With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable ener...With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.展开更多
When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicator...When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be conducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. Consideringthat the reinforcement learning model performs poorly in satisfying safety constraints, a safe action-correctionframework is proposed to modify the learning model. In the framework, the action of load shedding is correctedaccording to sensitivity analysis results under a small discrete increment so as to match the constraints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.展开更多
Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calcul...Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid.Therefore,it cannot provide carbon factor information beforehand.To address this issue,a prediction model based on the graph attention network is proposed.The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised network using the loads of the grid nodes and the corresponding carbon factor data.The network extracts features and transmits information more suitable for the power system and can flexibly adjust the equivalent topology,thereby increasing the diversity of the structure.Its input and output data are simple,without the power grid parameters.We demonstrated its effect by testing IEEE-39 bus and IEEE-118 bus systems with average error rates of 2.46%and 2.51%.展开更多
After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and de...After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.展开更多
The China Fusion Engineering Test Reactor plans to build a 200 k V/25 A acceleration grid power supply(AGPS)for the negative-ion-based neutral beam injector prototype system.The AGPS uses a rectifier-inverter-isolated...The China Fusion Engineering Test Reactor plans to build a 200 k V/25 A acceleration grid power supply(AGPS)for the negative-ion-based neutral beam injector prototype system.The AGPS uses a rectifier-inverter-isolated step-up structure.There is a DC bus between the rectifier and the inverter.In order to limit DC bus voltage ripple and transient fluctuations,a large number of capacitors are used,which degrades the reliability of the power supply and occupies a large amount of space.This work finds that due to the difference in the turn-off time of the rectifier and the inverter,the capacitance mainly depends on the rectifier current when the inverter is turned off.On this basis,an active power filter(APF)scheme is proposed to absorb the current.To enhance the dynamic response ability of the APF,model predictive control is adopted.In this paper,the circuit structure of the APF is introduced,the prediction model is deduced,the corresponding control strategy and signal detection method are proposed,and the simulation and experimental results show that APF can track the transient current of the DC bus and reduce the voltage fluctuation significantly.展开更多
The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challeng...The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.展开更多
To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article com...To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.展开更多
This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve co...This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsiveness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet current and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.展开更多
This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(...This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.展开更多
China Southern Power Grid is a unique EHV AC/DC hybrid transmission network that operates in China. In its service area, the distribution of energy resources and the development of economy are extremely unbalanced, so...China Southern Power Grid is a unique EHV AC/DC hybrid transmission network that operates in China. In its service area, the distribution of energy resources and the development of economy are extremely unbalanced, so long-distance and bulk power transmission are needed; besides, the geography and climate conditions are serious, rains, fogs, lightning and typhoon as well as high temperature are common all the year round. Facing these challenges, the power grid enhanced stability control, improved the equipment and strengthen the network structure. In the future, the power grid plans to optimize the disposition of power sources and build digitalized power system.展开更多
The power grid operation process is complex,and many operation process data involve national security,business secrets,and user privacy.Meanwhile,labeled datasets may exist in many different operation platforms,but th...The power grid operation process is complex,and many operation process data involve national security,business secrets,and user privacy.Meanwhile,labeled datasets may exist in many different operation platforms,but they cannot be directly shared since power grid data is highly privacysensitive.How to use these multi-source heterogeneous data as much as possible to build a power grid knowledge map under the premise of protecting privacy security has become an urgent problem in developing smart grid.Therefore,this paper proposes federated learning named entity recognition method for the power grid field,aiming to solve the problem of building a named entity recognition model covering the entire power grid process training by data with different security requirements.We decompose the named entity recognition(NER)model FLAT(Chinese NER Using Flat-Lattice Transformer)in each platform into a global part and a local part.The local part is used to capture the characteristics of the local data in each platform and is updated using locally labeled data.The global part is learned across different operation platforms to capture the shared NER knowledge.Its local gradients fromdifferent platforms are aggregated to update the global model,which is further delivered to each platform to update their global part.Experiments on two publicly available Chinese datasets and one power grid dataset validate the effectiveness of our method.展开更多
