为了演示和验证稳定器设计的就地相位补偿法在多机电力系统中的应用,介绍在多机电力系统中,就地补偿设计稳定器的2个应用实例。第1个实例是在多机电力系统中就地补偿设计电力系统稳定器（power system stabilizer,PSS）,阻尼电力系统局...为了演示和验证稳定器设计的就地相位补偿法在多机电力系统中的应用,介绍在多机电力系统中,就地补偿设计稳定器的2个应用实例。第1个实例是在多机电力系统中就地补偿设计电力系统稳定器（power system stabilizer,PSS）,阻尼电力系统局部模振荡。第2个实例是就地补偿设计附加在静态同步补偿器（static synchronous compensator,STATCOM）上的稳定器,抑制多机电力系统中的区域模振荡,并给出在一个16机电力系统中的应用计算和仿真结果。展开更多
The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission ...The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).展开更多
The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and tra...The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.展开更多
This paper describes a stabilization effect after installating an adjustable speed generator (ASG) in a multi machine power system. A personal computer based ASG module has been de veloped for the simulations in...This paper describes a stabilization effect after installating an adjustable speed generator (ASG) in a multi machine power system. A personal computer based ASG module has been de veloped for the simulations in parallel with the analog power system simulator i n the Research Laboratory of the Kyushu Electric Power Co. The three phase ins t antaneous value based ASG model has been developed in the Matlab/Simulink envir onment for its detailed and real time simulations, which have been performed on a digital signal processor (DSP) board with AD and DA conversion interfaces inst alled in a personal computer (PC). Simulational results indicate the hig hly improved overall stability of the multi machine power system after installa ting the ASG.展开更多
This paper presented a novel wide-area nonlinear excitation control strategy for multi-machine power systems.A simple and effective model transformation method was proposed for the system's mathematical model in t...This paper presented a novel wide-area nonlinear excitation control strategy for multi-machine power systems.A simple and effective model transformation method was proposed for the system's mathematical model in the COI(center of inertia)coordinate system.The system was transformed to an uncertain linear one where deviation of generator terminal voltage became one of the new state variables.Then a wide-area nonlinear robust voltage controller was designed utilizing a LMI(linear matrix inequality)based robust control theory.The proposed controller does not rely on any preselected system operating point,adapts to variations of network parameters and system operation conditions,and assures regulation accuracy of generator terminal voltages.Neither rotor angle nor any variable's differentiation needs to be measured for the proposed controller,and only terminal voltages,rotor speeds,active and reactive power outputs of generators are required.In addition,the proposed controller not only takes into account time delays of remote signals,but also eliminates the effect of wide-area information's incompleteness when not all generators are equipped with PMU(phase measurement unit).Detailed tests were conducted by PSCAD/EMTDC for a three-machine and four-machine power systems respectively,and simulation results illustrate high performance of the proposed controller.展开更多
This paper proposes a coordinated switching power system stabilizer(SPSS)to enhance the stability of multimachine power systems.The SPSS switches between a bang-bang power system stabilizer(BPSS)and a conventional pow...This paper proposes a coordinated switching power system stabilizer(SPSS)to enhance the stability of multimachine power systems.The SPSS switches between a bang-bang power system stabilizer(BPSS)and a conventional power system stabilizer(CPSS)based on a state-dependent switching strategy.The BPSS is designed as a bang-bang constant funnel controller(BCFC).It is able to provide fast damping of rotor speed oscillations in a bang-bang manner.The closed-loop stability of the power system controlled by the SPSSs and the CPSSs is analyzed.To verify the control performance of the SPSS,simulation studies are carried out in a 4-generator 11-bus power system and the IEEE 16-generator 68-bus power system.The damping ability of the SPSS is evaluated in aspects of small-signal oscillation damping and transient stability enhancement,respectively.Meanwhile,the coordination between different SPSSs and the coordination between the SPSS and the CPSS are investigated therein.展开更多
This paper proposes a switching structure excitation controller(SSEC)to enhance the transient stability of multimachine power systems.The SSEC switches between a bangbang funnel excitation controller(BFEC)and a conven...This paper proposes a switching structure excitation controller(SSEC)to enhance the transient stability of multimachine power systems.The SSEC switches between a bangbang funnel excitation controller(BFEC)and a conventional excitation controller(CEC),based on an appropriately designed state-dependent switching strategy.Only the tracking error of rotor angle is required to realize the BFEC in a bang-bang manner with two control values.If the feasibility assumptions of the BFEC are satisfied,the tracking error of rotor angle can be regulated within the predefined error funnels.The power system having the SSEC installed can achieve faster convergence performance compared to that having the CEC implemented only.Simulation studies are carried out in the New England 10-generator 39-bus power system.The control performance of the SSEC is evaluated in the cases that three-phase-to-ground fault and transmission line outage occur in the power system,respectively.展开更多
