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Review of Carbon Footprint for Thermal Power Industry in China AI Introduction
Abstract：ObjectivesUnder the background of the “double-carbon” target, thermal power is facing great pressure to reduce emissions. Thermal power carbon footprint evaluation can directly show the greenhouse gas emissions of thermal power and help tap the potential of carbon reduction. Therefore, the research status of thermal power carbon footprint assessment was reviewed.MethodsThis paper introduced the main standards and methods for thermal power footprint evaluation, and summarized the thermal power footprint evaluation process. The differences in the evaluation process were reviewed and some suggestions were given. The life cycle is divided into upstream, core and downstream. According to the high concentration of carbon emissions in the core links, the carbon footprint of the construction, decommissioning and power transmission of coal-fired power plants can be ignored in some cases.ConclusionsThe life cycle of different types of thermal power generation is similar, but the carbon footprint of waste incineration power generation does not include the acquisition process of domestic waste. Regardless of the form of thermal power, in the absence of measured emission factors, it is recommended that the emission factors select the default values of the published standards, literature and databases at home and abroad.Keywords：thermal power industry;carbon footprint;full life cycle;evaluation method;greenhouse gas;emission factor;carbon emission99|475|15<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Carbon Neutrality
Application Status and Existing Problem Analysis of the Natural Draft Cooling Towers With Flue Gas Injection Technology in Thermal Power Plants AI Introduction
Abstract：ObjectivesThe natural draft cooling towers with flue gas injection (NDCT-FGI) is a crucial retrofitting technique for enhancing the efficiency of thermal power plants. However, its operational impacts on existing systems are significant and cannot be overlooked. Therefore, the current status of NDCT-FGI technology and its problems in operation were analyzed, and the countermeasures were put forward.MethodsThrough comprehensive analysis of the existing research, the causes and formation mechanism of environmental impact, cooling tower corrosion, and deterioration of circulating cooling water quality caused by the technical transformation of NDCT-FGI were discussed.ResultsThe protective distance can be reasonably set by the simulation results of flue gas emission trajectory and pollutant landing concentration by computational fluid dynamics (CFD). Installation of baffles at the tower top can prevent flue gas washdown during the extreme weather conditions. Different anticorrosive coatings are recommended for various parts of the cooling tower to extend its service life. To control and optimize cooling water quality, the advanced water treatment techniques are necessary for optimizing chemical dosing, and the management of effluent and makeup water must be carefully controlled to ensure operational sustainability.ConclusionsBy implementing appropriate and effective countermeasures, the negative impacts of NDCT-FGI retrofitting can be mitigated, thereby enhancing both the environmental and economic benefits for thermal power plants.Keywords：thermal power;cooling tower;smoke emission;environmental pollution;boiler;corrosion;desulphurization;denitration64|396|2<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Experimental Study on Sintering and Melting Characteristics and Mineral Transformation Law of Synthetic Biomass Ash AI Introduction
Abstract：ObjectiveThe coking problem of biomass in fluidized bed combustion process was studied, and the influence of potassium salt form and content on the sintering and melting characteristics of biomass ash was analyzed.MethodsThe sintering and melting characteristics and the mineral transformation law of synthetic biomass ash were analyzed by experiments with scanning electron microscope coupled energy dispersive spectrometer, X-ray diffractometer, X-ray fluorescence, and FactSage thermodynamic calculation software.ResultsIn the typical operating temperature range of 750-950 ℃, the sintering and melting degree of synthetic biomass ash aggravates with the increase of temperature and potassium salt mass fraction. In addition, the effects of different forms of potassium salt on the sintering and melting characteristics of biomass synthetic ash are also significantly different. When the potassium salt is in the form of K2CO3, the liquid phase in the synthetic ash could reach up to 34.36%, leading consequently to severe sintering of the ash. When the potassium salt is in the form of KCl, most of K and Cl elements escape at 750-850 ℃, and the sintering degree of synthetic ash is weakened in comparison with the K2CO3 situation. When the potassium salt is in the form of K2SO4, the liquid phase in the synthetic ash is the least, and the sintering and melting degree is also the weakest.ConclusionChanging the form of potassium salt and controlling the temperature of fluidized bed are expected to alleviate the coking problem of biomass in fluidized bed combustion.Keywords：biomass;fluidized bed;synthetic ash;sintering and melting;potassium salt73|241|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Performance Analysis of Combined Medical Waste-Waste Tire Resource Utilization System Based on Gasification and Pyrolysis AI Introduction