Climate change is becoming an important issue in all fields of infrastructure development.Electricity plays a core role in the decarbonized energy system’s path to a regional zero-emission pattern.A well-built trans-...Climate change is becoming an important issue in all fields of infrastructure development.Electricity plays a core role in the decarbonized energy system’s path to a regional zero-emission pattern.A well-built trans-Mediterranean backbone grid can hedge the profound evolution of regional power generation,transmission,and consumption.To date,only Turkey and the Maghreb countries(i.e.,Morocco,Algeria,and Tunisia)are connected with the Continental European Synchronous Area.Other south-and east-shore countries have insufficient interconnection infrastructures and synchronization difficulties that have proven to be major hurdles to the implementation of large-scale solar and wind projects and achievement of climate goals.This study analyzes the current trans-boundary grid interconnections and power and carbon emission portfolios in the Mediterranean region.To align with the recently launched new climate target‘Fit for 55’program and the accelerated large-scale renewables target,a holistic review of projected trans-Mediterranean grids and their market,technical,and financial obstacles of implementation was conducted.For south-and east-shore countries,major legal and regulatory barriers encompassing non-liberalized market structure,regulation gaps of taxation and transmission tariffs,and the private sector’s access rights need to be removed.Enhancement of domestic grids,substations,and harmonized grid codes and frequency,voltage,and communication technology standards among all trans-Mediterranean countries are physical prerequisites for implementing the Trans-Mediterranean Electricity Market.In addition,the mobilization of capital instruments along with private and international investments is indispensable for the realization of supranational transmission projects.As the final section of the decarbonization roadmap,the development of electric appliances,equipment,and vehicles with higher efficiency is inevitable in the decarbonized building,transportation,and industry sectors.展开更多
Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,t...Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data.This article proposes a physics-informed artificial intelligence(AI)surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance.The incomplete dataset,built with numerical weather prediction data,historical wind power generation,and weather factors data,is augmented based on generative adversarial networks.After augmentation,the enriched data is then fed into a multiple AI surrogates model constructed by two extreme learning machine networks to train the forecasting model for wind power.Therefore,the forecasting models’accuracy and generalization ability are improved by mining the implicit physics information from the incomplete dataset.An incomplete dataset gathered from a wind farm in North China,containing only 15 days of weather and wind power generation data withmissing points caused by occasional shutdowns,is utilized to verify the proposed method’s performance.Compared with other probabilistic forecastingmethods,the proposed method shows better accuracy and probabilistic performance on the same incomplete dataset,which highlights its potential for more flexible and sensitive maintenance of smart grids in smart cities.展开更多
The planning environmental impact assessment (EIA) of transmission and transformation power grid at levels of 500 and 220 kV had been finished completely in the 13 municipalities of Jiangsu Province by the end of 20...The planning environmental impact assessment (EIA) of transmission and transformation power grid at levels of 500 and 220 kV had been finished completely in the 13 municipalities of Jiangsu Province by the end of 2012, which played important roles in guiding and planning the following transmission and transformation projects in environmental protection. In this paper, through the detail analysis on the objective and significance of the planning EIA of transmission and transformation power grid, legal basis and planning EIA practices, some suggestions and thinking about the planning EIA of transmission and transformation power grid were put forward.展开更多
The acceleration grid power supply(AGPS)rated 200 kV/25 A is a key component devoted to supply the acceleration grids of the China fusion engineering test reactor negative-ion-based neutral beam injector(N-NBI)prototy...The acceleration grid power supply(AGPS)rated 200 kV/25 A is a key component devoted to supply the acceleration grids of the China fusion engineering test reactor negative-ion-based neutral beam injector(N-NBI)prototype system.This paper focused on the design and control of the AGPS conversion system(AGPS-CS),with emphasis on the requirement of the wide range output voltage and rise time.A voltage regulation switch at the front of step-down transformer is applied to optimize the grid current and DC-link voltage.Moreover,a new feedforward control strategy with piecewise PI compensator is proposed to improve the characteristics of AGPS.The simulation results of the proposed AGPS-CS are presented,proving the performance of the power supply to achieve the desired requirements.展开更多
