Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
The complex working environment of distribution networks tends to cause impermanent single-phase-to-ground(SPG)fault,and high-temperature ground fault arc is prone to endanger lives and power equipment,resulting in la...The complex working environment of distribution networks tends to cause impermanent single-phase-to-ground(SPG)fault,and high-temperature ground fault arc is prone to endanger lives and power equipment,resulting in large-scale power outages and fire accidents.Thus,fault arc should be extinguished in time.Meanwhile,stable operation conditions of distribution networks and reliable load power supply should be guaranteed to provide high-quality customer service.This paper proposes an active mitigation strategy for SPG fault,and provide active and reactive power compensation at the same time by utilizing an improved flexible power electronic equipment(FPEE)with dc-link sources.These controls are decoupled from each other,so utilization of FPEE is maximized as much as possible.When a SPG fault occurs in distribution networks,FPEE can output,simultaneously,active power,reactive power,and SPG fault compensation current by controlling output current on the d,q,0 coordinate system,respectively.During normal operation of distribution networks,the FPEE can be used as a virtual synchronous generator to compensate load power and its fluctuation.The proposed simultaneous multi-function can also be applied in other cases.Simulation cases are implemented to verify principles and practicability.展开更多
In contemporary medium-voltage distribution networks heavily penetrated by distributed energy resources(DERs),the harmonic components injected by power-electronic interfacing converters,together with the inherently in...In contemporary medium-voltage distribution networks heavily penetrated by distributed energy resources(DERs),the harmonic components injected by power-electronic interfacing converters,together with the inherently intermittent output of renewable generation,distort the zero-sequence current and continuously reshape its frequency spectrum.As a result,single-line-to-ground(SLG)faults exhibit a pronounced,strongly non-stationary behaviour that varies with operating point,load mix and DER dispatch.Under such circumstances the performance of traditional rule-based algorithms—or methods that rely solely on steady-state frequency-domain indicators—degrades sharply,and they no longer satisfy the accuracy and universality required by practical protection systems.To overcome these shortcomings,the present study develops an SLG-fault identification scheme that transforms the zero-sequence currentwaveforminto two-dimensional image representations and processes themwith a convolutional neural network(CNN).First,the causes of sample-distribution imbalance are analysed in detail by considering different neutralgrounding configurations,fault-inception mechanisms and the statistical probability of fault occurrence on each phase.Building on these insights,a discriminator network incorporating a Convolutional Block Attention Module(CBAM)is designed to autonomously extract multi-layer spatial-spectral features,while Gradient-weighted Class Activation Mapping(Grad-CAM)is employed to visualise the contribution of every salient image region,thereby enhancing interpretability.A comprehensive simulation platform is subsequently established for a DER-rich distribution system encompassing several representative topologies,feeder lengths and DER penetration levels.Large numbers of realistic SLG-fault scenarios are generated—including noise and measurement uncertainty—and are used to train,validate and test the proposed model.Extensive simulation campaigns,corroborated by field measurements from an actual utility network,demonstrate that the proposed approach attains an SLG-fault identification accuracy approaching 100 percent and maintains robust performance under severe noise conditions,confirming its suitability for real-world engineering applications.展开更多
Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variat...Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition(VMD)and Channel Attention Mechanism.First,Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical power.Second,the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition(VMD).Finally,the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM model.In this model,the convolutional neural network(CNN)and channel attention mechanism dynamically adjust the weights while capturing the spatial features of the input data to improve the discriminative ability of key features.The extracted data is then fed into the bidirectional long short-term memory network(BiLSTM)to capture the time-series features,and the final output is the prediction result.The verification is conducted using a dataset from a distributed photovoltaic power station in the Northwest region of China.The results show that compared with other prediction methods,the method proposed in this paper has a higher prediction accuracy,which helps to improve the proportion of distributed PV access to the grid,and can guarantee the safe and stable operation of the power grid.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to...A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.展开更多
The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distribute...The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.展开更多
This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for man...This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.展开更多
A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete ...A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.展开更多
