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最新刊期
卷 47 ， 期 9 ， 2023
- 摘要：The power industry is the largest industry for coal consumption and carbon emission in China. Real-time, accurate, and comprehensive measurement of electric power carbon emission is the basis and premise for estimating the potential of electric power carbon emission reduction, incentivizing power consumers to reduce carbon emission, and supporting the data foundation of carbon markets. Therefore, based on the “three abilities” principle of “measurability, reportability, and verifiability” proposed by the United Nations Framework Convention on Climate Change, a carbon measurement method for the whole chain of the power system is proposed. The framework is based on the theory of the carbon emission flow for the power system and realizes the “minute-level” real-time carbon measurement and “consumer-level” precise carbon measurement on the generation-transmission-load sides. On this basis, the carbon measurement system for the whole chain of the power system is designed. The basic concept and implementation form of the power carbon meter system are introduced in detail. The simulation verification is carried out based on the actual system operation data and load data of Changzhou City, Jiangsu Province, China. The simulation results verify the effectiveness of the proposed method. Finally, the key issues that need to be further studied in the field of carbon measurement of power system are prospected.关键词：carbon measurement;carbon accounting;carbon emission flow;carbon meter system;electric carbon platform;carbon emission factor2|0|0更新时间：2025-06-16
- 摘要：Under the target of carbon emission peak and carbon neutrality, energy conservation and emission reduction has become the primary task for energy reform in China. The macroscopic measurement of carbon emission can no longer satisfy the in-depth study on carbon emission from energy system. The detailed description of carbon emission characteristics of the energy consumption side can further guide users to realize low-carbon energy consumption. A carbon trajectory tracking method of the electric-thermal interconnected integrated energy system (ETI-IES) is proposed based on the carbon entropy index. Firstly, this paper introduces the concept of “carbon entropy” based on the similar characteristics of “entropy” and “carbon emission” to describe the disorder of carbon emission with energy flow and study the carbon entropy relationship between the energy supply side and the demand side. Secondly, based on the superposition of electric and thermal systems, this paper establishes a carbon entropy model of the ETI-IES to form an explicit expression of the relationship between carbon source and load, to track the carbon emissions in ETI-IES and calculate the carbon index of the demand side under multi-energy supply, as well as to analyze the carbon entropy component of a single carbon source. Finally, an example of ETI-IES in a region of Jilin Province of China is used for arithmetic analysis to verify the advantages and effectiveness of the carbon entropy model.关键词：carbon entropy;integrated energy system (IES);carbon emission;carbon trajectory tracking;low-carbon energy consumption2|0|0更新时间：2025-06-16
- 摘要：In order to promote the power industry to achieve the low-carbon target, the reasonable and effective power system planning is very important. The participation of demand response in the power system planning is an important means to reduce system carbon emission. To this end, a power system bilevel low-carbon planning model considering carbon emission flow and demand response is designed. The upper-level planning model is the investment planning model, which aims to minimize the sum of investment cost and operation cost, embeds the annual 8 760 h sequential operation simulation model, and adopts the unit clustering linearization method to model the traditional coal-fired unit, so as to coordinate and optimize the construction capacity of traditional unit, renewable energy and energy storage. According to the unit output and line power flow data calculated by the upper-level model, the lower-level model forms a demand response model based on the carbon emission flow theory and the load-side step carbon price mechanism, and reasonably adjusts the load distribution to reduce the carbon emission and carbon emission cost. Finally, the proposed model is analyzed and verified on an modified IEEE RTS-24-bus system.关键词：power system planning;carbon emission;unit clustering linearization;demand response;step carbon price2|0|0更新时间：2025-06-16
