Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decisi...Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decision making is adopted to ascertain the action sequence of reactive power compensation devices. First, a set of evaluation indexes including control sensitivity, regulation margin, response time, response level and cost is set up, and fuzziness of the proposed qualitative indexes is introduced to make them comparable to the proposed quantitative indexes. Then a method to calculate fuzzy weight of each index is put forward for evaluating relative importance of the proposed indexes. Finally, the action sequence of reactive power compensation devices is determined through the theory of fuzzy compromise decision making. The case study shows that the proposed method is effective to obtain the action sequence of reactive power compensation device which correspond to experience.展开更多
Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is ...Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature.Whenever there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy systems.In this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power systems.Frequency control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning models.The performance analysis of the proposed method is done with different machine learning based approaches.The forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting accuracy.Simulation results show that the Mean Absolute Percentage Error(MAPE),Root Mean Square Error(RMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.展开更多
This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and ...This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and a solar field in order to optimize the production of all the technologies. The results obtained made it possible to evaluate the operating performance of the installation and to show the complementarity between the two energy sources with regard to temporary and seasonal variations in resources. During nighttime periods or periods of low sunlight, the wind turbine is a good alternative to energy storage by batteries, the output of the wind turbine can be up to 853.76 W. It was also a question of proposing solutions for optimizing the hybrid system through the automation of the hybrid charge regulator. A minimum height of 30 m above the ground has been chosen as the optimum height for the wind turbine.展开更多
This paper presents a frequency support strategy for the diode rectifier unit(DRU)-high-voltage direct current(HVDC)-based offshore wind power integration system,which coordinates multiple power sources without commun...This paper presents a frequency support strategy for the diode rectifier unit(DRU)-high-voltage direct current(HVDC)-based offshore wind power integration system,which coordinates multiple power sources without communication to reduce receiving grid frequency fluctuations.First,based on the deduced DRU's frequency transfer characteristic,a fine-designed ripple carrying frequency information is superimposed on the HVDC link,transferring the onshore frequency to offshore wind turbines(WTs)via the DC ripple and coupled AC harmonic without communication.Second,multiple power sources are utilized for frequency support,including HVDC capacitance and grid-forming WTs combined with energy storage systems,and appropriate sources are activated in the order specified by the designed thresholds.Finally,the effectiveness of the proposed frequency support strategy is verified by simulations in PSCAD/EMTDC.展开更多
The wide-area damping controllers(WADCs),which are essential for mitigating regional low-frequency oscillations,face cyber-physical security threats due to the vulnerability of wide-area measurement system to cyber at...The wide-area damping controllers(WADCs),which are essential for mitigating regional low-frequency oscillations,face cyber-physical security threats due to the vulnerability of wide-area measurement system to cyber attacks and wind power uncertainties.This paper introduces reachability analysis method to quantify the impact of varying-amplitude attacks and uncertain wind fluctuations on the performance of WADC.Firstly,considering wind farm integration and attack injection,a nonlinear power system model with multiple buses is constructed based on Kron reduction method to improve computational efficiency and mitigate the constraints imposed by algebraic constraints.Then,a zonotope-based polytope construction method is employed to effectively model the range of attack amplitudes and wind uncertainties.By conducting reachability analysis,the reachable set preserving the nonlinear characteristics of studied system is computed,which enables the quantification of the maximum fluctuation range of regional oscillations under the dual disturbances.Case studies are undertaken on two multi-machine power systems with wind farm integration.The obtained results emphasize the efficacy of designed method,providing valuable insights into the magnitude of the impact that attacks exert on the operational characteristics of power system under various uncertain factors.展开更多