With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have cho...With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have chosen different indexing methods in the filtering stage to obtain more optimized query results because currently there is no uniform and efficient indexing mechanism that achieves good query results. In the traditional algorithm, the hash table for index storage is prone to "collision" problems, which decrease the index construction efficiency. Aiming at the problem of quick index entry, based on the construction of frequent subgraph indexes, a method of serialized storage optimization based on multiple hash tables is proposed. This method mainly uses the exploration sequence to make the keywords evenly distributed; it avoids conflicts of the stored procedure and performs a quick search of the index. The proposed algorithm mainly adopts the "filterverify" mechanism; in the filtering stage, the index is first established offline, and then the frequent subgraphs are found using the "contains logic" rule to obtain the candidate set. Experimental results show that this method can reduce the time and scale of candidate set generation and improve query efficiency.展开更多
This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution pric...This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.展开更多
Demand response has been intensively studied in recent years. It can motivate customers to change their consumption patterns according to the dynamic(time-varying) electricity price, which is considered to be the most...Demand response has been intensively studied in recent years. It can motivate customers to change their consumption patterns according to the dynamic(time-varying) electricity price, which is considered to be the most cost-effective and reliable solution for smoothing the demand curve. However, many existing schemes, based on users' demand request in each period, require users to consume their requested electricity exactly, which sometimes causes inconvenience and losses to the utility, because customers cannot always be able to consume the accurate electricity demand due to various personal reasons. In this paper, we tackle this problem in a novel approach. Instead of charging after consumption, we adopt the prepayment mechanism to implement power request. Furthermore, we propose a trading market running by the control center to cope with the users' dynamic demand. It is noteworthy that both users' original demand and trading records are protected against potential adversaries including the curious control center. Through the numerical simulation, we demonstrate that our scheme is highly efficient in both computation and communication.展开更多
基金supported by State Grid Corporation of China Project“Research and Application of Key Technologies for Active Power Control in Regional Power Grid with High Penetration of Distributed Renewable Generation”(5108-202316044A-1-1-ZN).
文摘With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.
基金the Incubation Project of State Grid Jiangsu Corporation of China“Construction and Application of Intelligent Load Transferring Platform for Active Distribution Networks”(JF2023031).
文摘When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be conducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. Consideringthat the reinforcement learning model performs poorly in satisfying safety constraints, a safe action-correctionframework is proposed to modify the learning model. In the framework, the action of load shedding is correctedaccording to sensitivity analysis results under a small discrete increment so as to match the constraints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.
基金This work is supposed by the Science and Technology Projects of China Southern Power Grid(YNKJXM20222402).
文摘Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid.Therefore,it cannot provide carbon factor information beforehand.To address this issue,a prediction model based on the graph attention network is proposed.The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised network using the loads of the grid nodes and the corresponding carbon factor data.The network extracts features and transmits information more suitable for the power system and can flexibly adjust the equivalent topology,thereby increasing the diversity of the structure.Its input and output data are simple,without the power grid parameters.We demonstrated its effect by testing IEEE-39 bus and IEEE-118 bus systems with average error rates of 2.46%and 2.51%.
基金supported by the State Grid Henan Economic Research Institute Science and Technology Project“Calculation and Demonstration of Distributed Photovoltaic Open Capacity Based on Multi-Source Heterogeneous Data”(5217L0230013).
文摘After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.
基金supported in part by the National Key Research and Development Program of China(No.2017YFE0300104)in part by National Natural Science Foundation of China(No.51821005)。
文摘The China Fusion Engineering Test Reactor plans to build a 200 k V/25 A acceleration grid power supply(AGPS)for the negative-ion-based neutral beam injector prototype system.The AGPS uses a rectifier-inverter-isolated step-up structure.There is a DC bus between the rectifier and the inverter.In order to limit DC bus voltage ripple and transient fluctuations,a large number of capacitors are used,which degrades the reliability of the power supply and occupies a large amount of space.This work finds that due to the difference in the turn-off time of the rectifier and the inverter,the capacitance mainly depends on the rectifier current when the inverter is turned off.On this basis,an active power filter(APF)scheme is proposed to absorb the current.To enhance the dynamic response ability of the APF,model predictive control is adopted.In this paper,the circuit structure of the APF is introduced,the prediction model is deduced,the corresponding control strategy and signal detection method are proposed,and the simulation and experimental results show that APF can track the transient current of the DC bus and reduce the voltage fluctuation significantly.
