With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secur...With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secure operation.Aiming at the SCC limitations,we use multiple back-toback voltage source converter based(B2B VSC)systems to separate a large-scale AC power grid into two asynchronous power grids.A multi-objective robust optimal secure operation model of large-scale power grid with multiple B2B VSC systems considering the SCC limitation is established based on the AC power flow equations.The decision variables include the on/off states of synchronous generators,power output,terminal voltage,transmission switching,bus sectionalization,and modulation ratios of B2B VSC systems.The influence of inner current sources of renewable energy generators on the system SCC is also considered.To improve the computational efficiency,a mixedinteger convex programming(MICP)framework based on convex relaxation methods including the inscribed N-sided approximation for the nonlinear SCC limitation constraints is proposed.Moreover,combined with the column-and-constraint generation(C&CG)algorithm,a method to directly solve the compromise optimal solution(COS)of the multi-objective robust optimal secure operation model is proposed.Finally,the effectiveness and computational efficiency of the proposed solution method is demonstrated by an actual 4407-bus provincial power grid and the modified IEEE 39-bus power grid,which can reduce the consumed CPU time of solving the COS by more than 90%and obtain a better COS.展开更多
The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context ...The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.展开更多
Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency devia...Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.展开更多
Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To thi...Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.展开更多
In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is rel...In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is relatively simple. Thus, connecting large-capacity wind power units complicates the peak load regulation and stable operation of the power grids in these regions. Most wind turbines use power electronic converter technology, which affects the safety and stability of the power grid differently compared with conventional synchronous generators. Furthermore, fluctuations in wind power cause fluctuations in the output of wind farms, making it difficult to create and implement suitable power generation plans for wind farms. The generation technology and grid connection scheme for wind power and conventional thermal power generation differ considerably. Moreover, the active and reactive power control abilities of wind turbines are weaker than those of thermal power units, necessitating additional equipment to control wind turbines. Hence, to address the aforementioned issues with large-scale wind power generation, this study analyzes the differences between the grid connection and collection strategies for wind power bases and thermal power plants. Based on this analysis, the differences in the power control modes of wind power and thermal power are further investigated. Finally, the stability of different control modes is analyzed through simulation. The findings can be beneficial for the planning and development of large-scale wind power generation farms.展开更多
With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,whic...With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.展开更多
With the problem of global energy shortage and people’s awareness of energy saving, electric vehicles receive world-wide attention from government to business. Then the load of the power grid will rapidly increase in...With the problem of global energy shortage and people’s awareness of energy saving, electric vehicles receive world-wide attention from government to business. Then the load of the power grid will rapidly increase in a short term, and a series of effects will bring to the power grid operation, management, production and planning. With the large-scale penetration of electric vehicles and distributed energy gradually increased, if they can be effectively controlled and regulated, they can play the roles of load shifting, stabling intermittent renewable energy sources, providing emergency power supply and so on. Otherwise they may have a negative impact, which calls for a good interaction of electric vehicles and power grid. Analyzed the status of the current study on the interaction between the electric vehicles and the power grid, this paper builds the material basis, information architecture and the corresponding control method for the interaction from the aspect of the energy and information exchanging, and then discusses the key issues, which makes a useful exploration for the further research.展开更多