This paper proposes an enhanced grid-forming(GFM)control scheme for modular multilevel converter-based high-voltage direct current(MMC-HVDC)systems interfacing offshore wind farms.The proposed strategy adopts an impro...This paper proposes an enhanced grid-forming(GFM)control scheme for modular multilevel converter-based high-voltage direct current(MMC-HVDC)systems interfacing offshore wind farms.The proposed strategy adopts an improved DC voltage synchronization approach,which not only provides instantaneous active and reactive power support,but also achieves enhanced DC-link voltage regulation.To validate its control performance,PSCAD/EMTDC simulations are conducted using the actual parameters of the Borwin6 MMC-HVDC project.Simulation results demonstrate the scheme’s effectiveness in delivering instantaneous grid support and maintaining system stability under various challenging conditions,including phase angle jumps,frequency variations,voltage dips,short-circuit ratio(SCR)changes and AC grid faults.展开更多
Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and h...Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and high upkeep costs.Therefore,the development of a specialized front-end filter tailored for direct current water-cooled system is importance.This involves the integration of dimensionally stable anode(DSA)and nickel alloy cathode,valued for their corrosion resistance in seawater,into a novel front-end filter system for Water-cooled applications.This system has the dual capability of generating hydrogen and chlorine for self-cleaning purposes.Implementing a flushing pulse electrolysis mode,it effectively mitigates electrode failure induced by cathodic calcium and magnesium deposition,thereby significantly prolonging electrode lifespan.Laboratory tests comprising system assembly and performance evaluations were conducted,with the system programmed to operate for 5 minutes every 24 hours under continuous flushing by natural seawater to simulate real-world conditions.After more than 11 months of continuous flushing,observations reveal that the DSA mesh and nickel alloy mesh maintain intact structural integrity and normal functioning.Subsequent 1꞉1 physical prototype Sea trial further validated the soundness of the system design and electrolytic control parameters.展开更多
The rapid development of wind energy in the power sectors raises the question about the reliability of wind turbines for power system planning and operation.The electrical subsystem of wind turbines(ESWT),which is one...The rapid development of wind energy in the power sectors raises the question about the reliability of wind turbines for power system planning and operation.The electrical subsystem of wind turbines(ESWT),which is one of the most vulnerable parts of the wind turbine,is investigated in this paper.The hygrothermal aging of power electronic devices(PEDs)is modeled for the first time in the comprehensive reliability evaluation of ESWT,by using a novel stationary“circuit-like”approach.First,the failure mechanism of the hygrothermal aging,which includes the solder layer fatigue damage and packaging material performance degradation,is explained.Then,a moisture diffusion resistance concept and a hygrothermal equivalent circuit are proposed to quantitate the hygrothermal aging behavior.A conditional probability function is developed to calculate the time-varying failure rate of PEDs.At last,the stochastic renewal process is simulated to evaluate the reliability for ESWT through the sequential Monte Carlo simulation,in which failure,repair,and replacement states of devices are all included.The effectiveness of our proposed reliability evaluation method is verified on an ESWT in a 2 MW wind turbine use time series data collected from a wind farm in China.展开更多
In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)d...In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)during disturbances.Moreover,due to the frequency decoupling between the two ends of the MMCHVDC,the sending-end wind farm(SEWF)cannot obtain the frequency variation information of the REG to provide inertia response.Therefore,this paper proposes a novel coordinated source-network-storage inertia control strategy based on wind power transmission via MMC-HVDC system.First,the grid-side MMC station(GS-MMC)maps the frequency variations of the REG to direct current(DC)voltage variations through the frequency mapping control,and uses submodule capacitor energy to provide inertial power.Then,the wind farm-side MMC station(WF-MMC)restores the DC voltage variations to frequency variations through the frequency restoration control and power loss compensation,providing real-time frequency information for the wind farm.Finally,based on real-time frequency information,thewind farmutilizes the rotor kinetic energy and energy storage to provide fast and lasting power support through the wind-storage coordinated inertia control strategy.Meanwhile,when the wind turbines withdraw from the inertia response phase,the energy storage can increase the power output to compensate for the power deficit,preventing secondary frequency drops.Furthermore,this paper uses small-signal analysis to determine the appropriate values for the key parameters of the proposed control strategy.A simulation model of the wind power transmission via MMCHVDC system is built in MATLAB/Simulink environment to validate and evaluate the proposed method.The results show that the proposed coordinated control strategy can effectively improve the system inertia level and avoid the secondary frequency drop under the load sudden increase condition.展开更多
