The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys th...The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys the research experiments and development efforts related to space solar power stations and microwave wireless power transmission technologies worldwide.The objective is to assess the progress and current state of this technological foundation,determine the necessary focus for developing high-power microwave wireless power transmission technology,and provide clarity on the direction of future technology development in these areas.Finally,a distributed space solar power station plan that is immediately feasible is proposed.展开更多
The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.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
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL pow...As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.展开更多
Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constr...Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.展开更多
Recently,an article was published on solid effect(SE)dynamic nuclear polarization(DNP)enhancement,where the au-thors reported achieving 1H enhancement factors up to 500 by increasing the microwave power at 9.4 T,marki...Recently,an article was published on solid effect(SE)dynamic nuclear polarization(DNP)enhancement,where the au-thors reported achieving 1H enhancement factors up to 500 by increasing the microwave power at 9.4 T,marking the highest SE enhancement to date[1].展开更多
On 30 September 2024,the UK shuttered its last remaining coal-fired power plant[1].The closure marks a historic milestone,the end of 142 years of coal fueled prosperity.The country opened the world’s first plant to s...On 30 September 2024,the UK shuttered its last remaining coal-fired power plant[1].The closure marks a historic milestone,the end of 142 years of coal fueled prosperity.The country opened the world’s first plant to supply electric streetlamps in 1882,spark-ing a global energy revolution that has led to today’s nearly univer-sally electrified world.展开更多
Ladle furnaces are known for their high power consumption,making research on power-saving process crucial.In response to the defect of thin slag thickness in the industrial production of a 120-t ladle furnace at a ste...Ladle furnaces are known for their high power consumption,making research on power-saving process crucial.In response to the defect of thin slag thickness in the industrial production of a 120-t ladle furnace at a steel plant,with its production of ship plate steel DH36 as the focus,experiments involving adding the foaming agent and shifting power delivery gears were conducted.Based on the principle of measuring alternating current by Rogowski coils,the power consumption during the ladle furnace refining process was calculated theoretically,and the actual industrial power consumption matched with it basically,confirming the accuracy of the theoretical calculations.Additionally,the impacts of argon flow rate,foaming agents,and shifting power delivery gears on power consumption were studied.The results showed that adding 0.59 and 0.50 kg/t foaming agents in two batches improved the refining process of the ladle furnace,allowing for effective submerged-arc operations and saving electric energy of 7.2382 kWh per ton of steel.Similarly,utilizing a power supply mode of 7-step short arc during the refining process significantly enhanced the desulfurization rate of molten steel and saved electric energy of 11.6387 kWh per ton of steel.展开更多
Isolated power converters have emerged as an active research topic in power integrated circuit(IC)design.Reflecting this growing interest,ISSCC 2025 has featured a dedicated session on"Isolated Power and Gate Dri...Isolated power converters have emerged as an active research topic in power integrated circuit(IC)design.Reflecting this growing interest,ISSCC 2025 has featured a dedicated session on"Isolated Power and Gate Drivers".These converters enable safe and reliable power delivery across voltage domains and are widely used in renewable energy,electric vehicles,and telecommunications.Galvanic isolation prevents surge currents and ground loop issues in harsh high-voltage environments.As demand grows for compact,efficient,and high–power-density solutions,fully integrated architectures featuring on-chip transformers are increasingly favored over traditional module-based designs,offering>5 kV isolation with a smaller footprint and lower system cost[1].展开更多
This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.Ho...China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.However,because of the randomness and volatility of wind and photovoltaic power,the large-scale development of renewable energy faces challenges with accommodation and transmission.At present,the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China.Nonetheless,solving the problems of high carbon dioxide emission,carbon dioxide capture,and the utilization of thermal power is still necessary.Based on power-to-hydrogen,powerto-methanol,and oxygen-enriched combustion power generation technologies,this article proposes a power-to-hydrogen-andmethanol model based on the collaborative optimization of energy flow and material flow,which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power.Models with different ways of linking power to hydrogen and methanol are established,and an 8760-hour-time-series operation simulation is incorporated into the planning model.A case study is then conducted on renewable energy bases in the deserts of western and northern China.The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage,reduce the cost of carbon capture,make full use of by-product oxygen and captured carbon dioxide,and produce high-value chemical raw materials,thus exhibiting significant economic advantages.展开更多
Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodolo...Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodologies often need to adequately handle these fluctuations from solar radiation and ambient temperature variations.We introduce the Memory-Enhanced Autoencoder with Adversarial Training(MemAAE)model to overcome these limitations,designed explicitly for robust anomaly detection in VPP environments.The MemAAE model integrates three principal components:an LSTM-based autoencoder that effectively captures temporal dynamics to distinguish between normal and anomalous behaviors,an adversarial training module that enhances system resilience across diverse operational scenarios,and a prediction module that aids the autoencoder during the reconstruction process,thereby facilitating precise anomaly identification.Furthermore,MemAAE features a memory mechanism that stores critical pattern information,mitigating overfitting,alongside a dynamic threshold adjustment mechanism that adapts detection thresholds in response to evolving operational conditions.Our empirical evaluation of the MemAAE model using real-world solar power data shows that the model outperforms other comparative models on both datasets.On the Sopan-Finder dataset,MemAAE has an accuracy of 99.17%and an F1-score of 95.79%,while on the Sunalab Faro PV 2017 dataset,it has an accuracy of 97.67%and an F1-score of 93.27%.Significant performance advantages have been achieved on both datasets.These results show that MemAAE model is an effective method for real-time anomaly detection in virtual power plants(VPPs),which can enhance robustness and adaptability to inherent variables in solar power generation.展开更多
We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scen...We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scenario,in which the lifetime associated with a particular risk is not observable;rather,we observe only the maximum lifetime value among all risks.The distribution exhibits decreasing,increasing,unimodal and bathtub shaped hazard rate functions,depending on its parameters.Several properties of the EPLPS distribution are investigated.Moreover,we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix.Finally,applications to three real data sets show the flexibility and potentiality of the EPLPS distribution.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1...Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1].Thus,highdensity multiphase DC−DC converters are pivotal for implementing vertical power delivery(VPD)architectures in XPU platforms.Strategically positioning these converters beneath processors and maximizing spatial utilization enables core rail currents exceeding 2 kA while significantly reducing the power distribution network(PDN)losses compared to conventional solutions.The VPD configuration elevates system-level energy efficiency with>100 W power saving per processor,yielding megawatt-scale savings in a datacenter that uses~100000 processors.The synergy of 48 V power conversion architectures and advanced packaging techniques enables the industry’s commitment to balancing computational demands with CO_(2)emission reduction and environmental sustainability.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.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
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
基金Entrusted Fund of National Institute of Information and Communications Technology(NICT),Japan(JPJ012368C02401)。
文摘The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys the research experiments and development efforts related to space solar power stations and microwave wireless power transmission technologies worldwide.The objective is to assess the progress and current state of this technological foundation,determine the necessary focus for developing high-power microwave wireless power transmission technology,and provide clarity on the direction of future technology development in these areas.Finally,a distributed space solar power station plan that is immediately feasible is proposed.
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
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In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
文摘As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.
文摘Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.
文摘Recently,an article was published on solid effect(SE)dynamic nuclear polarization(DNP)enhancement,where the au-thors reported achieving 1H enhancement factors up to 500 by increasing the microwave power at 9.4 T,marking the highest SE enhancement to date[1].
文摘On 30 September 2024,the UK shuttered its last remaining coal-fired power plant[1].The closure marks a historic milestone,the end of 142 years of coal fueled prosperity.The country opened the world’s first plant to supply electric streetlamps in 1882,spark-ing a global energy revolution that has led to today’s nearly univer-sally electrified world.
基金The authors gratefully express their appreciation to the National Natural Science Foundation of China(51834002)for sponsoring this work.
文摘Ladle furnaces are known for their high power consumption,making research on power-saving process crucial.In response to the defect of thin slag thickness in the industrial production of a 120-t ladle furnace at a steel plant,with its production of ship plate steel DH36 as the focus,experiments involving adding the foaming agent and shifting power delivery gears were conducted.Based on the principle of measuring alternating current by Rogowski coils,the power consumption during the ladle furnace refining process was calculated theoretically,and the actual industrial power consumption matched with it basically,confirming the accuracy of the theoretical calculations.Additionally,the impacts of argon flow rate,foaming agents,and shifting power delivery gears on power consumption were studied.The results showed that adding 0.59 and 0.50 kg/t foaming agents in two batches improved the refining process of the ladle furnace,allowing for effective submerged-arc operations and saving electric energy of 7.2382 kWh per ton of steel.Similarly,utilizing a power supply mode of 7-step short arc during the refining process significantly enhanced the desulfurization rate of molten steel and saved electric energy of 11.6387 kWh per ton of steel.