Large-capacity hydropower transmission from southwestern China to load centers via ultra-high voltage direct current(UHVDC) or ultra-high voltage alternating current(UHVAC) transmission lines is an important measure o...Large-capacity hydropower transmission from southwestern China to load centers via ultra-high voltage direct current(UHVDC) or ultra-high voltage alternating current(UHVAC) transmission lines is an important measure of the accommodation of large-scale hydropower in China. The East China Grid(ECG) is the main hydropower receiver of the west–east power transmission channel in China. Moreover, it has been subject to a rapidly increasing rate of hydropower integration over the past decade. Currently, large-scale outer hydropower is one of the primary ECG power sources. However, the integration of rapidly increasing outer hydropower into the power grid is subject to a series of severe drawbacks. Therefore, this study considered the load demands and hydropower transmission characteristics for the analysis of several major problems and the determination of appropriate solutions. The power supply-demand balance problem, hydropower transmission schedule problem, and peakshaving problem were considered in this study. Correspondingly, three solutions are suggested in this paper, which include coordination between the outer hydropower and local power sources, an inter-provincial power complementary operation, and the introduction of a market mechanism. The findings of this study can serve as a basis to ensure that the ECG effectively receives an increased amount of outer hydropower in the future.展开更多
At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a pr...At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a project of "973 Program". Mr. Zhou, the chief engineer of China Electric Power Research Institute(CEPRI) and an academician of Chinese Academy of Sciences, is the chief scientist in charge of this research project.展开更多
Constructing an industrial system for a large-scale,non-grid-connected wind power industry is a key step towards the diverse utilization of wind power.However,wind power exploitation is not only a technical challenge ...Constructing an industrial system for a large-scale,non-grid-connected wind power industry is a key step towards the diverse utilization of wind power.However,wind power exploitation is not only a technical challenge but an industrial problem as well.The objective of this study is to introduce a concept of large-scale,non-grid-connected wind power(LSNGCWP) industrial zones and establish an evaluation model to assess their industrial arrangement.The data of wind energy,industry,nature resources and socio-economy were collected in this study.Using spatial overlay analysis of geographic information system,this study proposes a spatial arrangement of the LSNGCWP indus-trial zones in the coastal areas of China,which could be summarized as the 'one line and three circles' structure,which will contribute to the optimization of the industrial structure,advance the wind power technology,coordinate the multi-industrial cooperation,and upgrade the industrial transformation of China's coastal areas.展开更多
The first stage project of Jiuquan wind energy base with 5.5-GW installed capacity is about to be completed. However, there exist several technical issues such as power transfer capability, electricity accommodation, ...The first stage project of Jiuquan wind energy base with 5.5-GW installed capacity is about to be completed. However, there exist several technical issues such as power transfer capability, electricity accommodation, frequency control and peak load regulation as well as system stability. In addition, the high capital cost and operation cost of the supporting transmission project invested and constructed by the Gansu Provincial Power Company will definitely have significant impacts on the management and economic profit of the Company. Through analysis of the construction and operation cost changes resulting from the wind power collection and delivery project, the author carried out research into the effects of developing large-scale wind power base on the management and economic benefits of power grid enterprises and proposed corresponding suggestions to make the related policies perfect.展开更多
The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.H...The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.展开更多
Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constr...Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.展开更多
This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as ru...This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.展开更多
Dear Editor,This letter investigates the grid-forming control for power converters.Recently,grid-forming control based on matching of synchronous machines was suggested by using continuous measurements.In the present ...Dear Editor,This letter investigates the grid-forming control for power converters.Recently,grid-forming control based on matching of synchronous machines was suggested by using continuous measurements.In the present letter,we suggest a digital implementation using artificial delays where the controller employs the discrete-time measurements only.展开更多