A wind-turbine power system is often challenged by voltage instability,reactive power imbalance,and limited fault ride-through capability under grid disturbances.Doubly Fed Induction Generator based wind farms,owing t...A wind-turbine power system is often challenged by voltage instability,reactive power imbalance,and limited fault ride-through capability under grid disturbances.Doubly Fed Induction Generator based wind farms,owing to their partial coupling with the grid,are particularly vulnerable to voltage dips and excessive reactive power absorption during fault events.This study proposes an adaptive control strategy based on Model Reference Adaptive Control integrated with stator flux-oriented vector control to regulate active and reactive power of a DFIG-based wind farm connected to a standard IEEE 9-bus power system under fault conditions.The proposed control scheme is developed and validated using detailed MATLAB/Simulink modeling under normal operation,symmetrical three-phase fault conditions,and post-fault recovery scenarios.A three-phase-to-ground fault is applied at the wind farm interconnection bus for a duration of 150 ms to evaluate transient performance.Simulation results demonstrate that the adaptive controller ensures fast power tracking,effective reactive power support,and enhanced voltage recovery compared to a conventional proportional–integral controller.Quantitatively,the proposed method improves voltage recovery time by approximately 45%,reduces active power overshoot by 38%,and lowers total harmonic distortion by 52% following fault clearance.Furthermore,the adaptive controller maintains stable operation under variations in wind speed and machine parameters without requiring retuning,highlighting its robustness against system uncertainties.The results confirm that the proposed control strategy significantly enhances fault ride-through capability,power quality,and dynamic stability of grid-interfaced wind farms.These findings demonstrate the practical applicability of adaptive control techniques for improving the reliability and resilience of modern power systems with high wind energy penetration.展开更多
Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that devi...Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)syste...This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.展开更多
Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptio...Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.展开更多
New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates beca...New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates because of harsh weather,significantly affecting the maintenance procedures and reliability.Different types of failure rates of the wind turbine(WT)and wave energy converter(WEC),e.g.,the degradation and failure rates during regular wind speed fluctuation,the degradation and failure rates during intense wind speed fluctuation are considered.By incorporating both WT and WEC,the HWWPG system is designed to enhance the overall amount of electrical energy produced by the system over a given period under varying weather conditions.The universal generating function technique is used to calculate the HWWPG system dependability measures in a structured and efficient manner.This research highlights that intense weather conditions increase the failure rates of both WT and WEC,resulting in higher maintenance costs and more frequent downtimes,thus impacting the HWWPG system’s reliability.Although the HWWPG system can meet the energy demands in the presence of high failure rates,the reliance of the hybrid system on both WT and WEC helps maintain a relatively stable demand satisfaction during periods of high energy demand despite adverse weather conditions.To confirm the added value and applicability of the developed model,a case study of an offshore hybrid platform is conducted.The findings underscore the system’s robustness in maintaining energy production under varied weather conditions,though higher failure rates and maintenance costs arise in intense scenarios.展开更多
Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid syste...Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid systems are mostly based on single-column platforms such as spars(single coaxial-cylinder hybrid system'hereafter).Systems based on multiple-column platforms such as semi-submersible platforms('multiple coaxial-cylinder hybrid systems'hereafter)are rarely seen or studied,despite their superiority in wave-power absorption due to the use of multiple WECs as well as in dynamic stability.This paper proposes a novel WindFloat-annular-WEC hybrid system,based on our study investigating its dynamic and power features,and optimizing the geometry and power take-off of the WECs.Our results show that the dynamic and power features of a multiple coaxial-cylinder hybrid system are different from those of a single coaxial-cylinder hybrid system,so the same optimization parameters cannot be directly applied.Flatter annular WECs absorb slightly more power in a wider wave-period range,but their geometry is confined by limitations in installation and structural strength.The overall effect of an oblique incident wave is greater intensity in the motions of the hybrid system in yaw and the direction perpendicular to propagation,although the difference is small and maybe negligible.展开更多
As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowc...As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.展开更多
This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mod...This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.展开更多
The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACT...The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.展开更多