基金supported in part by the National Natural Science Foundation of China under Grant U23A20353.
文摘Isolated power converters have emerged as an active research topic in power integrated circuit(IC)design.Reflecting this growing interest,ISSCC 2025 has featured a dedicated session on"Isolated Power and Gate Drivers".These converters enable safe and reliable power delivery across voltage domains and are widely used in renewable energy,electric vehicles,and telecommunications.Galvanic isolation prevents surge currents and ground loop issues in harsh high-voltage environments.As demand grows for compact,efficient,and high–power-density solutions,fully integrated architectures featuring on-chip transformers are increasingly favored over traditional module-based designs,offering>5 kV isolation with a smaller footprint and lower system cost[1].
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
基金the financial support provided by the Major Program of Xiangjiang Laboratory(No.23XJ01006).
文摘China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.However,because of the randomness and volatility of wind and photovoltaic power,the large-scale development of renewable energy faces challenges with accommodation and transmission.At present,the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China.Nonetheless,solving the problems of high carbon dioxide emission,carbon dioxide capture,and the utilization of thermal power is still necessary.Based on power-to-hydrogen,powerto-methanol,and oxygen-enriched combustion power generation technologies,this article proposes a power-to-hydrogen-andmethanol model based on the collaborative optimization of energy flow and material flow,which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power.Models with different ways of linking power to hydrogen and methanol are established,and an 8760-hour-time-series operation simulation is incorporated into the planning model.A case study is then conducted on renewable energy bases in the deserts of western and northern China.The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage,reduce the cost of carbon capture,make full use of by-product oxygen and captured carbon dioxide,and produce high-value chemical raw materials,thus exhibiting significant economic advantages.
基金supported by“Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2021RIS-002)the Technology Development Program(RS-2023-00266141)funded by the Ministry of SMEs and Startups(MSS,Republic of Korea).
文摘Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodologies often need to adequately handle these fluctuations from solar radiation and ambient temperature variations.We introduce the Memory-Enhanced Autoencoder with Adversarial Training(MemAAE)model to overcome these limitations,designed explicitly for robust anomaly detection in VPP environments.The MemAAE model integrates three principal components:an LSTM-based autoencoder that effectively captures temporal dynamics to distinguish between normal and anomalous behaviors,an adversarial training module that enhances system resilience across diverse operational scenarios,and a prediction module that aids the autoencoder during the reconstruction process,thereby facilitating precise anomaly identification.Furthermore,MemAAE features a memory mechanism that stores critical pattern information,mitigating overfitting,alongside a dynamic threshold adjustment mechanism that adapts detection thresholds in response to evolving operational conditions.Our empirical evaluation of the MemAAE model using real-world solar power data shows that the model outperforms other comparative models on both datasets.On the Sopan-Finder dataset,MemAAE has an accuracy of 99.17%and an F1-score of 95.79%,while on the Sunalab Faro PV 2017 dataset,it has an accuracy of 97.67%and an F1-score of 93.27%.Significant performance advantages have been achieved on both datasets.These results show that MemAAE model is an effective method for real-time anomaly detection in virtual power plants(VPPs),which can enhance robustness and adaptability to inherent variables in solar power generation.
文摘We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scenario,in which the lifetime associated with a particular risk is not observable;rather,we observe only the maximum lifetime value among all risks.The distribution exhibits decreasing,increasing,unimodal and bathtub shaped hazard rate functions,depending on its parameters.Several properties of the EPLPS distribution are investigated.Moreover,we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix.Finally,applications to three real data sets show the flexibility and potentiality of the EPLPS distribution.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
文摘Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1].Thus,highdensity multiphase DC−DC converters are pivotal for implementing vertical power delivery(VPD)architectures in XPU platforms.Strategically positioning these converters beneath processors and maximizing spatial utilization enables core rail currents exceeding 2 kA while significantly reducing the power distribution network(PDN)losses compared to conventional solutions.The VPD configuration elevates system-level energy efficiency with>100 W power saving per processor,yielding megawatt-scale savings in a datacenter that uses~100000 processors.The synergy of 48 V power conversion architectures and advanced packaging techniques enables the industry’s commitment to balancing computational demands with CO_(2)emission reduction and environmental sustainability.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
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.
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.