Abstract：ObjectivesWith the annual increase in the generation of solid waste, traditional treatment methods have struggled to meet the increasingly stringent environmental requirements and the demands for resource recycling. In order to realize the efficient utilization of solid waste resources, a combined medical waste-waste tire resource utilization system based on gasification and pyrolysis was proposed.MethodsThe system fully combined the advantages of plasma gasification and pyrolysis technologies, coupling the medical waste plasma gasification power generation technology with tire pyrolysis technology. The syngas obtained from the gasification and pyrolysis processes was utilized together as the fuel of a gas turbine. At the same time, the high-temperature flue gas produced by the gas turbine provided the heat source for tire pyrolysis, after which the flue gas heat was recovered by a waste heat boiler. While harmlessly treating the medical waste-waste tires, the gradient utilization of energy was realized. The energy analysis and economic analysis of the proposed system were carried out under the condition of fixed feed rate.ResultsThe system is able to achieve a total energy output of 23.59 MW, with a total energy utilization efficiency of 52.56%, which is much higher than the efficiency of conventional waste-to-energy generation. The system has good economic returns, and can realize a relative net present value of 727.978 1 million yuan in a 20-year life cycle, and the dynamic payback cycle is only 3.13 years.ConclusionsThe research results provide a new technical path for the efficient co-processing of solid waste resources.Keywords：solid waste treatment;energy recovery;gas turbine;plasma gasification;tire pyrolysis;steam cycle45|218|2<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15- Abstract：ObjectivesIn order to solve the shortcomings of the traditional preventive maintenance method of air preheater in large thermal power unit, a general mode of predictive maintenance based on digital twin was proposed, and the digital twin system of air preheater was constructed based on digital twin technology.MethodsThe proposed system included physical entity of rotary air preheater, real-time data acquisition and analysis module, digital twin model construction module, thermal parameter state monitoring, rotor thermal field video and thermal deformation visualization and ash accumulation prediction module. By the real-time acquisition of temperature parameter state and video data, and through the temperature field, video image, air leakage calculation and other modules, the calculation of thermal parameters and the prediction of ash accumulation were realized. At the same time, the 3D configuration screen was used to display data in real time, continuously optimize the accuracy of thermal parameter calculation and ash accumulation prediction, and realize the automatic optimization of soot-blowing strategy.ResultsThe proposed scheme realizes the state monitoring and dynamic control of the thermal calculation process of the air preheater, and solves the problem that the ash accumulation factor of the rotary air preheater in the existing power station affects the safe and reliable operation of the thermal power unit.ConclusionsThrough engineering testing of actual units, the proposed scheme effectively improves the operation and maintenance efficiency of the air preheater of thermal power units, verifies the feasibility of the proposed method, and provides technical support for the development of smart power plant systems in future.Keywords：thermal power unit;preventive maintenance;predictive maintenance;digital twin;air preheater75|427|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Experimental Study on Fluidity of High Moisture Lignite AI Introduction