A modified flux-coupling type superconducting fault current limiter(SFCL)is proposed here for suppressing fault currents.The modified SFCL consists of a coupling transformer,an yttrium barium copper oxide(YBCO)pancake...A modified flux-coupling type superconducting fault current limiter(SFCL)is proposed here for suppressing fault currents.The modified SFCL consists of a coupling transformer,an yttrium barium copper oxide(YBCO)pancake coil,and a controlled switch.By flexibly adjusting the controlled switch’s contact states based on the system operational conditions,the coupling transformer’s primary inductance as well as the YBCO coil’s normal-state resistance are incorporated into the main system for current limitation.Because the modified SFCL has the advantages of resistive and inductive SFCLs,it may improve the power system’s transient behavior.Hence,the SFCL’s effect on the transient stability of a multi-machine power system was also theoretically investigated.Further,simulations were conducted for accessing the SFCL’s performance characteristics under different fault conditions.The results show that using the proposed SFCL can effectively restrain the increased fault current and improve the bus voltage sag;meanwhile,the imitated multi-machine system’s power-angle oscillation can be obviously reduced.展开更多
The role of Power System Stabilizer (PSS) in the power system is to provide necessary damping torque to the system in order to suppress the oscillations caused by a variety of disturbances that occur frequently and ma...The role of Power System Stabilizer (PSS) in the power system is to provide necessary damping torque to the system in order to suppress the oscillations caused by a variety of disturbances that occur frequently and maintain the stability of the system. In this paper, a PSS design technique is proposed using Whale Optimization Algorithm (WOA) by considering eigenvalue objective function. Two bench mark multi machine test systems: three- generator nine- bus system, two- area four- generator inter connected system working on various operating conditions are considered as case studies and tested with the proposed technique. Extensive simulation results are obtained and effectiveness of proposed WOA-PSS are compared with well - known PSO and DE based stabilizers under several disturbances.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Space-Based Solar Power(SBSP) presents a promising solution for achieving carbon neutrality and Renewable Electricity 100%(RE100) goals by offering a stable and continuous energy supply. However, its commercialization...Space-Based Solar Power(SBSP) presents a promising solution for achieving carbon neutrality and Renewable Electricity 100%(RE100) goals by offering a stable and continuous energy supply. However, its commercialization faces significant obstacles due to the technical challenges of long-distance microwave Wireless Power Transmission(WPT) from geostationary orbit. Even ground-based kilometer-scale WPT experiments remain difficult because of limited testing infrastructure, high costs, and strict electromagnetic wave regulations. Since the 1975 NASA-Raytheon experiment, which successfully recovered 30 kW of power over 1.55 km, there has been little progress in extending the transmission distance or increasing the retrieved power. This study proposes a cost-effective methodology for conducting long-range WPT experiments in constrained environments by utilizing existing infrastructure. A deep space antenna operating at 2.08 GHz with an output power of 2.3 kW and a gain of 55.3 dBi was used as the transmitter. Two test configurations were implemented: a 1.81 km ground-to-air test using an aerostat to elevate the receiver and a 1.82 km ground-to-ground test using a ladder truck positioned on a plateau. The rectenna consists of a lightweight 3×3 patch antenna array(0.9 m × 0.9 m), accompanied by a steering device and LED indicators to verify power reception. The aerostat-based test achieved a power density of 154.6 mW/m2, which corresponds to approximately 6.2% of the theoretical maximum. The performance gap is primarily attributed to near-field interference, detuning of the patch antenna, rectifier mismatch, and alignment issues. These limitations are expected to be mitigated through improved patch antenna fabrication, a transition from GaN to GaAs rectifiers optimized for lower input power, and the implementation of an automated alignment system. With these enhancements, the recovered power is expected to improve by approximately four to five times. The results demonstrate a practical and scalable framework for long-range WPT experiments under constrained conditions and provide key insights for advancing SBSP technology.展开更多
Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-mach...Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.展开更多
In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along...In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.展开更多
The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbi...The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.展开更多
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
Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency devia...Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.展开更多
Accurate photovoltaic(PV)power generation forecasting is essential for the efficient integration of renewable energy into power grids.However,the nonlinear and non-stationary characteristics of PV power signals,driven...Accurate photovoltaic(PV)power generation forecasting is essential for the efficient integration of renewable energy into power grids.However,the nonlinear and non-stationary characteristics of PV power signals,driven by fluctuating weather conditions,pose significant challenges for reliable prediction.This study proposes a DOEP(Decomposition–Optimization–Error Correction–Prediction)framework,a hybrid forecasting approach that integrates adaptive signal decomposition,machine learning,metaheuristic optimization,and error correction.The PV power signal is first decomposed using CEEMDAN to extract multi-scale temporal features.Subsequently,the hyperparameters and window sizes of the LSSVM are optimized using a Segment-based EBQPSO strategy.The main novelty of the proposed DOEP framework lies in the incorporation of Segment-based EBQPSO as a structured optimization mechanism that balances elite exploitation and population diversity during LSSVM tuning within the CEEMDAN-based forecasting pipeline.This strategy effectively mitigates convergence instability and sensitivity to initialization,which are common limitations in existing hybrid PV forecasting models.Each IMF is then predicted individually and aggregated to generate an initial forecast.In the error-correction stage,the residual error series is modeled using LSTM,and the final prediction is obtained by combining the initial forecast with the predicted error component.The proposed framework is evaluated using two PV power plant datasets with different levels of complexity.The results demonstrate that DOEP consistently outperforms benchmark models across multiple error-based and goodness-of-fit metrics,achieving MSE reductions of approximately 15%–60%on the ResPV-BDG dataset and 37%–92%on the NREL dataset.Analyses of predicted vs.observed values and residual distributions further confirm the superior calibration and robustness of the proposed approach.Although the DOEP framework entails higher computational costs than single model methods,it delivers significantly improved accuracy and stability for PV power forecasting under complex operating conditions.展开更多
Background:Low relative sit-to-stand(STS)power has emerged as a critical predictor of adverse health outcomes,such as frailty and disability,in older adults.However,its impact on falls,fractures,hospitalizations,and a...Background:Low relative sit-to-stand(STS)power has emerged as a critical predictor of adverse health outcomes,such as frailty and disability,in older adults.However,its impact on falls,fractures,hospitalizations,and all-cause mortality remains unclear.Therefore,this longitudinal study aimed to investigate the potential associations between low relative STS power and these adverse health outcomes in older adults.Methods:A total of 1876 older adults(aged≥65 years,56.4%women)were included from the Toledo Study for Healthy Aging.Relative STS power was assessed using the 30-s STS test and the Alcazar equation.Participants were categorized as having low relative STS power based on previously established cut-off points(2.53 W/kg for men and 2.01 W/kg for women).Falls and fractures(hip and all-type)within the previous year were recorded.Hospitalizations and all-cause mortality were obtained during a follow-up of 6.8±3.1 years(mean±SD;median=7.8 years;interquartile range:3.9-10.1 years)and 9.7±3.5 years(median=10.9 years;interquartile range:8.2-12.5 years),respectively.Generalized linear mixed models,binary logistic regression,and proportional hazards regression adjusted for age,educational level,and comorbidities were used.Results:In men,low relative STS power was significantly associated with an increased likelihood of history of falls(odds ratio(OR)=1.73,95%confidence interval(95%CI):1.08-2.75,p=0.022)and all-type fractures(OR=1.86,95%CI:1.21-2.84,p=0.004)in the previous year.In women,low relative STS power was associated with a higher probability of hip fractures within the previous year(OR=3.25,95%CI:1.07-9.86,p=0.038).Low relative STS power predicted hospitalizations in women(hazard ratio(HR)=1.29,95%CI:1.06-1.58,p=0.012)and longer hospital stays in both men(p=0.020)and women(p=0.033).Low relative STS power significantly increased all-cause mortality in both men(HR=1.57,95%CI:1.26-1.97,p<0.001)and women(HR=2.04,95%CI:1.51-2.74,p<0.001).Conclusion:Low relative STS power was associated with history of hip fractures in women,whereas in men it was associated with history of falls and all-type fractures.Low relative STS power predicted hospitalizations in women but not in men.In both men and women,low relative STS power was associated with longer hospital stays and increased risk of all-cause mortality.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
文摘为了演示和验证稳定器设计的就地相位补偿法在多机电力系统中的应用,介绍在多机电力系统中,就地补偿设计稳定器的2个应用实例。第1个实例是在多机电力系统中就地补偿设计电力系统稳定器（power system stabilizer,PSS）,阻尼电力系统局部模振荡。第2个实例是就地补偿设计附加在静态同步补偿器（static synchronous compensator,STATCOM）上的稳定器,抑制多机电力系统中的区域模振荡,并给出在一个16机电力系统中的应用计算和仿真结果。
文摘The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).
