO Zhihui, ZHAO Xiaoyue, LI Zhenrong, XIA Xiangyang

2026, 59(1): 115-123. DOI: 10.11930/j.issn.1004-9649.202408046

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With the continuous rise in photovoltaic(PV) penetration, the problem of inherent resonant frequency offset of LCL filters caused by PV-storage grid-connected systems has become increasingly prominent, which has evolved into a key bottleneck restricting the stable operation of the systems. An inverter-side current feedback active damping (ICFAD) strategy is proposed. Firstly, the small-signal transfer function of the inverter connected to the grid via the LCL filter under this strategy is established. Secondly, the fmincon function is adopted to search for the optimal damping factor of the transfer function. Finally, the optimal parameters of the active damping controller are designed based on the search results. This strategy can effectively suppress the shifted resonant peaks of the system while overcoming the limitations in solving the characteristic roots of the third-order systems. Simulation results demonstrate that the proposed control strategy exhibits resonant suppression performance under different short-circuit ratios of the power grid, thus effectively improving the operational stability of PV-storage grid-connected systems.

Coordinated control strategy for multi-type energy storage participating in power system frequency regulation

LIU Jiayu, LIANG Xiaobin, HUANG Xifang, ZENG Xingxing, WANG Yu, CAO Yang

2026, 59(1): 124-132. DOI: 10.11930/j.issn.1004-9649.202509060

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A synergistic control strategy is proposed considering the participation of multiple types of energy storage in the power system frequency regulation to address the issue of low-inertia system's difficulty in coping with the frequency fluctuations caused by the high proportion of new energy access. Firstly, the frequency change rate signal is processed by a low-pass filter to realize the coordinated control of electrochemical and flywheel energy storage. Then, combined with the coordinated control model of multi-type energy storage, the fluctuation of new energy output and the lagging response characteristics of traditional thermal power units, the system frequency response (SFR) model is established. Next, a control strategy model for energy storage system participating in the secondary frequency adjustment is constructed, and differentiated charging and discharging strategies are formulated to balance the immediate and long-term regulation needs. Finally, verification is conducted on the simulation platform, and the proposed strategy can improve the transient recovery speed of the system frequency by 44.3%, which helps to enhance the frequency stability of the power system.

Thoughts and practices on the construction of the electricity price transmission system in Zhejiang power market

LIU Weidong, DENG Hui, JIA Xing, ZHUANG Xiaodan, CHEN Mengyao, LI Zhiyi

2026, 59(1): 133-142. DOI: 10.11930/j.issn.1004-9649.202508060

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With initial progress in China's power market system construction, the market-oriented pricing mechanism for electricity has been gradually improved. Market-oriented electricity price signals, formed through competition among power generation enterprises, power selling companies and other entities, are transmitted through wholesale, retail and other links to end users. Their effectiveness and stability will be an important criterion for evaluating the comprehensive construction of the power market. Against this backdrop, we first summarize the development of domestic and international power market price systems and key issues in price transmission system construction; then, from Zhejiang's perspective, we sort out core ideas and practical experience of its price transmission system, and discuss future development, aiming to provide references for building a market-oriented price system reflecting electricity's multiple values.

Voltage source equivalent model of offshore direct current wind turbine based on LLC resonant converter

NING Yujie, HU Shuju, CHEN Yijing, LI Chunhua, LI Fenglin, ZHAO Dawei

2026, 59(1): 143-152. DOI: 10.11930/j.issn.1004-9649.202501008

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Offshore wind farms adopting a DC collection scheme can avoid overvoltage problems caused by the capacitive charging effect of undersea cables, and also eliminate the need for bulky power-frequency transformers, representing an important direction for future development. This paper firstly establishes a detailed model of an offshore direct current (DC) wind turbine based on the LLC resonant converter and designs an integrated control strategy for the turbine unit. Then, based on the averaging model and the operating principles of the LLC resonant converter, the detailed model is simplified to obtain an equivalent voltage source model. Finally, a comparative analysis of the dynamic characteristics is conducted under various operating conditions among the equivalent voltage source model, the detailed model, and the existing current source equivalent model established in previous studies, verifying the accuracy of the former. The established model holds practical reference value for conducting stability analysis on the integration of offshore DC wind farms into the main power grid.

An optimization method for imbalance funds in a multi-agent game-theoretic electricity market

WANG Jiang, CHEN Xiaodong, XU Zhe, WANG Jingliang, WANG Lipeng

2026, 59(1): 153-162. DOI: 10.11930/j.issn.1004-9649.202409028

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As China's power market reforms advance, pilot regions across the country have encountered imbalance funds of different scales during actual settlement processes in their spot power markets. This significantly impacts the profitability of each market participant and reduces market efficiency. Therefore, this study proposes an optimization method for allocating power market imbalance funds based on multi-agent games. Considering significant differences among provinces in medium-to-long-term trading rules, energy structures, and spot market development, an Agent-Based Model (ABM) is employed to characterize market participants such as system operators and power generators. Reinforcement learning is used to explore the behavioral decisions of these participants under different allocation methods. Second, within the Stackelberg game framework, we uncover the endogenous evolutionary mechanisms of market participants under different allocation methods, evaluating the impact of multiple imbalance fund allocation approaches on market efficiency and other metrics. By leveraging ABM and reinforcement learning to capture the interactive characteristics among multiple market participants and constructing endogenous evolutionary mechanisms to simulate risk-averse behaviors, this approach facilitates the identification of province-specific, optimized imbalance fund allocation proposed methods, thereby preventing resource misallocation. The results of the calculation examples show that the ABM algorithm and endogenous evolution mechanism fully reflect the behavioral strategies of market entities. When the imbalance fund allocation proposed method causes partial capital outflow, the incentive compatibility indicator reaches 0.22, and all market entities exhibit a strong conservative stance. When the imbalance fund allocation proposed method guides market entities through spread penalties, all market entities adopt proactive strategies, effectively improving market operational efficiency.

CNN-BiGRU-ATT multi-branched distribution network fault location based on multi-dimensional fault feature extraction

ZHANG Yumin, WANG Delong, ZHANG Xiao, JI Xingquan, ZHANG Xiangxing, HUANG Xinyue, WANG Xuelin

2026, 59(1): 163-174. DOI: 10.11930/j.issn.1004-9649.202507050

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To address the difficulty in fault feature extraction for multi-branched distribution network fault location under weak fault conditions, this paper proposes a fault location method based on multi-dimensional feature extraction, which integrates the convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and attention mechanism (ATT). Firstly, the traveling wave characteristics of different fault locations and fault branches are analyzed. A wavefront calibration method based on the line segment detector (LSD) is employed to extract information features such as the coordinates, amplitudes, and slope of fault wavefronts, and principal component analysis (PCA) is used to construct a multi-dimensional fault-feature space that maps to fault locations. Then, a CNN-BiGRU-ATT fault location model is established to deeply explore the correlations between temporal features, amplitude features, and fault locations. Finally, classification and regression tasks are integrated to achieve both fault section identification and precise fault location. Under the condition of limited samples, the fault section location accuracy reaches 99.6429%, the accurate location error is 55.77 m, and the cross-condition error is as low as 2.95 m. The results show that the proposed model can effectively correlate multi-dimensional fault features with fault information, and exhibits superior stability of fault location accuracy and scenario generalization ability compared with the comparative models.

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