Abstract：[Objecttives] The influence of moisture in raw coal, particle size and coal bunker material on the fluidity of raw coal was studied to find out the main reasons for coal clogging in raw coal bunkers.MethodsA raw coal flowability experimental device was designed and built to conduct flowability experiments on raw coal with different moisture and particle sizes, and flow characteristics diagrams were drew to obtain the effects of various factors on raw coal flowability.ResultsThe greater the moisture in the raw coal, the more right the broken line in the flow characteristic diagram is, the less the falling mass, the worse the mobility, and the greater the rotation angle required for complete falling.The difference in the initial position of coal falling is due to the difference in static friction between different particle sizes, resulting in different repose angles. At the same time, the decrease in moisture will reduce the friction force and increase the falling mass. The liquidity bend line of polytetrafluoroethylene material is located at the front, and the friction coefficient at the bottom is small. At the same angle, the mass drops more and the mobility is enhanced.ConclusionsMoisture plays a key role in the fluidity of raw coal, the influence of particle size on the fluidity of raw coal is weak, and only the interaction with moisture can have a great influence on the fluidity of raw coal. Material also has a greater impact on the fluidity of raw coal, but when the moisture is low, the impact can be ignored.Keywords：coal-fired power;high-moisture lignite;raw coal fluidity;coal blockage;moisture;particle size50|164|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Power Generation and Environmental Protection
Multi-Area Interconnected Integrated Energy System Planning Considering Cloud Energy Storage AI Introduction
Abstract：ObjectivesIn order to promote the efficient utilization of energy storage and user-side resources and improve the level of clean energy consumption, a multi-area interconnected integrated energy system planning model considering cloud energy storage was proposed.MethodsOn the basis of establishing the energy router model of the regional integrated energy system, a virtual energy router model considering electricity/heat/gas cloud energy storage was proposed. Aiming at the problem that cloud energy storage and integrated energy system belong to different investment entities, considering the limitation of the investment return period of cloud energy storage, a dual-subject two-stage planning model was proposed. In the first stage, the grid, equipment capacity and cloud energy storage price were planned. In the second stage, the operation strategy of the integrated energy system was optimized. Aiming at the high complexity of multi-energy flow grid planning, a pre-screening algorithm based on minimum spanning tree was proposed.ResultsThe example analysis results of a three-park integrated energy system planning show that the proposed model is helpful to improve energy efficiency, reduce carbon emissions, and improve the economic benefits of interconnected integrated energy systems.ConclusionsThe research reveals the potential of collaborative planning between cloud energy storage and multi-area integrated energy systems, and provides reference for the in-depth application and commercial promotion of multi-type energy storage in the energy field.Keywords：integrated energy system;energy internet;cloud storage system;energy router;two-stage stochastic programming57|172|11<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Optimization and Scheduling of Integrated Energy Systems With Carbon Capture and Storage-Power to Gas Based on Information Gap Decision Theory AI Introduction
Abstract：ObjectivesThe main issue in the current rational optimization of integrated energy systems is to adopt technological means to improve energy conversion efficiency, reduce system energy waste and regional environmental pollution, in order to scientifically coordinate the optimization goals of economic, stability, and low-carbon operation of the integrated energy system. To this end, a low-carbon optimization strategy for a carbon capture and storage (CCS)two-stage power to gas (P2G)integrated energy system based on scenario generation and information gap decision theory (IGDT) was proposed.MethodsAt the technical level, by finely modeling the two-stage conversion from power to gas, the efficiency of hydrogen energy utilization was improved, and a combined heating and power (CHP)-CCS-P2G coupling model was established. At the market mechanism level, a tiered carbon trading model was introduced to reduce CO2 emissions in the system. Finally, based on the IGDT, an optimization scheduling model was constructed for different risk preferences.ResultsTaking a typical integrated energy system as an example, the simulation results show that the proposed model can improve the wind and solar energy consumption rate, achieve low-carbon, economic, and stable operation of the system.ConclusionsThis optimization strategy can effectively help decision-makers develop scheduling plans under risk avoidance and risk pursuit strategies based on their risk preferences, achieving a balance between system uncertainty and economy.Keywords：integrated energy system;scenario generation;information gap decision theory(IGDT);carbon capture and storage(CCS);power to gas(P2G);stepped carbon trading64|332|13<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Comprehensive Utilization of Energy
Performance Analysis and Experimental Study of a Kind of Thin and Light Photovoltaic/Thermal Collector AI Introduction