基金Sponsored by the Natural Science Foundation of Hebei Province,China(Grant No.F2016203006)
文摘The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.
文摘This paper describes a stabilization effect after installating an adjustable speed generator (ASG) in a multi machine power system. A personal computer based ASG module has been de veloped for the simulations in parallel with the analog power system simulator i n the Research Laboratory of the Kyushu Electric Power Co. The three phase ins t antaneous value based ASG model has been developed in the Matlab/Simulink envir onment for its detailed and real time simulations, which have been performed on a digital signal processor (DSP) board with AD and DA conversion interfaces inst alled in a personal computer (PC). Simulational results indicate the hig hly improved overall stability of the multi machine power system after installa ting the ASG.
文摘This paper presented a novel wide-area nonlinear excitation control strategy for multi-machine power systems.A simple and effective model transformation method was proposed for the system's mathematical model in the COI(center of inertia)coordinate system.The system was transformed to an uncertain linear one where deviation of generator terminal voltage became one of the new state variables.Then a wide-area nonlinear robust voltage controller was designed utilizing a LMI(linear matrix inequality)based robust control theory.The proposed controller does not rely on any preselected system operating point,adapts to variations of network parameters and system operation conditions,and assures regulation accuracy of generator terminal voltages.Neither rotor angle nor any variable's differentiation needs to be measured for the proposed controller,and only terminal voltages,rotor speeds,active and reactive power outputs of generators are required.In addition,the proposed controller not only takes into account time delays of remote signals,but also eliminates the effect of wide-area information's incompleteness when not all generators are equipped with PMU(phase measurement unit).Detailed tests were conducted by PSCAD/EMTDC for a three-machine and four-machine power systems respectively,and simulation results illustrate high performance of the proposed controller.
基金funded by State Key Program of National Natural Science of China(No.51437006)Guangdong Innovative Research Team Program(No.201001N0104744201),China.
文摘This paper proposes a coordinated switching power system stabilizer(SPSS)to enhance the stability of multimachine power systems.The SPSS switches between a bang-bang power system stabilizer(BPSS)and a conventional power system stabilizer(CPSS)based on a state-dependent switching strategy.The BPSS is designed as a bang-bang constant funnel controller(BCFC).It is able to provide fast damping of rotor speed oscillations in a bang-bang manner.The closed-loop stability of the power system controlled by the SPSSs and the CPSSs is analyzed.To verify the control performance of the SPSS,simulation studies are carried out in a 4-generator 11-bus power system and the IEEE 16-generator 68-bus power system.The damping ability of the SPSS is evaluated in aspects of small-signal oscillation damping and transient stability enhancement,respectively.Meanwhile,the coordination between different SPSSs and the coordination between the SPSS and the CPSS are investigated therein.
基金funded by State Key Program of National Natural Science of China(NO.51437006)Guangdong Innovative Research Team Program(NO.201001N0104744201),China。
文摘This paper proposes a switching structure excitation controller(SSEC)to enhance the transient stability of multimachine power systems.The SSEC switches between a bangbang funnel excitation controller(BFEC)and a conventional excitation controller(CEC),based on an appropriately designed state-dependent switching strategy.Only the tracking error of rotor angle is required to realize the BFEC in a bang-bang manner with two control values.If the feasibility assumptions of the BFEC are satisfied,the tracking error of rotor angle can be regulated within the predefined error funnels.The power system having the SSEC installed can achieve faster convergence performance compared to that having the CEC implemented only.Simulation studies are carried out in the New England 10-generator 39-bus power system.The control performance of the SSEC is evaluated in the cases that three-phase-to-ground fault and transmission line outage occur in the power system,respectively.
基金Supported by the Fujian Young and Middle-Aged Teachers’Science and Technology Research Project(JAT201101).