- 摘要：This paper establishes an optimal dispatching model of the park-level integrated energy system based on a dual game of supply and demand sides. Firstly, the concept of the carbon-to-charge ratio of energy storage and the principle of carbon emission balance during a dispatching period are introduced, and an augmented carbon emission flow model is established. Based on the model, the carbon-oriented pricing mechanism is implemented in the park, and the bilevel game model between the park and its users is established. Besides, Nash bargain model is adopted to simulate the gaming behavior of various entities participating in carbon trading market among multiple parks, so as to form a dual-game mechanism. A data-driven two-stage robust optimization combined with adaptive alternating direction method of multipliers is used to solve the problem. The optimal trading volume of carbon quota and trading price can be obtained. Finally, the case simulation results show the correctness of the proposed augmented carbon emission flow model and the role of pricing mechanism based on carbon emission flow in reducing carbon emission. At the same time, the effect of carbon trading market and carbon capture on different resource endowment entities as well as the effectiveness of the adopted algorithm is analyzed in this paper.关键词：integrated energy system;optimal dispatching;carbon capture;carbon trade;dual game;carbon emission flow;Nash bargain model2|0|0更新时间：2025-06-16
Power System Analysis and Optimization from Carbon Perspective
- 摘要：The conversion of energy with different qualities in an integrated energy system (IES) and the uncertainty of source and load on the background of high proportional renewable energy integration both increase the energy unavailability of the system. To analyze the energy unavailability in the above scenarios in a unified and quantitative way, based on the network properties of IES, the entropy state mechanism and analysis method of IES for the renewable energy integration are proposed. Based on the IES exergy flow mechanism model, the IES thermodynamic entropy increase mechanism model on the physical level is established. Based on the generalized information work theory, the IES informatics equivalent thermodynamic entropy increase mechanism model is introduced. Combining with the networking characteristics of IES, the basic concepts of IES entropy state including entropy state, entropy increase flow, cumulative entropy increase flow, entropy increase source, and node entropy increase are defined. On this basis, the entropy state modeling method for each link in IES is proposed. Finally, case studies verify that the proposed model can effectively solve the entropy state distribution of IES, and the influence of the difference between source and load prediction on the entropy distribution of the system is discussed.关键词：integrated energy system;energy degradation;uncertainty;entropy state;entropy increase flow2|2|0更新时间：2025-06-16
- 摘要：The operation optimization of the urban integrated energy system faces multiple challenges such as strong randomness and volatility of renewable energy generation, uncertainties of load power and system parameters. In this paper, the dispatching model of user-side flexible resources is constructed considering aggregation characteristics, and a two-stage optimal dispatching strategy for urban integrated energy system considering uncertainties and interactive power is proposed. In the day-ahead stage, hybrid stochastic-robust optimization method is adopted to deal with the uncertainties of building group parameters, renewable energy and load. Meanwhile, the optimal interactive power interval between urban distribution network and superior power grid is obtained. In the intra-day stage, the dispatching strategy is rolling optimized by model predictive control based on the forecast results of renewable energy generation and load. Test results show that the proposed dispatching strategy can ensure the thermal comfort requirements of users, and the obtained interactive power interval has the ability to cope with the uncertainties within a day. Moreover, the impact of short-term violent fluctuations of interactive power on the safety and economy of system operation is reduced.关键词：urban integrated energy system;optimal dispatching;hybrid stochastic-robust optimization;model predictive control;renewable energy;uncertainty4|2|0更新时间：2025-06-16
- 摘要：To give full play to the role of characteristics of the interaction between source and load on the energy production side and the consumption side of the building integrated energy system (BIES), it is necessary to ensure the comfort of energy supply. Based on the heat acclimatization principle that the thermal comfort of a group would adjust its thermal expectation to the environment with the seasons, a unified optimization model for the type selection and capacity determination of energy hubs in a BIES is established. The model takes into account the influence of typical daily outdoor temperature, solar radiation intensity and rigid electric heating load on indoor thermostatically controlled load and energy hub output, restricts the room temperature regulation strategy and energy hub capacity configuration based on the group thermal environment comfort zone, and realizes the collaborative optimization of building thermal comfort energy supply and energy hub architecture economy. The Benders decomposition method is adopted to solve the model. Analysis results of the example show that the planning model with the modified thermal comfort zone can reduce the configuration capacity of the energy hub, effectively improve the utilization rate of renewable energy, and reduce the overall carbon emission of the system.关键词：building integrated energy system;optimal configuration;heat acclimatization;thermostatically controlled load;low-carbon economy3|1|0更新时间：2025-06-16