Abstract：ObjectivesThe demand for energy in outdoor work and survival is increasing, and there are some significant shortcomings in the existing conventional energy supply methods, such as the need to carry a large amount of fuel for conventional generators and heavy weight of cells. Solar photovoltaic/thermal (PV/T) technology can effectively solve the problem of lack of energy for outdoor survival and field work. However, most of the existing PV/T collectors are rigid structures with large weight and are not easy to carry.MethodsA light and thin PV/T module based on the combination of a Cu(In,Ga)Se2(CIGS) thin film battery and a piece of capillary network were proposed. The energy collection performance of the module and the impact of water flow rate on the photoelectric and photothermal conversion efficiency of the module were studied experimentally.ResultsUnder the typical Shanghai climate conditions, the all-day electrical efficiency and thermal efficiency of the module are 13.04% and 22.50%, respectively. Under experimental conditions with an average irradiance of 760 W/m², the optimal energy collection performance of this PV/T is achieved when the water flow rate is 2.1 L/min. The cooling water in the capillary network can effectively reduce the cell temperature (by 10 ℃) and improve the energy utilization efficiency (by 23.94%).ConclusionsThe module has the characteristics of high power density, light weight and flexibility, and can be used for energy supply during outdoor work and survival, providing a new idea for the design of outdoor energy equipment.Keywords：photovoltaic/thermal collectors;capillary network;portable energy equipment40|208|4<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Onshore Wind Farm Collector Circuit Division and Topology Optimization Based on Improved Fuzzy C-Means Clustering AI Introduction
Abstract：ObjectivesDriven by the dual carbon goal and the accelerated transformation of China’s energy structure, the scale of the wind power industry continues to grow rapidly, and there is an urgent need to reduce costs and increase efficiency to cope with the pressure of grid parity. The cost of collector lines accounts for a relatively large proportion of investment, and there is considerable space for optimization. In order to reduce the investment cost, an improved fuzzy C-means (FCM) clustering algorithm was proposed.MethodsThe improved FCM clustering algorithm was used to divide the collector circuit of onshore wind farm. The algorithm comprehensively considered the azimuth angle and the Euclidean distance to ensure that the lines between the circuits were not crossed, and the adjacent units were gathered to the same circuit. The correction factor of the distance from the machine position to the cluster center was introduced, and the circuit capacity was limited by adjusting the distance correction factor. On the basis of circuit division, the dynamic Prim algorithm was used to optimize the line selection of each circuit. Finally, the effectiveness of the method was verified by an example of an onshore wind farm.ResultsCompared with the clustering method only considering the azimuth angle, the improved FCM algorithm considering azimuth angle and spacing has better optimization effect. The total cost of single-circuit and double-circuit collection lines is reduced by 2.6% and 5.4%, respectively.ConclusionsThe proposed algorithm can effectively reduce the total cost of collector lines, and has certain application value. It can provide a reference for the design of wind farm collector lines.Keywords：onshore wind farm;collector line;topology optimization;fuzzy C-means (FCM) clustering algorithm;dynamic Prim algorithm81|250|2<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15- Abstract：ObjectivesDistributed photovoltaic power prediction is of great significance for the operation and scheduling of photovoltaic power plants. Point prediction methods are difficult to comprehensively describe the uncertainty of distributed photovoltaic power. This article proposed a distributed photovoltaic power interval prediction model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and sparrow search algorithm optimized least squares support vector machine (SSA-LSSVM).MethodsFirstly, the photovoltaic sequence was broken down into multimodal components through CEEMDAN, and then the high-frequency non-stationary components obtained from the first decomposition were decomposed twice. Secondly, sample entropy (SE) was used to reconstruct all components into trend and oscillation components. Then, the point prediction values of the two components were obtained through SSA-LSSVM. Finally, the probability density estimation was performed on the point prediction error of the oscillation component, and the stacked point prediction value was used to obtain the overall prediction interval result.ResultsThe interval prediction model proposed in this paper has higher interval coverage and narrower average interval width.ConclusionsAdding secondary modal decomposition to distributed photovoltaic power data processing and combining sample entropy to reconstruct its sub-sequences can effectively reduce the complexity of the original prediction components and improve the accuracy of model prediction.Keywords：distributed photovoltaic;power prediction;kernel density estimation;intervel prediction70|496|16<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Operation Analysis of a Photovoltaic-Piezoelectric Composite Independent Power Supply System AI Introduction