This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded(UBB)external disturbance and measurement noise.In order to ...This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded(UBB)external disturbance and measurement noise.In order to improve the estimation reliability and performance in cases of poor data collection and potential communication interruption,a multisensor network configuration is presented to cooperatively measure the vehicular yaw rate,and further compute local state and fault estimates.Toward this aim,an augmented descriptor vehicle model is first established,where the unknown sensor fault is modeled as an auxiliary state of the system model.Then,a new distributed ellipsoidal set-membership estimation approach is developed so as to construct an optimized bounding ellipsoidal set which guarantees to contain the vehicle’s true state and the sensor fault at each time step despite the existence of UBB disturbance and measurement noises.Furthermore,a convex optimization algorithm is put forward such that the gain matrix of each distributed estimator can be recursively obtained.Finally,simulation results are provided to validate the effectiveness of the proposed approach.展开更多
In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm i...In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.展开更多
The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/D...The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/DC hybrid distribution network is put forward according to the demands of power grid, with advantages of accepting DG and DC loads, while clearing DC fault by blocking the clamping double sub-module(CDSM) of input stage. Then, this paper shows the typical structure of AC/DC distribution network that is hand in hand. Based on the new topology, this paper designs the control and modulation strategies of each stage, where the outer loop controller of input stage is emphasized for its twocontrol mode. At last, the rationality of new topology and the validity of control strategies are verified by the steady and dynamic state simulation. At the same time, the simulation results highlight the role of PET in energy regulation.展开更多
The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and e...The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.展开更多
The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the exis...The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution network.Firstly,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are established.Additionally,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the EVcharger.Amultiobjective optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy consumption.Then,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time scales.Themulti-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control optimization.Simulation results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution network.It effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.展开更多
In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line select...In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line selection always existed in existing methods. According to the characteristics that transient current was different between the fault feeder and other faultless feeders, wavelet transformation was performed on data of the transient current within a power frequency cycle after the fault occurred. Based on different fault angles, wavelet energy in corresponding frequency band was chosen to compare. The result was that wavelet energy in fault feeder was the largest of all, and it was larger than sum of those in other faultless feeders, when the bus broke down, the disparity between each wavelet energy was not significant. Fault line could be selected out by the criterion above. The results of MATLAB/simulink simulation experiment indicated that this method had anti-interference capacity and was feasible.展开更多
In order to improve the voltage quality of rural power distribution network, the series capacitor in distribution lines is proposed. The principle of series capacitor compensation technology to improve the quality of ...In order to improve the voltage quality of rural power distribution network, the series capacitor in distribution lines is proposed. The principle of series capacitor compensation technology to improve the quality of rural power distribution lines voltage is analyzed. The real rural power distribution network simulation model is established by Power System Power System Analysis Software Package (PSASP). Simulation analysis the effect of series capacitor compensation technology to improve the voltage quality of rural power distribution network, The simulation results show that the series capacitor compensation can effectively improve the voltage quality and reduce network losses and improve the transmission capacity of rural power distribution network.展开更多
The rapid growth of distributed photovoltaic(PV)has remarkable influence for the safe and economic operation of power systems.In view of the wide geographical distribution and a large number of distributed PV power st...The rapid growth of distributed photovoltaic(PV)has remarkable influence for the safe and economic operation of power systems.In view of the wide geographical distribution and a large number of distributed PV power stations,the current situation is that it is dificult to access the current dispatch data network.According to the temporal and spatial characteristics of distributed PV,a graph convolution algorithm based on adaptive learning of adjacency matrix is proposed to estimate the real-time output of distributed PV in regional power grid.The actual case study shows that the adaptive graph convolution model gives different adjacency matrixes for different PV stations,which makes the corresponding output estimation algorithm have higher accuracy.展开更多
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
基金supported in part by the National Natural Science Foundation of China(No.51677030).