With the accelerating urbanization process,the load demand of urban power grids is constantly increasing,giving rise to a batch of ultra-large urban power grids featuring large electricity demand,dense load distributi...With the accelerating urbanization process,the load demand of urban power grids is constantly increasing,giving rise to a batch of ultra-large urban power grids featuring large electricity demand,dense load distribution,and tight construction land constraints.This paper establishes a network planning method for urban power grids based on series reactors and MMC-MTEDC,focusing on four aspects:short-circuit current suppression,accommodation of external power supply,flexible inter-regional power support,and voltage stability enhancement in load centers.It proposes key indicators including node short-circuit current margin,line thermal stability margin,maximum fault-induced regional power loss,and voltage recovery time,thereby constructing an evaluation system for MMT-MTEDC network planning in urban power grids.Based on the Shenzhen power grid planning data,simulations using DSP software reveal that series reactors reduce short-circuit current by up to 5.0%,while the MMC-MTEDC system enhances node short-circuit margins by 4.212.9%and shortens voltage recovery time by 19.8%.Additionally,the MMC-MTEDC system maintains 3.34-6.76 percentage points higher thermal stability margins than conventional AC systems and enables complete avoidance of external power curtailment during N-2 faults via power reallocation between terminals.Compared with traditional AC or point-to-point HVDC schemes,the proposed hybrid planning method better adapts to the spatial and reliability demands of ultra-large receiving-end grids.This methodology provides practical insights into coordinated AC/DC development under high load density and strong external power reliance.Future work will extend the approach to include electromagnetic transient constraints and lightweight MMC station designs for urban applications.展开更多
The rapid evolution and expanding scale of AI(artificial intelligence)technologies exert unprecedented energy demands on global electrical grids.Powering computationally intensive tasks such as large-scale AI model tr...The rapid evolution and expanding scale of AI(artificial intelligence)technologies exert unprecedented energy demands on global electrical grids.Powering computationally intensive tasks such as large-scale AI model training and widespread real-time inference necessitates substantial electricity consumption,presenting a significant challenge to conventional power infrastructure.This paper examines the critical need for a fundamental shift towards smart energy grids in response to AI’s growing energy footprint.It delves into the symbiotic relationship wherein AI acts as a significant energy consumer while offering the intelligence required for dynamic load management,efficient integration of renewable energy sources,and optimized grid operations.We posit that advanced smart grids are indispensable for facilitating AI’s sustainable growth,underscoring this synergy as a pivotal advancement toward a resilient energy future.展开更多
On the world's highest plateau,a sixty-year energy revolution has quietly reshaped this ancient land.As night falls,the lights of the Barkhor Street in Lhasa flicker on one after another,while in the depths of the...On the world's highest plateau,a sixty-year energy revolution has quietly reshaped this ancient land.As night falls,the lights of the Barkhor Street in Lhasa flicker on one after another,while in the depths of the Changtang grasslands,herding families watch the evening news on their televisions.Behind these ordinary scenes lies the extraordinary journey of Xizang's electric power industry-from nothing to existence,from weakness to strength.展开更多
False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading fail...False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.展开更多
基金supported by the National Natural Science Foundation of China(No.51977080).
文摘With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secure operation.Aiming at the SCC limitations,we use multiple back-toback voltage source converter based(B2B VSC)systems to separate a large-scale AC power grid into two asynchronous power grids.A multi-objective robust optimal secure operation model of large-scale power grid with multiple B2B VSC systems considering the SCC limitation is established based on the AC power flow equations.The decision variables include the on/off states of synchronous generators,power output,terminal voltage,transmission switching,bus sectionalization,and modulation ratios of B2B VSC systems.The influence of inner current sources of renewable energy generators on the system SCC is also considered.To improve the computational efficiency,a mixedinteger convex programming(MICP)framework based on convex relaxation methods including the inscribed N-sided approximation for the nonlinear SCC limitation constraints is proposed.Moreover,combined with the column-and-constraint generation(C&CG)algorithm,a method to directly solve the compromise optimal solution(COS)of the multi-objective robust optimal secure operation model is proposed.Finally,the effectiveness and computational efficiency of the proposed solution method is demonstrated by an actual 4407-bus provincial power grid and the modified IEEE 39-bus power grid,which can reduce the consumed CPU time of solving the COS by more than 90%and obtain a better COS.
文摘The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.
基金the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,for funding this research work through the project number“NBU-FFR-2025-3623-11”.
文摘Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.
基金funded by“The Factors Affecting the Accuracy of Wind Resource Assessment and Comprehensive Post-Evaluation Techniques for Operating Wind Power Projects,”grant number YJ24.002“The Research and Application of Future Medium to Long Term Wind Resource Assessment for Wind Farms Based on Artificial Intelligence Project,”grant number 2023021。
文摘Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.
基金This work was supported by National Key Research and Development Program of China(2018YFB0904000).