【Purposes】The new energy generation represented by wind power is the most realistic strategic choice to achieve the goals of carbon peaking and carbon neutrality. To absorb renewable energy electricity in power grid...【Purposes】The new energy generation represented by wind power is the most realistic strategic choice to achieve the goals of carbon peaking and carbon neutrality. To absorb renewable energy electricity in power grids, a new probabilistic evaluation method for available transmission capacity in transmission systems is proposed based on joint cumulants, and a decision model for risk available transmission capacity based on expected quantiles is proposed accordingly. As a vital component of available transmission capacity(ATC) calculation, the transmission reliability margin(TRM), as a reserved transmission capacity, reflects the impact of uncertainty factors on transmission capacity. However, in traditional calculation methods, TRM is determined through deterministic or probabilistic methods, which is difficult to reflect the risks brought by large-scale wind power consumption to ATC and cannot meet the requirements for transmission capacity risk management. 【Methods】Firstly, to address the issue that the cumulative method requires variables to be independent of each other and cannot consider the correlation of wind power output, a joint cumulative method combined with FGM Copula function is proposed to characterize the correlation of wind power output;Secondly, for the probabilistic assessment of available transmission capacity, a probabilistic assessment model for available transmission capacity is established by combining the partition integration method and the Comish Fisher expansion;Finally, in response to the problem that decision methods based on value at risk only consider the probability achieved at the tail of the probability distribution and cannot describe the risks generated throughout the distribution, a risk available transmission capacity index based on expected quantiles is proposed, and its evaluation process is proposed. 【Results】Verify the feasibility and practicality of the proposed indicators and models through case analysis.展开更多
文摘Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decision making is adopted to ascertain the action sequence of reactive power compensation devices. First, a set of evaluation indexes including control sensitivity, regulation margin, response time, response level and cost is set up, and fuzziness of the proposed qualitative indexes is introduced to make them comparable to the proposed quantitative indexes. Then a method to calculate fuzzy weight of each index is put forward for evaluating relative importance of the proposed indexes. Finally, the action sequence of reactive power compensation devices is determined through the theory of fuzzy compromise decision making. The case study shows that the proposed method is effective to obtain the action sequence of reactive power compensation device which correspond to experience.
文摘Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature.Whenever there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy systems.In this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power systems.Frequency control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning models.The performance analysis of the proposed method is done with different machine learning based approaches.The forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting accuracy.Simulation results show that the Mean Absolute Percentage Error(MAPE),Root Mean Square Error(RMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.
文摘This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and a solar field in order to optimize the production of all the technologies. The results obtained made it possible to evaluate the operating performance of the installation and to show the complementarity between the two energy sources with regard to temporary and seasonal variations in resources. During nighttime periods or periods of low sunlight, the wind turbine is a good alternative to energy storage by batteries, the output of the wind turbine can be up to 853.76 W. It was also a question of proposing solutions for optimizing the hybrid system through the automation of the hybrid charge regulator. A minimum height of 30 m above the ground has been chosen as the optimum height for the wind turbine.
基金supported by the State Grid Corporation of China Science and Technology Project(No.5500-202319103A-1-1-ZN).
文摘This paper presents a frequency support strategy for the diode rectifier unit(DRU)-high-voltage direct current(HVDC)-based offshore wind power integration system,which coordinates multiple power sources without communication to reduce receiving grid frequency fluctuations.First,based on the deduced DRU's frequency transfer characteristic,a fine-designed ripple carrying frequency information is superimposed on the HVDC link,transferring the onshore frequency to offshore wind turbines(WTs)via the DC ripple and coupled AC harmonic without communication.Second,multiple power sources are utilized for frequency support,including HVDC capacitance and grid-forming WTs combined with energy storage systems,and appropriate sources are activated in the order specified by the designed thresholds.Finally,the effectiveness of the proposed frequency support strategy is verified by simulations in PSCAD/EMTDC.