基金Department of Navy Awards N00014-22-1-2001 and N00014-23-1-2124 issued by the Office of Naval Research。
文摘The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.
基金funded by National Key Research and Development Program of China (2021YFB2601400)。
文摘To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.
文摘This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsiveness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet current and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.
文摘This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.
文摘China Southern Power Grid is a unique EHV AC/DC hybrid transmission network that operates in China. In its service area, the distribution of energy resources and the development of economy are extremely unbalanced, so long-distance and bulk power transmission are needed; besides, the geography and climate conditions are serious, rains, fogs, lightning and typhoon as well as high temperature are common all the year round. Facing these challenges, the power grid enhanced stability control, improved the equipment and strengthen the network structure. In the future, the power grid plans to optimize the disposition of power sources and build digitalized power system.
基金Thisworkwas supported by State Grid Science and TechnologyResearch Program(SGSCJY00NYJS2200026).
文摘The power grid operation process is complex,and many operation process data involve national security,business secrets,and user privacy.Meanwhile,labeled datasets may exist in many different operation platforms,but they cannot be directly shared since power grid data is highly privacysensitive.How to use these multi-source heterogeneous data as much as possible to build a power grid knowledge map under the premise of protecting privacy security has become an urgent problem in developing smart grid.Therefore,this paper proposes federated learning named entity recognition method for the power grid field,aiming to solve the problem of building a named entity recognition model covering the entire power grid process training by data with different security requirements.We decompose the named entity recognition(NER)model FLAT(Chinese NER Using Flat-Lattice Transformer)in each platform into a global part and a local part.The local part is used to capture the characteristics of the local data in each platform and is updated using locally labeled data.The global part is learned across different operation platforms to capture the shared NER knowledge.Its local gradients fromdifferent platforms are aggregated to update the global model,which is further delivered to each platform to update their global part.Experiments on two publicly available Chinese datasets and one power grid dataset validate the effectiveness of our method.
基金supported by the National Science Foundation of China(Grant No.41701232).
文摘Climate change is becoming an important issue in all fields of infrastructure development.Electricity plays a core role in the decarbonized energy system’s path to a regional zero-emission pattern.A well-built trans-Mediterranean backbone grid can hedge the profound evolution of regional power generation,transmission,and consumption.To date,only Turkey and the Maghreb countries(i.e.,Morocco,Algeria,and Tunisia)are connected with the Continental European Synchronous Area.Other south-and east-shore countries have insufficient interconnection infrastructures and synchronization difficulties that have proven to be major hurdles to the implementation of large-scale solar and wind projects and achievement of climate goals.This study analyzes the current trans-boundary grid interconnections and power and carbon emission portfolios in the Mediterranean region.To align with the recently launched new climate target‘Fit for 55’program and the accelerated large-scale renewables target,a holistic review of projected trans-Mediterranean grids and their market,technical,and financial obstacles of implementation was conducted.For south-and east-shore countries,major legal and regulatory barriers encompassing non-liberalized market structure,regulation gaps of taxation and transmission tariffs,and the private sector’s access rights need to be removed.Enhancement of domestic grids,substations,and harmonized grid codes and frequency,voltage,and communication technology standards among all trans-Mediterranean countries are physical prerequisites for implementing the Trans-Mediterranean Electricity Market.In addition,the mobilization of capital instruments along with private and international investments is indispensable for the realization of supranational transmission projects.As the final section of the decarbonization roadmap,the development of electric appliances,equipment,and vehicles with higher efficiency is inevitable in the decarbonized building,transportation,and industry sectors.
基金funded by the National Natural Science Foundation of China under Grant 62273022.
文摘Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data.This article proposes a physics-informed artificial intelligence(AI)surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance.The incomplete dataset,built with numerical weather prediction data,historical wind power generation,and weather factors data,is augmented based on generative adversarial networks.After augmentation,the enriched data is then fed into a multiple AI surrogates model constructed by two extreme learning machine networks to train the forecasting model for wind power.Therefore,the forecasting models’accuracy and generalization ability are improved by mining the implicit physics information from the incomplete dataset.An incomplete dataset gathered from a wind farm in North China,containing only 15 days of weather and wind power generation data withmissing points caused by occasional shutdowns,is utilized to verify the proposed method’s performance.Compared with other probabilistic forecastingmethods,the proposed method shows better accuracy and probabilistic performance on the same incomplete dataset,which highlights its potential for more flexible and sensitive maintenance of smart grids in smart cities.