文摘A modified flux-coupling type superconducting fault current limiter(SFCL)is proposed here for suppressing fault currents.The modified SFCL consists of a coupling transformer,an yttrium barium copper oxide(YBCO)pancake coil,and a controlled switch.By flexibly adjusting the controlled switch’s contact states based on the system operational conditions,the coupling transformer’s primary inductance as well as the YBCO coil’s normal-state resistance are incorporated into the main system for current limitation.Because the modified SFCL has the advantages of resistive and inductive SFCLs,it may improve the power system’s transient behavior.Hence,the SFCL’s effect on the transient stability of a multi-machine power system was also theoretically investigated.Further,simulations were conducted for accessing the SFCL’s performance characteristics under different fault conditions.The results show that using the proposed SFCL can effectively restrain the increased fault current and improve the bus voltage sag;meanwhile,the imitated multi-machine system’s power-angle oscillation can be obviously reduced.
文摘The role of Power System Stabilizer (PSS) in the power system is to provide necessary damping torque to the system in order to suppress the oscillations caused by a variety of disturbances that occur frequently and maintain the stability of the system. In this paper, a PSS design technique is proposed using Whale Optimization Algorithm (WOA) by considering eigenvalue objective function. Two bench mark multi machine test systems: three- generator nine- bus system, two- area four- generator inter connected system working on various operating conditions are considered as case studies and tested with the proposed technique. Extensive simulation results are obtained and effectiveness of proposed WOA-PSS are compared with well - known PSO and DE based stabilizers under several disturbances.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
文摘Space-Based Solar Power(SBSP) presents a promising solution for achieving carbon neutrality and Renewable Electricity 100%(RE100) goals by offering a stable and continuous energy supply. However, its commercialization faces significant obstacles due to the technical challenges of long-distance microwave Wireless Power Transmission(WPT) from geostationary orbit. Even ground-based kilometer-scale WPT experiments remain difficult because of limited testing infrastructure, high costs, and strict electromagnetic wave regulations. Since the 1975 NASA-Raytheon experiment, which successfully recovered 30 kW of power over 1.55 km, there has been little progress in extending the transmission distance or increasing the retrieved power. This study proposes a cost-effective methodology for conducting long-range WPT experiments in constrained environments by utilizing existing infrastructure. A deep space antenna operating at 2.08 GHz with an output power of 2.3 kW and a gain of 55.3 dBi was used as the transmitter. Two test configurations were implemented: a 1.81 km ground-to-air test using an aerostat to elevate the receiver and a 1.82 km ground-to-ground test using a ladder truck positioned on a plateau. The rectenna consists of a lightweight 3×3 patch antenna array(0.9 m × 0.9 m), accompanied by a steering device and LED indicators to verify power reception. The aerostat-based test achieved a power density of 154.6 mW/m2, which corresponds to approximately 6.2% of the theoretical maximum. The performance gap is primarily attributed to near-field interference, detuning of the patch antenna, rectifier mismatch, and alignment issues. These limitations are expected to be mitigated through improved patch antenna fabrication, a transition from GaN to GaAs rectifiers optimized for lower input power, and the implementation of an automated alignment system. With these enhancements, the recovered power is expected to improve by approximately four to five times. The results demonstrate a practical and scalable framework for long-range WPT experiments under constrained conditions and provide key insights for advancing SBSP technology.
基金Supported by the National Natural Science Foundation of China (Nos. 59837270 and 50377018) and the National Key Basic Re-search Special Fund of China (No. G1998020309)
文摘Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.
文摘In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.
文摘The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.
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the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,for funding this research work through the project number“NBU-FFR-2025-3623-11”.
文摘Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.
基金support from the Ministry of Science and Technology of Taiwan(Contract Nos.113-2221-E-011-130-MY2 and 113-2218-E-011-002)the support from Intelligent Manufactur-ing Innovation Center(IMIC),National Taiwan University of Science and Technology(NTUST),Taipei,Taiwan.