基金supported in part by the Young Elite Scientists Sponsorship Program by the Chinese Society for Electrical Engineering under Grant CSEE-YESS-2022019in part by the Guangzhou Basic and Applied Basic Research Foundation under Grand 2024A04J3672in part by the National Natural Science Foundation of China under Grant 52207106.
文摘The wide-area damping controllers(WADCs),which are essential for mitigating regional low-frequency oscillations,face cyber-physical security threats due to the vulnerability of wide-area measurement system to cyber attacks and wind power uncertainties.This paper introduces reachability analysis method to quantify the impact of varying-amplitude attacks and uncertain wind fluctuations on the performance of WADC.Firstly,considering wind farm integration and attack injection,a nonlinear power system model with multiple buses is constructed based on Kron reduction method to improve computational efficiency and mitigate the constraints imposed by algebraic constraints.Then,a zonotope-based polytope construction method is employed to effectively model the range of attack amplitudes and wind uncertainties.By conducting reachability analysis,the reachable set preserving the nonlinear characteristics of studied system is computed,which enables the quantification of the maximum fluctuation range of regional oscillations under the dual disturbances.Case studies are undertaken on two multi-machine power systems with wind farm integration.The obtained results emphasize the efficacy of designed method,providing valuable insights into the magnitude of the impact that attacks exert on the operational characteristics of power system under various uncertain factors.
文摘This paper proposes an enhanced grid-forming(GFM)control scheme for modular multilevel converter-based high-voltage direct current(MMC-HVDC)systems interfacing offshore wind farms.The proposed strategy adopts an improved DC voltage synchronization approach,which not only provides instantaneous active and reactive power support,but also achieves enhanced DC-link voltage regulation.To validate its control performance,PSCAD/EMTDC simulations are conducted using the actual parameters of the Borwin6 MMC-HVDC project.Simulation results demonstrate the scheme’s effectiveness in delivering instantaneous grid support and maintaining system stability under various challenging conditions,including phase angle jumps,frequency variations,voltage dips,short-circuit ratio(SCR)changes and AC grid faults.
基金Supported by the Project of Design of Anti-corrosion and Anti-fouling Solutions for Offshore Wind Power Water-Cooled Systems(No.E428161)the National Natural Science Foundation of China(No.42176047)。
文摘Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and high upkeep costs.Therefore,the development of a specialized front-end filter tailored for direct current water-cooled system is importance.This involves the integration of dimensionally stable anode(DSA)and nickel alloy cathode,valued for their corrosion resistance in seawater,into a novel front-end filter system for Water-cooled applications.This system has the dual capability of generating hydrogen and chlorine for self-cleaning purposes.Implementing a flushing pulse electrolysis mode,it effectively mitigates electrode failure induced by cathodic calcium and magnesium deposition,thereby significantly prolonging electrode lifespan.Laboratory tests comprising system assembly and performance evaluations were conducted,with the system programmed to operate for 5 minutes every 24 hours under continuous flushing by natural seawater to simulate real-world conditions.After more than 11 months of continuous flushing,observations reveal that the DSA mesh and nickel alloy mesh maintain intact structural integrity and normal functioning.Subsequent 1꞉1 physical prototype Sea trial further validated the soundness of the system design and electrolytic control parameters.
基金supported by the National Natural Science Foundation of China under Grant 52022016China Postdoctoral Science Foundation under grant 2021M693711Fundamental Research Funds for the Central Universities under grant 2021CDJQY-037.
文摘The rapid development of wind energy in the power sectors raises the question about the reliability of wind turbines for power system planning and operation.The electrical subsystem of wind turbines(ESWT),which is one of the most vulnerable parts of the wind turbine,is investigated in this paper.The hygrothermal aging of power electronic devices(PEDs)is modeled for the first time in the comprehensive reliability evaluation of ESWT,by using a novel stationary“circuit-like”approach.First,the failure mechanism of the hygrothermal aging,which includes the solder layer fatigue damage and packaging material performance degradation,is explained.Then,a moisture diffusion resistance concept and a hygrothermal equivalent circuit are proposed to quantitate the hygrothermal aging behavior.A conditional probability function is developed to calculate the time-varying failure rate of PEDs.At last,the stochastic renewal process is simulated to evaluate the reliability for ESWT through the sequential Monte Carlo simulation,in which failure,repair,and replacement states of devices are all included.The effectiveness of our proposed reliability evaluation method is verified on an ESWT in a 2 MW wind turbine use time series data collected from a wind farm in China.