Abstract：ObjectivesIn order to make the small independent power supply unit provide more flexible and stable power supply, a photovoltaic-piezoelectric composite independent power supply system was designed, and its performance in actual operation was analyzed.MethodsConsidering the power supply scenarios such as bus stations, the output characteristics model of piezoelectric ceramics and photovoltaic cells was established, the system configuration of photovoltaic-piezoelectric outdoor independent power supply unit was designed, and the power output and system stability under typical daily, typical annual and long-term operating conditions were analyzed. For the system design with or without piezoelectric ceramics, the reliability rate of power supply, curtailment power and power generation cost of the system were analyzed.ResultsAfter adding piezoelectric ceramics, the reliability rate of the system is 99.18%, the power generation cost is 1.399 yuan/(kW⋅h), and the annual curtailment power is 161.24 kW⋅h. Compared with the system without piezoelectric ceramics, the reliability rate is increased by 0.12%, the cost is increased by 0.8%, and the curtailment power is reduced by 18.6%.ConclusionsAfter the addition of piezoelectric ceramics, although the power generation cost of the system increases slightly, the reliability of the system power supply is improved and the curtailment power is reduced. With the reduction of the cost of piezoelectric ceramics and the development of technology, the photovoltaic-piezoelectric composite independent power supply system will have a better application prospect in special scenarios.Keywords：photovoltaic power generation;piezoelectric ceramic power generation;photovoltaic cells;independent power supply;operation analysis;economic analysis46|250|2<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Joint Simulation Study on Load Characteristics of Wind Turbines in Low Voltage Ride Through Process AI Introduction
Abstract：ObjectiveThe grid fault of voltage drop will cause severe variations to the load of wind turbines, and seriously affect the safe and stable operation of wind turbines. With the increasing of the wind turbine scale, the blade length and the tower height increase continually, leading to the increase of the sensitivity of load characteristics to the system parameter fluctuations. Therefore, it is necessary to study the load and vibration characteristics of key components in the process of grid voltage drop.MethodsA data interaction method based on dynamic link library and Socket communication was proposed, and a joint simulation method of Simulink and Bladed was established. Firstly, based on a 3.4 MW wind turbine model, the joint simulation platform was verified by a given wind speed variation condition. Then, the relationship between the overall performance of the unit and the load of the blade and tower during low voltage ride through (LVRT) was studied.ResultsThe amplitude of grid voltage drop has a great impact on the generator power, and has little impact on the wind turbine control parameters. In the process of LVRT, the blade pitch angle and rotational speed of the wind turbine fluctuate for a long time, the load change at the outer blade span is greater than that at the inner blade span, the blade tip displacement increases, and the vibration frequency of the tower is close to the natural frequency. These potential risks should be considered in wind turbine design.ConclusionThe joint simulation platform can effectively simulate the aerodynamic performance of the wind turbines and the transient characteristics of the component loads, and provide a reference for the optimal control of the unit.Keywords：new energy power generation;wind turbines;joint simulation;low voltage ride through (LVRT);transient characteristic;load62|489|10<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
New Energy