- 摘要：This paper proposes a novel probability prediction method of photovoltaic output combining the probabilistic model of quantile linear interpolation with the deep autoregressive recurrent neural network, which can make up for the shortcomings of traditional methods in probability modeling and describing complex nonlinear relationship. First, a probability model for photovoltaic output is built based on the quantile linear interpolation, which can comprehensively and accurately depict probability distribution of photovoltaic output in various circumstances. Then, continuous ranked probability score (CRPS) is used as the loss function for the training prediction model, and the closed analytic expression of the CRPS integral is derived for model training to ensure the feasibility and efficiency of training. Finally, a deep autoregressive recurrent neural network is adopted to model time-series of photovoltaic output. Combined with the proposed probability model of photovoltaic output, a new photovoltaic output probability prediction method is formed. Numerical results of the case study demonstrate that the proposed method can provide reliable and high-quality probability prediction for photovoltaic output关键词：photovoltaic output;probability prediction;quantile interpolation;recurrent neural network2|2|0更新时间：2025-06-16
- 摘要：Existing research on the power output prediction of offshore wind farms does not take into account the complex spatio-temporal relationship, and the prediction models are mostly “black boxes”, lacking the interpretable ability. To fully exploit the spatio-temporal correlation and realize the interpretability of the model, this paper proposes a power output prediction model of offshore wind farms based on multiple spatio-temporal attention graph neural network (MSTAGNN). Firstly, a graph topology of the offshore wind farm considering the spatial correlation is proposed, and the spatial attention mechanism is introduced to realize the dynamic change of graph topology. Secondly, the graph convolutional network and temporal gated convolution network are separately used to extract spatial and temporal features. Then, the multi-dimensional and multi-head attention mechanism is introduced into the proposed model to obtain multiple interpretable abilities. Finally, based on the real data of 34 wind turbines in Donghai Bridge wind farm, China, this paper conducts the simulation verification. The results show that, compared with traditional prediction models, the proposed model has higher prediction accuracy, and has reasonable interpretability in multiple dimensions of space, feature and time.关键词：offshore wind farm;power output prediction;graph neural network;Attention mechanism;interpretability;spatio-temporal feature2|0|0更新时间：2025-06-16
- 摘要：Aiming at the problem of safe and economic operation of distribution networks with multi-type microgrids, a mixed game model is constructed with the objective of minimizing the cost of each agent. First, the clustering method is used to reduce the scenarios, and the master-slave game model is constructed considering the integrated demand response of multi-type loads. As the leader, the distribution network formulates the price for trading with the microgrid with the objective of minimizing the operation cost. As the follower, the multi-type microgrids form a cooperative alliance to formulate the price for trading between microgrids and the benefit distribution mechanism under the optimized price. By the coupling decision-making function of the optimized transaction price and the microgrid electricity purchase and sale plan, a win-win situation for different stakeholders is realized. Secondly, considering the influence of interactive power on the safe operation of distribution networks, a coordinated optimization method considering the power flow of distribution networks is proposed. According to the characteristics of the model, the adaptive state transition algorithm (ASTA) is used to solve the master model, and the Cplex solver is used to solve the slave model, while the master-slave model interacts to obtain the equilibrium strategy of the mixed game model. Finally, the simulation results verify the effectiveness and rationality of the proposed method.关键词：active distribution network;demand response;multi-microgrid system;mixed game;reactive power optimization2|0|0更新时间：2025-06-16
- 摘要：The intermittent fluctuations of distributed generators and stochastic factors such as repeated charging and discharging of energy storage and electric vehicles bring great challenges to the stable operation of DC distribution systems. First, this paper establishes a reduced-order stochastic differential equation for the stochastic excitation of the DC distribution system under master-slave control and derives the analytical solution of the stochastic differential equation. Then, the analytic criterion of mean and mean square stability is established, and the relationship between small disturbance stability and average and mean square stability is comprehensively portrayed. The criterion of small disturbance instability, average stability and mean square stability is derived. Finally, the validity of the theoretical analysis is verified by simulation and experiment.关键词：flexible DC distribution system;stochastic differential equation;average stability;mean square stability;small disturbance stability2|1|0更新时间：2025-06-16