文摘The complex working environment of distribution networks tends to cause impermanent single-phase-to-ground(SPG)fault,and high-temperature ground fault arc is prone to endanger lives and power equipment,resulting in large-scale power outages and fire accidents.Thus,fault arc should be extinguished in time.Meanwhile,stable operation conditions of distribution networks and reliable load power supply should be guaranteed to provide high-quality customer service.This paper proposes an active mitigation strategy for SPG fault,and provide active and reactive power compensation at the same time by utilizing an improved flexible power electronic equipment(FPEE)with dc-link sources.These controls are decoupled from each other,so utilization of FPEE is maximized as much as possible.When a SPG fault occurs in distribution networks,FPEE can output,simultaneously,active power,reactive power,and SPG fault compensation current by controlling output current on the d,q,0 coordinate system,respectively.During normal operation of distribution networks,the FPEE can be used as a virtual synchronous generator to compensate load power and its fluctuation.The proposed simultaneous multi-function can also be applied in other cases.Simulation cases are implemented to verify principles and practicability.
基金supported by the Science and Technology Program of China Southern Power Grid(031800KC23120003).
文摘In contemporary medium-voltage distribution networks heavily penetrated by distributed energy resources(DERs),the harmonic components injected by power-electronic interfacing converters,together with the inherently intermittent output of renewable generation,distort the zero-sequence current and continuously reshape its frequency spectrum.As a result,single-line-to-ground(SLG)faults exhibit a pronounced,strongly non-stationary behaviour that varies with operating point,load mix and DER dispatch.Under such circumstances the performance of traditional rule-based algorithms—or methods that rely solely on steady-state frequency-domain indicators—degrades sharply,and they no longer satisfy the accuracy and universality required by practical protection systems.To overcome these shortcomings,the present study develops an SLG-fault identification scheme that transforms the zero-sequence currentwaveforminto two-dimensional image representations and processes themwith a convolutional neural network(CNN).First,the causes of sample-distribution imbalance are analysed in detail by considering different neutralgrounding configurations,fault-inception mechanisms and the statistical probability of fault occurrence on each phase.Building on these insights,a discriminator network incorporating a Convolutional Block Attention Module(CBAM)is designed to autonomously extract multi-layer spatial-spectral features,while Gradient-weighted Class Activation Mapping(Grad-CAM)is employed to visualise the contribution of every salient image region,thereby enhancing interpretability.A comprehensive simulation platform is subsequently established for a DER-rich distribution system encompassing several representative topologies,feeder lengths and DER penetration levels.Large numbers of realistic SLG-fault scenarios are generated—including noise and measurement uncertainty—and are used to train,validate and test the proposed model.Extensive simulation campaigns,corroborated by field measurements from an actual utility network,demonstrate that the proposed approach attains an SLG-fault identification accuracy approaching 100 percent and maintains robust performance under severe noise conditions,confirming its suitability for real-world engineering applications.
基金supported by the Inner Mongolia Power Company 2024 Staff Innovation Studio Innovation Project“Research on Cluster Output Prediction and Group Control Technology for County-Wide Distributed Photovoltaic Construction”.
文摘Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition(VMD)and Channel Attention Mechanism.First,Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical power.Second,the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition(VMD).Finally,the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM model.In this model,the convolutional neural network(CNN)and channel attention mechanism dynamically adjust the weights while capturing the spatial features of the input data to improve the discriminative ability of key features.The extracted data is then fed into the bidirectional long short-term memory network(BiLSTM)to capture the time-series features,and the final output is the prediction result.The verification is conducted using a dataset from a distributed photovoltaic power station in the Northwest region of China.The results show that compared with other prediction methods,the method proposed in this paper has a higher prediction accuracy,which helps to improve the proportion of distributed PV access to the grid,and can guarantee the safe and stable operation of the power grid.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
文摘A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.
文摘The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.
文摘This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.
文摘A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.