- Abstract：ObjectivesWith the continuous development of China's new power system, there is a growing integration of new energy sources such as photovoltaic and wind power into the grid. However, this integration has also led to an increase in intelligent control equipment and nonlinear loads, resulting in more complex power quality issues. In order to enhance the power supply quality of the entire power grid and achieve economic operation and efficient development, it is crucial to conduct a scientific and rational quantitative evaluation of power quality.MethodsStarting from three aspects of power quality evaluation indicators, weighting methods and evaluation models, the comprehensive power quality evaluation methods were systematically summarized and compared, and the research status of comprehensive power quality evaluation methods was summarized. On this basis, the shortcomings and problems that need to be solved of various existing comprehensive power quality assessment methods were summarized, and the possible research directions in this field were prospected.ConclusionsAlthough many results have been achieved in the research on comprehensive evaluation of power quality at home and abroad, each method has its own advantages and disadvantages, there are still a series of important neglected problems that need to be solved in this field.Keywords：new power system;power quality;comprehensive evaluation;indicator;weight;evaluation model78|417|12<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Voltage Hierarchical Control Strategy of Active Distribution Network Based on Deep Reinforcement Learning AI Introduction
Abstract：ObjectivesThe randomness and volatility of distributed power generation poses significant challenges for the voltage control in active distribution network (AND). In this context, there is an urgent need for an efficient voltage control strategy to ensure the safe operation of ADN.MethodsBased on the deep reinforcement learning method, a voltage control strategy for double-layer regional distribution networks was proposed. First, based on the adjustment characteristics of voltage regulating equipment and the complexity of controllable elements, a regional coordinated control area and a local autonomous control area were designed for the radiating grid structure of the ADN, and the voltage control model of each area was constructed. Then, the model was solved by deep Q-Network (DQN) algorithm and deep deterministic policy gradient (DDPG) algorithm to achieve the purpose of tracking voltage changes in real time, and effectively solve the voltage control problem during the operation of the ADN. Finally, the method was verified by IEEE 33-bus simulation examples.ResultsThe DQN algorithm and the DDPG algorithm were used to solve the control variables in the coordinated control region and the local autonomous region respectively, realizing real-time decision-making of voltage regulation in the ADN system, and solving the problems of bidirectional flow of ADN power flow and complex and changeable voltage.ConclusionsThe proposed control strategy has obvious effect on controlling voltage deviation, and has strong accuracy and practicality.Keywords：active distribution network (ADN);regional coordination control;local autonomous control;deep reinforcement learning;voltage control strategy69|803|12<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Research on Temperature Situation Awareness and Auxiliary Decision-Making System Scheme of Substation Equipment AI Introduction
Abstract：ObjectivesTo enhance the intelligent management of substation equipment maintenance, timely identify and mitigate the risks of failures caused by device overheating, and ensure the safe and stable operation of the power grid, the temperature situation awareness and auxiliary decision-making scheme of substation equipment were proposed.MethodsThe research was carried out from four aspects: the perception layer, the understanding layer, the prediction layer, and the auxiliary decision-making layer. In the perception layer, the K-nearest neighbor (KNN) classification algorithm was used to analyze the correlation of multi-class temperature data. In the understanding layer, a BP neural network was employed to construct a historical data transmission model to address missing historical data issues. In the prediction layer, a temperature prediction model combining autoregressive integrated moving average (ARIMA) and support vector machine (SVM) was designed to handle nonlinear data and noise. In the auxiliary decision-making layer, the grey relational analysis was applied to analyze the relationship between equipment temperature changes and fault risks.ResultsThe verification results of numerical examples based on the proposed scheme show that the scheme realizes the effective perception of the future temperature variation trends of the equipment and provides a basis for the identification of equipment defects.ConclusionsThrough multi-dimensional and deep-level temperature data analysis, the proposed scheme reveals the potential correlation between equipment temperature and fault risk, realizes the prediction of the operational trend of substation equipment, and provides a reference for the optimization of operational mode and the formulation of equipment maintenance plan.Keywords：power system;substation;temperature state awareness;auxiliary decision-making;autoregressive integrated moving average (ARIMA) model;BP neural network;support vector machine (SVM)106|241|5<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15Renewable Energy Distribution Network Overcurrent Protection Based on Positive-Sequence Sudden-Change Component Locus Identification AI Introduction