- 摘要：Considering that the existing deep learning based transient stability assessment methods do not fully describe the input data of power systems, the heterogeneous data is often ignored, and lots of feature information is unable to be effectively fused. In order to make full use of the various kinds of heterogeneous data of the power system to improve the accuracy of the model and the performance of the algorithm, a deep learning method based on the feature-level fusion of heterogeneous data is proposed. Firstly, the multi-layer perceptron (MTL), graph convolutional network (GCN), and gated recurrent unit (GRU) are used to extract the features from static multivariable data, topological graph data, and time series multivariable data, respectively. Secondly, the method of tensor fusion is used to carry out the feature-level fusion of the extracted features. After the flattened fusion features are input into the shared layer, the transient stability discrimination and margin prediction are realized simultaneously by using the multi-task learning method based on the homoscedastic uncertainty. On this basis, a transient stability assessment model is established to evaluate the performance of the proposed method. Finally, the New England 10-machine 39-bus system is adopted for simulation, training and verification. The results show that the proposed method can effectively improve the assessment accuracy and robustness.关键词：transient stability assessment;heterogeneous data;deep learning;feature-level fusion;adaptive multi-task learning2|1|0更新时间：2025-06-16
- 摘要：Aiming at the repair problem of missed and abnormal wind speed data, considering the correlation of node data in wind speed sampling network, a repair method for missed and abnormal wind speed data based on the reference sequence and full convolution network is proposed. Firstly, a data repair model based on the full convolution interpolation network and full convolution gate control network is constructed. Then, the full convolution interpolation network is used to calculate the non-reference repair data, the full convolution gate control network is used to calculate the weight coefficient of the non-reference repair data and the reference data, and the two kinds of data are weighted and summed to get the final repair data. Finally, the algorithm effect is verified using the data of two wind farms. The results show that, compared with other non-reference repair methods, the proposed method can use the reference wind speed data of similar nodes to improve the repair accuracy of wind speed time-series data of target nodes关键词：wind farm;wind speed data;data repair;deep learning;full convolution network2|4|0更新时间：2025-06-16
Basic Research
- 摘要：Multi-phase ring brushless exciter is widely used in million-kilowatt nuclear power plants at present. However, due to its lack of perfect relay protection, multiple faults on site have brought serious losses. The difficulty in implementing this protection lies in the fact that the exciter is a rotating-armature-type motor, and the only measurable quantity is the stator excitation current. Therefore, a single electrical characteristic is required to protect and distinguish various faults. Firstly, based on the characteristics of rotor armature current and spatial harmonic magnetic field before and after various faults, the fault characteristics and mechanism of exciter stator and rotor windings and rotating rectifier are deeply studied. According to the mutual induction relationship between stator and rotor currents in the asymmetric winding structure, the transient process and steady-state spectrum distribution characteristics and evolution laws of various faults are obtained. Secondly, taking the 11-phase ring brushless exciter as an example, the experiments and simulations with different faults are carried out on the prototype, and the experimental and simulation results verify the correctness of the theoretical analysis. Finally, a new protection principle based on stator excitation current is proposed. The prototype experiment and the field test results show that this protection method can not only realize reliable and sensitive protection from faults, but also distinguish the faults selectively.关键词：nuclear power unit;brushless exciter;relay protection;excitation current;harmonic;fault diagnosis4|1|0更新时间：2025-06-16