基金Supported by the National Key Technology R&D Program(2012BAC20B1003)the Key National Social Science Fund Project(12&ZD214)the Special Fund Project for the Scientific Research of the Environmental Protection Welfare Industry(201209001)
文摘The planning environmental impact assessment (EIA) of transmission and transformation power grid at levels of 500 and 220 kV had been finished completely in the 13 municipalities of Jiangsu Province by the end of 2012, which played important roles in guiding and planning the following transmission and transformation projects in environmental protection. In this paper, through the detail analysis on the objective and significance of the planning EIA of transmission and transformation power grid, legal basis and planning EIA practices, some suggestions and thinking about the planning EIA of transmission and transformation power grid were put forward.
基金This work is supported by the National Key R&D Program of China under Grant No.2017YFE0300104National Natural Science Foundation of China(Nos.51707073 and 51821005).
文摘The acceleration grid power supply(AGPS)rated 200 kV/25 A is a key component devoted to supply the acceleration grids of the China fusion engineering test reactor negative-ion-based neutral beam injector(N-NBI)prototype system.This paper focused on the design and control of the AGPS conversion system(AGPS-CS),with emphasis on the requirement of the wide range output voltage and rise time.A voltage regulation switch at the front of step-down transformer is applied to optimize the grid current and DC-link voltage.Moreover,a new feedforward control strategy with piecewise PI compensator is proposed to improve the characteristics of AGPS.The simulation results of the proposed AGPS-CS are presented,proving the performance of the power supply to achieve the desired requirements.
基金supported by the State Grid Science and Technology Project (Title: Research on High Performance Analysis Technology of Power Grid GIS Topology Based on Graph Database, 5455HJ160005)
文摘With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have chosen different indexing methods in the filtering stage to obtain more optimized query results because currently there is no uniform and efficient indexing mechanism that achieves good query results. In the traditional algorithm, the hash table for index storage is prone to "collision" problems, which decrease the index construction efficiency. Aiming at the problem of quick index entry, based on the construction of frequent subgraph indexes, a method of serialized storage optimization based on multiple hash tables is proposed. This method mainly uses the exploration sequence to make the keywords evenly distributed; it avoids conflicts of the stored procedure and performs a quick search of the index. The proposed algorithm mainly adopts the "filterverify" mechanism; in the filtering stage, the index is first established offline, and then the frequent subgraphs are found using the "contains logic" rule to obtain the candidate set. Experimental results show that this method can reduce the time and scale of candidate set generation and improve query efficiency.
基金the National Key Research and Development Program of China(Grant No.2020YFB1707804)the 2018 Key Projects of Philosophy and Social Sciences Research(Grant No.18JZD032)Natural Science Foundation of Hebei Province(Grant No.G2020403008).
文摘This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.
基金supported by the National Key Research and Development Plan of China under Grant No.2016YFB0800301the Fund of Science and Technology on Communication Networks Laboratory under Grant No.KX162600024Youth Innovation Promotion Association CAS under Grant No.2016394
文摘Demand response has been intensively studied in recent years. It can motivate customers to change their consumption patterns according to the dynamic(time-varying) electricity price, which is considered to be the most cost-effective and reliable solution for smoothing the demand curve. However, many existing schemes, based on users' demand request in each period, require users to consume their requested electricity exactly, which sometimes causes inconvenience and losses to the utility, because customers cannot always be able to consume the accurate electricity demand due to various personal reasons. In this paper, we tackle this problem in a novel approach. Instead of charging after consumption, we adopt the prepayment mechanism to implement power request. Furthermore, we propose a trading market running by the control center to cope with the users' dynamic demand. It is noteworthy that both users' original demand and trading records are protected against potential adversaries including the curious control center. Through the numerical simulation, we demonstrate that our scheme is highly efficient in both computation and communication.