文摘Accurate photovoltaic(PV)power generation forecasting is essential for the efficient integration of renewable energy into power grids.However,the nonlinear and non-stationary characteristics of PV power signals,driven by fluctuating weather conditions,pose significant challenges for reliable prediction.This study proposes a DOEP(Decomposition–Optimization–Error Correction–Prediction)framework,a hybrid forecasting approach that integrates adaptive signal decomposition,machine learning,metaheuristic optimization,and error correction.The PV power signal is first decomposed using CEEMDAN to extract multi-scale temporal features.Subsequently,the hyperparameters and window sizes of the LSSVM are optimized using a Segment-based EBQPSO strategy.The main novelty of the proposed DOEP framework lies in the incorporation of Segment-based EBQPSO as a structured optimization mechanism that balances elite exploitation and population diversity during LSSVM tuning within the CEEMDAN-based forecasting pipeline.This strategy effectively mitigates convergence instability and sensitivity to initialization,which are common limitations in existing hybrid PV forecasting models.Each IMF is then predicted individually and aggregated to generate an initial forecast.In the error-correction stage,the residual error series is modeled using LSTM,and the final prediction is obtained by combining the initial forecast with the predicted error component.The proposed framework is evaluated using two PV power plant datasets with different levels of complexity.The results demonstrate that DOEP consistently outperforms benchmark models across multiple error-based and goodness-of-fit metrics,achieving MSE reductions of approximately 15%–60%on the ResPV-BDG dataset and 37%–92%on the NREL dataset.Analyses of predicted vs.observed values and residual distributions further confirm the superior calibration and robustness of the proposed approach.Although the DOEP framework entails higher computational costs than single model methods,it delivers significantly improved accuracy and stability for PV power forecasting under complex operating conditions.
基金supported by Centro de Investigaci on Biom edica en Red Fragilidad y Envejecimiento Saludable(CIBERFES)(Grant Nos.CB16/10/00477,CB16/10/00456,and CB16/10/00464)Plan Propio de Investigaci on of the University of Castilla-La Mancha,and Fondo Europeo de Desarrollo Regional(FEDER)funds from the European Union(Grant No.2022-GRIN-34296)+3 种基金further funded by grants from the Instituto de Salud Carlos III(Grant Nos.PI031558,PI07/90637,PI07/90306,RD 06/0013,and PI18/00972)the Government of Castilla-La Mancha(Grant Nos.03031 and SBPLY/19/180501/000312)Red EXERNETRED DE EJERCICIO FISICO Y SALUD:RED2022-134800T from the Spanish Ministry of Innovation and Sciencesupported by a research grant from the University of Castilla-La Mancha(Programa Investigo,Grant No.2024INVGO-12359)。
文摘Background:Low relative sit-to-stand(STS)power has emerged as a critical predictor of adverse health outcomes,such as frailty and disability,in older adults.However,its impact on falls,fractures,hospitalizations,and all-cause mortality remains unclear.Therefore,this longitudinal study aimed to investigate the potential associations between low relative STS power and these adverse health outcomes in older adults.Methods:A total of 1876 older adults(aged≥65 years,56.4%women)were included from the Toledo Study for Healthy Aging.Relative STS power was assessed using the 30-s STS test and the Alcazar equation.Participants were categorized as having low relative STS power based on previously established cut-off points(2.53 W/kg for men and 2.01 W/kg for women).Falls and fractures(hip and all-type)within the previous year were recorded.Hospitalizations and all-cause mortality were obtained during a follow-up of 6.8±3.1 years(mean±SD;median=7.8 years;interquartile range:3.9-10.1 years)and 9.7±3.5 years(median=10.9 years;interquartile range:8.2-12.5 years),respectively.Generalized linear mixed models,binary logistic regression,and proportional hazards regression adjusted for age,educational level,and comorbidities were used.Results:In men,low relative STS power was significantly associated with an increased likelihood of history of falls(odds ratio(OR)=1.73,95%confidence interval(95%CI):1.08-2.75,p=0.022)and all-type fractures(OR=1.86,95%CI:1.21-2.84,p=0.004)in the previous year.In women,low relative STS power was associated with a higher probability of hip fractures within the previous year(OR=3.25,95%CI:1.07-9.86,p=0.038).Low relative STS power predicted hospitalizations in women(hazard ratio(HR)=1.29,95%CI:1.06-1.58,p=0.012)and longer hospital stays in both men(p=0.020)and women(p=0.033).Low relative STS power significantly increased all-cause mortality in both men(HR=1.57,95%CI:1.26-1.97,p<0.001)and women(HR=2.04,95%CI:1.51-2.74,p<0.001).Conclusion:Low relative STS power was associated with history of hip fractures in women,whereas in men it was associated with history of falls and all-type fractures.Low relative STS power predicted hospitalizations in women but not in men.In both men and women,low relative STS power was associated with longer hospital stays and increased risk of all-cause mortality.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