基金funded by State Grid Corporation of China Central Branch Technology Project(52140024000C).
文摘In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)during disturbances.Moreover,due to the frequency decoupling between the two ends of the MMCHVDC,the sending-end wind farm(SEWF)cannot obtain the frequency variation information of the REG to provide inertia response.Therefore,this paper proposes a novel coordinated source-network-storage inertia control strategy based on wind power transmission via MMC-HVDC system.First,the grid-side MMC station(GS-MMC)maps the frequency variations of the REG to direct current(DC)voltage variations through the frequency mapping control,and uses submodule capacitor energy to provide inertial power.Then,the wind farm-side MMC station(WF-MMC)restores the DC voltage variations to frequency variations through the frequency restoration control and power loss compensation,providing real-time frequency information for the wind farm.Finally,based on real-time frequency information,thewind farmutilizes the rotor kinetic energy and energy storage to provide fast and lasting power support through the wind-storage coordinated inertia control strategy.Meanwhile,when the wind turbines withdraw from the inertia response phase,the energy storage can increase the power output to compensate for the power deficit,preventing secondary frequency drops.Furthermore,this paper uses small-signal analysis to determine the appropriate values for the key parameters of the proposed control strategy.A simulation model of the wind power transmission via MMCHVDC system is built in MATLAB/Simulink environment to validate and evaluate the proposed method.The results show that the proposed coordinated control strategy can effectively improve the system inertia level and avoid the secondary frequency drop under the load sudden increase condition.
文摘A wind-turbine power system is often challenged by voltage instability,reactive power imbalance,and limited fault ride-through capability under grid disturbances.Doubly Fed Induction Generator based wind farms,owing to their partial coupling with the grid,are particularly vulnerable to voltage dips and excessive reactive power absorption during fault events.This study proposes an adaptive control strategy based on Model Reference Adaptive Control integrated with stator flux-oriented vector control to regulate active and reactive power of a DFIG-based wind farm connected to a standard IEEE 9-bus power system under fault conditions.The proposed control scheme is developed and validated using detailed MATLAB/Simulink modeling under normal operation,symmetrical three-phase fault conditions,and post-fault recovery scenarios.A three-phase-to-ground fault is applied at the wind farm interconnection bus for a duration of 150 ms to evaluate transient performance.Simulation results demonstrate that the adaptive controller ensures fast power tracking,effective reactive power support,and enhanced voltage recovery compared to a conventional proportional–integral controller.Quantitatively,the proposed method improves voltage recovery time by approximately 45%,reduces active power overshoot by 38%,and lowers total harmonic distortion by 52% following fault clearance.Furthermore,the adaptive controller maintains stable operation under variations in wind speed and machine parameters without requiring retuning,highlighting its robustness against system uncertainties.The results confirm that the proposed control strategy significantly enhances fault ride-through capability,power quality,and dynamic stability of grid-interfaced wind farms.These findings demonstrate the practical applicability of adaptive control techniques for improving the reliability and resilience of modern power systems with high wind energy penetration.
基金supported in part by the National Natural Science Foundation of China(No.52467008)Gansu Provincial Depatment of Education Youth Doctoral Suppo Project(2024QB-051).
文摘Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
文摘This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.
基金supported by the National Natural Science Foundation of China(No.U2433214)。
文摘Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.