- 摘要：In order to improve the utilization rate of idle energy storage of 5G base stations, this paper designs a multi-base-station energy storage system (MBSESS) that uses the energy storage of 5G base station to participate in power grid dispatching. By adopting the coordinated dispatching mechanism of participating in power grid demand response and charging during off-peak tariff and discharging during peak tariff, an economic model of MBSESS is established, which takes into account multiple factors such as overcharge and overdischarge penalties and dispatching costs. With the goal of maximizing economic benefits, a deep reinforcement learning based dispatching method is proposed for regulating the charging and discharging behavior of energy storage of 5G base station. The method uses deep deterministic policy gradient to learn system environment information, and groups energy storage of 5G base station to reduce the learning dimension. Simulation results show that the method can ensure the subsequent adjustable capacity of energy storage of 5G base station, effectively control the variation range of the state of charge (SOC) of the base station energy storage, and maximize the revenue of energy storage of 5G base station participating in power grid dispatching.关键词：5G base station;deep reinforcement learning;energy storage;dispatching strategy;economic benefit2|2|0更新时间：2025-06-16
- 摘要：This paper discusses and analyzes the participation of composite energy storage system in wind power fluctuation suppression. Firstly, aiming at the problem that the traditional filtering method determines the smoothness degree by the time period with large fluctuation of wind power when extracting the grid-connected power, and the overall smoothness effect varies greatly in different wind power fluctuation scenarios, an adaptive time-scale wavelet packet method is proposed. The filtering time scale can be adaptively planned according to wind power fluctuations, and the number of decomposition layers can be adaptively determined within the time scale, taking into account different wind power fluctuation periods, which improves the scene adaptability. Then, based on the charging and discharging response demarcation time of power-type and energy-type energy storage outputs, the proposed method is used for internal power allocation, and a dual-objective fuzzy control strategy is designed, which takes into account the optimization for the state of charge (SOC) of composite energy storage and the coordinated control of energy-type and power-type energy storage, so as to reduce the impact on grid-connected power while optimizing SOC. Finally, based on the typical daily data of a wind farm, the effectiveness of the proposed method is verified in MATLAB.关键词：adaptive time scale planning;adaptive wavelet packet decomposition;composite energy storage system;internal power coordination control;dual-objective fuzzy control;state of charge optimization2|0|0更新时间：2025-06-16
- 摘要：Participation of wind power in the frequency response is an important scheme to ensure the frequency stability of power systems with high penetration rate of wind power. However, the rotational speed recovery process of wind turbines may lead to the frequency secondary drop (FSD) of the system. On the basis of analyzing the process of wind turbines using rotor kinetic energy to participate in frequency response, the generation mechanism of FSD and the main factors affecting FSD, a frequency response control strategy of wind turbines is proposed to reduce FSD considering the penetration rate of wind power. Based on the integrated inertia control, the active power reference values of wind turbines in the frequency support process and the rotor speed recovery process are designed in stages, and the output power of wind turbines is dynamically adjusted to reduce FSD. Finally, simulation results verify that the proposed strategy can significantly reduce FSD in power systems with different penetration rates of wind power and improve the frequency response characteristics of power systems.关键词：wind turbine;frequency response;frequency secondary drop (FSD);rotor kinetic energy;integrated inertia control3|14|0更新时间：2025-06-16
- 摘要：On the background of power grid weakening caused by the high proportion of renewable energy integrated into the distribution network, the non-fundamental component of the reactive power compensation capacitor will easily cause the resonance of the grid-connected system, which limits the integration capacity improvement of the renewable energy group. First, by analyzing the Bode diagram of the source-grid side impedance in the frequency band of 1~1 000 Hz, it is revealed that the non-fundamental component of the reactive power compensation capacitor will essentially change the impedance characteristics of the grid side from inductance to capacitance. Under the fixed inverter side impedance designed in the inductive weak grid, the essential change of the grid-side impedance will lead to the mismatching of source-grid impedance and induce the resonance of the grid-connected system, which will limit the integration capacity improvement of the renewable energy group. On this basis, an active adaption control scheme based on capacitive feature cancellation is proposed. The operation capability of the grid-connected inverter is further improved while counteracting the influence of the reactive power compensation capacitor. Based on the dual constraints of the system Nyquist curve and the minimum peak value of the closed-loop amplitude-frequency characteristic of a single inverter, the engineering setting principles of the parameters in the proposed scheme are given. Finally, simulation and experiment results verify the correctness and feasibility of the above research.关键词：distribution network;reactive power compensation capacitor;integration capacity of renewable energy group;capacitive cancellation;active adaption;dual constraints2|1|0更新时间：2025-06-16