文摘In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is relatively simple. Thus, connecting large-capacity wind power units complicates the peak load regulation and stable operation of the power grids in these regions. Most wind turbines use power electronic converter technology, which affects the safety and stability of the power grid differently compared with conventional synchronous generators. Furthermore, fluctuations in wind power cause fluctuations in the output of wind farms, making it difficult to create and implement suitable power generation plans for wind farms. The generation technology and grid connection scheme for wind power and conventional thermal power generation differ considerably. Moreover, the active and reactive power control abilities of wind turbines are weaker than those of thermal power units, necessitating additional equipment to control wind turbines. Hence, to address the aforementioned issues with large-scale wind power generation, this study analyzes the differences between the grid connection and collection strategies for wind power bases and thermal power plants. Based on this analysis, the differences in the power control modes of wind power and thermal power are further investigated. Finally, the stability of different control modes is analyzed through simulation. The findings can be beneficial for the planning and development of large-scale wind power generation farms.
基金supported by the National Key R&D Program of China(2018AAA0101500).
文摘With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.
文摘With the problem of global energy shortage and people’s awareness of energy saving, electric vehicles receive world-wide attention from government to business. Then the load of the power grid will rapidly increase in a short term, and a series of effects will bring to the power grid operation, management, production and planning. With the large-scale penetration of electric vehicles and distributed energy gradually increased, if they can be effectively controlled and regulated, they can play the roles of load shifting, stabling intermittent renewable energy sources, providing emergency power supply and so on. Otherwise they may have a negative impact, which calls for a good interaction of electric vehicles and power grid. Analyzed the status of the current study on the interaction between the electric vehicles and the power grid, this paper builds the material basis, information architecture and the corresponding control method for the interaction from the aspect of the energy and information exchanging, and then discusses the key issues, which makes a useful exploration for the further research.
基金supported by the National Natural Science Foundation of China [No.51579029]Fundamental Research Funds for the Central Universities (No. DUT19JC43)
文摘Large-capacity hydropower transmission from southwestern China to load centers via ultra-high voltage direct current(UHVDC) or ultra-high voltage alternating current(UHVAC) transmission lines is an important measure of the accommodation of large-scale hydropower in China. The East China Grid(ECG) is the main hydropower receiver of the west–east power transmission channel in China. Moreover, it has been subject to a rapidly increasing rate of hydropower integration over the past decade. Currently, large-scale outer hydropower is one of the primary ECG power sources. However, the integration of rapidly increasing outer hydropower into the power grid is subject to a series of severe drawbacks. Therefore, this study considered the load demands and hydropower transmission characteristics for the analysis of several major problems and the determination of appropriate solutions. The power supply-demand balance problem, hydropower transmission schedule problem, and peakshaving problem were considered in this study. Correspondingly, three solutions are suggested in this paper, which include coordination between the outer hydropower and local power sources, an inter-provincial power complementary operation, and the introduction of a market mechanism. The findings of this study can serve as a basis to ensure that the ECG effectively receives an increased amount of outer hydropower in the future.
文摘At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a project of "973 Program". Mr. Zhou, the chief engineer of China Electric Power Research Institute(CEPRI) and an academician of Chinese Academy of Sciences, is the chief scientist in charge of this research project.
基金Under the auspices of National Basic Research Program (No.2007CB210306)
文摘Constructing an industrial system for a large-scale,non-grid-connected wind power industry is a key step towards the diverse utilization of wind power.However,wind power exploitation is not only a technical challenge but an industrial problem as well.The objective of this study is to introduce a concept of large-scale,non-grid-connected wind power(LSNGCWP) industrial zones and establish an evaluation model to assess their industrial arrangement.The data of wind energy,industry,nature resources and socio-economy were collected in this study.Using spatial overlay analysis of geographic information system,this study proposes a spatial arrangement of the LSNGCWP indus-trial zones in the coastal areas of China,which could be summarized as the 'one line and three circles' structure,which will contribute to the optimization of the industrial structure,advance the wind power technology,coordinate the multi-industrial cooperation,and upgrade the industrial transformation of China's coastal areas.