文摘New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates because of harsh weather,significantly affecting the maintenance procedures and reliability.Different types of failure rates of the wind turbine(WT)and wave energy converter(WEC),e.g.,the degradation and failure rates during regular wind speed fluctuation,the degradation and failure rates during intense wind speed fluctuation are considered.By incorporating both WT and WEC,the HWWPG system is designed to enhance the overall amount of electrical energy produced by the system over a given period under varying weather conditions.The universal generating function technique is used to calculate the HWWPG system dependability measures in a structured and efficient manner.This research highlights that intense weather conditions increase the failure rates of both WT and WEC,resulting in higher maintenance costs and more frequent downtimes,thus impacting the HWWPG system’s reliability.Although the HWWPG system can meet the energy demands in the presence of high failure rates,the reliance of the hybrid system on both WT and WEC helps maintain a relatively stable demand satisfaction during periods of high energy demand despite adverse weather conditions.To confirm the added value and applicability of the developed model,a case study of an offshore hybrid platform is conducted.The findings underscore the system’s robustness in maintaining energy production under varied weather conditions,though higher failure rates and maintenance costs arise in intense scenarios.
基金supported by the National Natural Science Foundation of China(Nos.52201322,52222109,and 52071096)the Guangdong Basic and Applied Basic Research Foundation(Nos.2022B1515020036 and 2023A1515012144)the Natural Science Foundation of Guangzhou City(No.202201010055),China.
文摘Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid systems are mostly based on single-column platforms such as spars(single coaxial-cylinder hybrid system'hereafter).Systems based on multiple-column platforms such as semi-submersible platforms('multiple coaxial-cylinder hybrid systems'hereafter)are rarely seen or studied,despite their superiority in wave-power absorption due to the use of multiple WECs as well as in dynamic stability.This paper proposes a novel WindFloat-annular-WEC hybrid system,based on our study investigating its dynamic and power features,and optimizing the geometry and power take-off of the WECs.Our results show that the dynamic and power features of a multiple coaxial-cylinder hybrid system are different from those of a single coaxial-cylinder hybrid system,so the same optimization parameters cannot be directly applied.Flatter annular WECs absorb slightly more power in a wider wave-period range,but their geometry is confined by limitations in installation and structural strength.The overall effect of an oblique incident wave is greater intensity in the motions of the hybrid system in yaw and the direction perpendicular to propagation,although the difference is small and maybe negligible.
基金supported by the Science and Technology Project of China Huaneng Group Co.,Ltd.Research on Key Technologies for Monitoring and Protection of Offshore Wind Power Underwater Equipment(HNKJ21-H40).
文摘As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.
基金supported by the 2022 Sanya Science and Technology Innovation Project,China(No.2022KJCX03)the Sanya Science and Education Innovation Park,Wuhan University of Technology,China(Grant No.2022KF0028)the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.2021JJLH0036).
文摘This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.
文摘The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.
文摘【Purposes】The new energy generation represented by wind power is the most realistic strategic choice to achieve the goals of carbon peaking and carbon neutrality. To absorb renewable energy electricity in power grids, a new probabilistic evaluation method for available transmission capacity in transmission systems is proposed based on joint cumulants, and a decision model for risk available transmission capacity based on expected quantiles is proposed accordingly. As a vital component of available transmission capacity(ATC) calculation, the transmission reliability margin(TRM), as a reserved transmission capacity, reflects the impact of uncertainty factors on transmission capacity. However, in traditional calculation methods, TRM is determined through deterministic or probabilistic methods, which is difficult to reflect the risks brought by large-scale wind power consumption to ATC and cannot meet the requirements for transmission capacity risk management. 【Methods】Firstly, to address the issue that the cumulative method requires variables to be independent of each other and cannot consider the correlation of wind power output, a joint cumulative method combined with FGM Copula function is proposed to characterize the correlation of wind power output;Secondly, for the probabilistic assessment of available transmission capacity, a probabilistic assessment model for available transmission capacity is established by combining the partition integration method and the Comish Fisher expansion;Finally, in response to the problem that decision methods based on value at risk only consider the probability achieved at the tail of the probability distribution and cannot describe the risks generated throughout the distribution, a risk available transmission capacity index based on expected quantiles is proposed, and its evaluation process is proposed. 【Results】Verify the feasibility and practicality of the proposed indicators and models through case analysis.