- 摘要：The equivalent impedance of the AC power grid reflects the strength of the AC system, and the reduction of the system strength will adversely affect the stable operation of the modular multilevel converter based high voltage direct current (MMC-HVDC) transmission system. In order to effectively avoid the safe operation risk of the AC/DC systems brought by high impedance/low strength and realize the rapid and accurate detection of the equivalent impedance of complex and changeable power grids, this paper proposes an online identification method of the equivalent impedance based on reactive power disturbance injection for the AC power grid with modular multilevel converters at both ends. First, the principle of impedance identification with reactive power injection is described from the theoretical perspective, and the influence of the resistance and measurement meter error on the impedance identification accuracy is analyzed. Then, an evaluation index for impedance identification accuracy based on AC bus voltage information is established. Based on this index, this paper proposes the principle to design the volume of reactive power disturbance injection and the online identification method for the equivalent impedance of the AC power grid based on the identification accuracy constraint. Finally, the feasibility of the proposed method and the controllability of the impedance identification accuracy are verified by simulation.关键词：flexible DC transmission;AC system;reactive power injection;impedance identification;accuracy evaluation;accuracy constraint2|1|0更新时间：2025-06-16
- 摘要：The distributed generator (DG) with flexible power control capability can adjust the distribution of network power flow, which contributes to the fault restoration of distribution network with DG. In recent years, fault restoration methods using network reconfiguration and DG power control collaboration have been developing rapidly. The transient electrical changes caused by the cooperation of the two recovery methods may threaten the safety of the fault restoration process, especially the research related to the closed-loop voltage fluctuations is still in its infancy. Therefore, this paper proposes a cooperative control method for distribution network fault restoration considering closed-loop voltage fluctuation suppression. Based on the system state after fault restoration and voltage fluctuations during the restoration, the necessity of the cooperation between DG output regulation and switching operation is analyzed. An upper-level model considering the system state after fault restoration and a lower-level model considering the voltage fluctuation during the restoration are established, forming a control sequence combination with the basic steps of “DG output regulation-closing branch switch-opening branch switch-DG output reset”. Furthermore, a method of generating a step-by-step implementation scheme for fault restoration is proposed. The case study shows that this method can maximize the security of recovery process and the system state after fault restoration, and effectively improve the power supply reliability of the distribution network containing DGs.关键词：distribution network;distributed generator (DG);fault restoration;voltage fluctuation suppression;cooperative control2|0|0更新时间：2025-06-16
Application Research
- 摘要：The single-phase cascaded multilevel inverter (CMI) has attracted much attention in the research field of grid-connected photovoltaic systems in recent years because of its advantages such as the module-level maximum power point tracking (MPPT), the module-level shutdown, the low harmonic content of multilevel output voltage and the structure integrating the optimizer and the grid-connected inverter. The single-phase transformerless photovoltaic cascaded multilevel inverter (PV-CMI) with the independent DC bus structure is taken as the research subject, and two existing problems are summarized. One is that the lack of isolation circuits may lead to leakage current problems, and the other is that the independent DC photovoltaic inputs between the units in single-phase PV-CMI may lead to power imbalance problems. These two problems threaten the safe and stable operation of the single-phase PV-CMI, thus greatly limiting the promotion and application of the single-phase PV-CMI. The basic principle and topology characteristics of the single-phase PV-CMI are analyzed, and the existing research schemes are summarized on the two key problems of its leakage current and photovoltaic power imbalance. Finally, the current technical challenges and the future development trends of the PV-CMI are presented, which provides references for the subsequent research.关键词：cascaded multilevel inverter (CMI);leakage current;power imbalance;photovoltaic inverter2|1|0更新时间：2025-06-16
Review
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