文摘The first stage project of Jiuquan wind energy base with 5.5-GW installed capacity is about to be completed. However, there exist several technical issues such as power transfer capability, electricity accommodation, frequency control and peak load regulation as well as system stability. In addition, the high capital cost and operation cost of the supporting transmission project invested and constructed by the Gansu Provincial Power Company will definitely have significant impacts on the management and economic profit of the Company. Through analysis of the construction and operation cost changes resulting from the wind power collection and delivery project, the author carried out research into the effects of developing large-scale wind power base on the management and economic benefits of power grid enterprises and proposed corresponding suggestions to make the related policies perfect.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010(5400-202199534A-0-5-ZN).
文摘The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.
文摘Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.
文摘This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.
基金supported by the National Natural Science Foundation of China(62403296,62303292,62173218).
文摘Dear Editor,This letter investigates the grid-forming control for power converters.Recently,grid-forming control based on matching of synchronous machines was suggested by using continuous measurements.In the present letter,we suggest a digital implementation using artificial delays where the controller employs the discrete-time measurements only.
基金Shenzhen Power SupplyCo.,Ltd.Grant number 090000KC24040028.
文摘With the accelerating urbanization process,the load demand of urban power grids is constantly increasing,giving rise to a batch of ultra-large urban power grids featuring large electricity demand,dense load distribution,and tight construction land constraints.This paper establishes a network planning method for urban power grids based on series reactors and MMC-MTEDC,focusing on four aspects:short-circuit current suppression,accommodation of external power supply,flexible inter-regional power support,and voltage stability enhancement in load centers.It proposes key indicators including node short-circuit current margin,line thermal stability margin,maximum fault-induced regional power loss,and voltage recovery time,thereby constructing an evaluation system for MMT-MTEDC network planning in urban power grids.Based on the Shenzhen power grid planning data,simulations using DSP software reveal that series reactors reduce short-circuit current by up to 5.0%,while the MMC-MTEDC system enhances node short-circuit margins by 4.212.9%and shortens voltage recovery time by 19.8%.Additionally,the MMC-MTEDC system maintains 3.34-6.76 percentage points higher thermal stability margins than conventional AC systems and enables complete avoidance of external power curtailment during N-2 faults via power reallocation between terminals.Compared with traditional AC or point-to-point HVDC schemes,the proposed hybrid planning method better adapts to the spatial and reliability demands of ultra-large receiving-end grids.This methodology provides practical insights into coordinated AC/DC development under high load density and strong external power reliance.Future work will extend the approach to include electromagnetic transient constraints and lightweight MMC station designs for urban applications.
文摘The rapid evolution and expanding scale of AI(artificial intelligence)technologies exert unprecedented energy demands on global electrical grids.Powering computationally intensive tasks such as large-scale AI model training and widespread real-time inference necessitates substantial electricity consumption,presenting a significant challenge to conventional power infrastructure.This paper examines the critical need for a fundamental shift towards smart energy grids in response to AI’s growing energy footprint.It delves into the symbiotic relationship wherein AI acts as a significant energy consumer while offering the intelligence required for dynamic load management,efficient integration of renewable energy sources,and optimized grid operations.We posit that advanced smart grids are indispensable for facilitating AI’s sustainable growth,underscoring this synergy as a pivotal advancement toward a resilient energy future.
文摘On the world's highest plateau,a sixty-year energy revolution has quietly reshaped this ancient land.As night falls,the lights of the Barkhor Street in Lhasa flicker on one after another,while in the depths of the Changtang grasslands,herding families watch the evening news on their televisions.Behind these ordinary scenes lies the extraordinary journey of Xizang's electric power industry-from nothing to existence,from weakness to strength.
基金supported by National Key Research and Development Plan of China(No.2022YFB3103304).
文摘False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.