Abstract：ObjectivesWith the widespread integration of renewable energy, the uncertainty of power flow in distribution networks with neutral points grounded through small resistors has made the setting of traditional three-stage current protection increasingly complex, and reduced its sensitivity and reliability. To solve the above issues, a new type of current protection based on positive sequence sudden-change variable current phasor trajectory identification was proposed.MethodsFirstly, the magnitude and distribution characteristics of the positive sequence sudden-change variable current upstream and downstream of the fault point were analyzed. Secondly, using the affinity clustering algorithm, the defined “main fault path” based on the clustering results was identified. Finally, a novel searching method was proposed to identify the source of the positive sequence sudden-change variable, which was the last level feeder located on the main fault path, as the faulted feeder.ResultsSimulation research based on PSCAD shows that the proposed protection method can adapt to various fault conditions, is immune to the integration of renewable energy, and has high sensitivity and reliability.ConclusionsThe research findings are helpful to enhance the operational safety of distribution networks with neutral points grounded through small resistors, and improve the efficiency of fault detection.Keywords：renewable energy;distribution network;relay protection;positive-sequence sudden-change component;affinity clustering algorithm68|354|8<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15- Abstract：ObjectivesVirtual power plant is usually composed of distributed generator (DG). When the system lacks power grid support, practical and reasonable comprehensive operation strategies and accurate control methods are needed to ensure the smooth operation of virtual power plant.MethodsAn operation strategy based on system fluctuation value was proposed. Then, aiming at the problem of generation control of distributed generators in the system, a distributed finite-time controller was designed. The amplitudes of voltage and frequency were adjusted to nominal values within a finite time, and the active power was distributed among each DG unit. Different from the traditional centralized control strategy, the proposed control method is based on distributed junction, which only requires information exchange between adjacent DG units through sparse communication network.ResultsThe feasibility of the proposed control method and its robustness to the uncertainty of model parameters and load variation were verified by simulation experiments.ConclusionsCompared with previous studies, the proposed operation strategy divides the system operating conditions in more detail, effectively improving the stability and security of the system.Keywords：virtual power plant;operation strategy;primary control;secondary control;finite-time control109|127|5<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
A Frequency Regulation Method of Energy Storage System Based on Adaptive Adjustment of Virtual Synchronous Generator Control Parameters AI Introduction
Abstract：ObjectivesThe large-scale penetration of wind power has reduced the frequency regulation capability of the power system to a certain extent.As a relatively mature and effective technical means, the energy storage system is widely used in power grid frequency regulation. Therefore, the response process and optimal configuration of energy storage system (ESS) participating in power grid frequency regulation under the control of virtual synchronous generator were studied.MethodsBased on the simulation software DIgSILENT/PowerFactory, an ESS control model and typical power system were constructed to analyze the frequency response characteristics of the grid before and after the ESS participation. Furthermore, considering the reserve capacity of wind turbines under different output modes, the configuration results of the ESS were optimized by dividing the wind speed range and determining the wind turbine power reserve coefficient, so as to realize the adaptive adjustment of the frequency regulation coefficient of the ESS.ResultsThe investment of the ESS can effectively improve the frequency response and reduce wind curtailment of the system. By reserving the frequency regulation capacity of wind turbines reasonably, the ESS can provide reliable power support for the power grid.ConclusionsThe self-adaptive adjustment method of the frequency regulation coefficient of the ESS based on the wind speed and the output power of fans can effectively reduce the overshoot and the output power of the ESS while meeting the frequency regulation requirements, thereby extending the working time.Keywords：double carbon;energy storage;new energy;wind power;virtual synchronous generator;frequency response;frequency regulation89|314|12<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-15
Smart Grid