基金supported by National Natural Science Foundation of China(61273108)the Fundamental Research Funds for the Central Universities(106112013CDJZR175501)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry
文摘This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded(UBB)external disturbance and measurement noise.In order to improve the estimation reliability and performance in cases of poor data collection and potential communication interruption,a multisensor network configuration is presented to cooperatively measure the vehicular yaw rate,and further compute local state and fault estimates.Toward this aim,an augmented descriptor vehicle model is first established,where the unknown sensor fault is modeled as an auxiliary state of the system model.Then,a new distributed ellipsoidal set-membership estimation approach is developed so as to construct an optimized bounding ellipsoidal set which guarantees to contain the vehicle’s true state and the sensor fault at each time step despite the existence of UBB disturbance and measurement noises.Furthermore,a convex optimization algorithm is put forward such that the gain matrix of each distributed estimator can be recursively obtained.Finally,simulation results are provided to validate the effectiveness of the proposed approach.
基金This work is supported by the project of Hebei power technology of state grid from 2018 to 2019:Research and application of real-time situation assessment and visualization(SZKJXM20170445).
文摘In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.
基金supported by National Key Research and Development Program of China (2016YFB0900500,2017YFB0903100)the State Grid Science and Technology Project (SGRI-DL-F1-51-011)
文摘The AC/DC hybrid distribution network is one of the trends in distribution network development, which poses great challenges to the traditional distribution transformer. In this paper, a new topology suitable for AC/DC hybrid distribution network is put forward according to the demands of power grid, with advantages of accepting DG and DC loads, while clearing DC fault by blocking the clamping double sub-module(CDSM) of input stage. Then, this paper shows the typical structure of AC/DC distribution network that is hand in hand. Based on the new topology, this paper designs the control and modulation strategies of each stage, where the outer loop controller of input stage is emphasized for its twocontrol mode. At last, the rationality of new topology and the validity of control strategies are verified by the steady and dynamic state simulation. At the same time, the simulation results highlight the role of PET in energy regulation.
文摘The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.
基金funded by the State Grid Corporation Science and Technology Project(5108-202218280A-2-391-XG).
文摘The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution network.Firstly,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are established.Additionally,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the EVcharger.Amultiobjective optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy consumption.Then,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time scales.Themulti-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control optimization.Simulation results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution network.It effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.
文摘In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line selection always existed in existing methods. According to the characteristics that transient current was different between the fault feeder and other faultless feeders, wavelet transformation was performed on data of the transient current within a power frequency cycle after the fault occurred. Based on different fault angles, wavelet energy in corresponding frequency band was chosen to compare. The result was that wavelet energy in fault feeder was the largest of all, and it was larger than sum of those in other faultless feeders, when the bus broke down, the disparity between each wavelet energy was not significant. Fault line could be selected out by the criterion above. The results of MATLAB/simulink simulation experiment indicated that this method had anti-interference capacity and was feasible.
文摘In order to improve the voltage quality of rural power distribution network, the series capacitor in distribution lines is proposed. The principle of series capacitor compensation technology to improve the quality of rural power distribution lines voltage is analyzed. The real rural power distribution network simulation model is established by Power System Power System Analysis Software Package (PSASP). Simulation analysis the effect of series capacitor compensation technology to improve the voltage quality of rural power distribution network, The simulation results show that the series capacitor compensation can effectively improve the voltage quality and reduce network losses and improve the transmission capacity of rural power distribution network.
基金the Science and Technology Program of State Grid Corporation of China(No.5211TZ1900S6)。
文摘The rapid growth of distributed photovoltaic(PV)has remarkable influence for the safe and economic operation of power systems.In view of the wide geographical distribution and a large number of distributed PV power stations,the current situation is that it is dificult to access the current dispatch data network.According to the temporal and spatial characteristics of distributed PV,a graph convolution algorithm based on adaptive learning of adjacency matrix is proposed to estimate the real-time output of distributed PV in regional power grid.The actual case study shows that the adaptive graph convolution model gives different adjacency matrixes for different PV stations,which makes the corresponding output estimation algorithm have higher accuracy.
