The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide ele...The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.展开更多
The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading ...The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource a...The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource allocation model to determine the type,number and location of flexible resources to increase the values of resilience,carbon reduction and renewable energy consumption.To evaluate the values of resilience,a restoration model for transmission systems is established that considers the coordination of fossil-fuel generators,energy storage systems(ESSs)and renewable energy generators in building restoration paths.The collaborative power-carbon-tradable green certificate(TGC)market model is then applied to evaluate the resource values in terms of carbon reduction and renewable energy consumption.Finally,the model is formulated as a mixed-integer linear programming(MILP)with a nonconvex feasible domain,and the normalized normal constraint(NNC)method is applied to obtain approximate Pareto frontiers for decision makers.Case studies validate the effectiveness of the proposed model in improving multi-factor values and analyze the impact of resource regulation capacity on values of restoration and carbon reduction.展开更多
Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hyb...To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.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 background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy sy...In the background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems(IES)is becoming increasingly obvious.In this case,to promote the low-carbon operation of IES and renewable energy consumption,and to improve the IES anti-interference ability,this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power(CSP)station.Firstly,CSP station,gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES,and combined with CCS-P2G coupling model,the IES low-carbon economic dispatch model is established.Secondly,the stepped carbon trading mechanism is applied,and the sensitivity analysis of IES carbon trading is carried out.Finally,an IES optimal scheduling strategy based on fuzzy opportunity constraints and an IES risk assessment strategy based on CVaR theory are established.The simulation shows that the gas-hydrogen doping model proposed in this paper reduces the operating cost and carbon emission of IES by 1.32%and 7.17%,and improves the carbon benefit by 5.73%;variable hydrogen doping ratio model reduces the operating cost and carbon emission of IES by 3.75%and 1.70%,respectively;CSP stations reduce 19.64%and 38.52%of the operating costs of IES and 1.03%and 1.80%of the carbon emissions of IES respectively compared to equal-capacity photovoltaic and wind turbines;the baseline price of carbon trading of IES and its rate of change jointly affect the carbon emissions of IES;evaluating the anti-interference capability of IES through trapezoidal fuzzy number and weighting coefficients,enabling IES to guarantee operation at the lowest cost.展开更多
Herein,we report a simple self-charging hybrid power system(SCHPS)based on binder-free zinc copper selenide nanostructures(ZnCuSe_(2) NSs)deposited carbon fabric(CF)(i.e.,ZnCuSe_(2)/CF),which is used as an active mate...Herein,we report a simple self-charging hybrid power system(SCHPS)based on binder-free zinc copper selenide nanostructures(ZnCuSe_(2) NSs)deposited carbon fabric(CF)(i.e.,ZnCuSe_(2)/CF),which is used as an active material in the fabrication of supercapacitor(SC)and triboelectric nanogenerator(TENG).At first,a binder-free ZnCuSe_(2)/CF was synthesized via a simple and facial hydrothermal synthesis approach,and the electrochemical properties of the obtained ZnCuSe_(2)/CF were evaluated by fabricating a symmetric quasi-solid-state SC(SQSSC).The ZCS-2(Zn:Cu ratio of 2:1)material deposited CF-based SQSSC exhibited good electrochemical properties,and the obtained maximum energy and power densities were 7.5 Wh kg^(-1)and 683.3 W kg^(-1),respectively with 97.6%capacitance retention after 30,000 cycles.Furthermore,the ZnCuSe_(2)/CF was coated with silicone rubber elastomer using a doctor blade technique,which is used as a negative triboelectric material in the fabrication of the multiple TENG(M-TENG).The fabricated M-TENG exhibited excellent electrical output performance,and the robustness and mechanical stability of the device were studied systematically.The practicality and applicability of the proposed M-TENG and SQSSC were systematically investigated by powering various low-power portable electronic components.Finally,the SQSSC was combined with the M-TENG to construct a SCHPS.The fabricated SCHPS provides a feasible solution for sustainable power supply,and it shows great potential in self-powered portable electronic device applications.展开更多
To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational par...To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational parameters of key equipment in real-time.The collected data is uploaded to the monitoring center,allowing operation and maintenance personnel to access equipment information promptly.Data analysis is used to provide fault warning and diagnosis for critical equipment.The system employs the Pure Pursuit algorithm,which effectively avoids obstacles and ensures path continuity and stability.Simulation results show that the Pure Pursuit algorithm significantly improves the navigation accuracy and task efficiency of the inspection robot,ensuring the reliability of thermal power plant inspections.展开更多
In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind,...In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.展开更多
To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy...To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.展开更多
The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the r...The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the railway power supply system.To address these challenges,this paper proposes a novel harmonic resonance prevention measure for RPC-network-train interaction system.Firstly,a harmonic model,a parallel resonance impedance model,a series resonance admittance model,and a control stability model are each established for the RPC-network-train interaction system.Secondly,a comprehensive resonance impact factor(CRIF)is proposed to efficiently and accurately identify the key components affecting resonance,and to provide the selection results of optimization parameters for resonance prevention.Next,the initially selected parameters are constrained by the requirements of ripple current,reactive power and stability.Subsequently,the impedance parameters(control parameters and filter parameters)of the RPC are optimized with the objective of reshaping the parallel resonance impedance and series resonance admittance of the RPC-network-train interaction system,ensuring the output current har-monics of RPC meet standards to achieve resonance prevention,while ensuring the stable operation of the RPC.Finally,the proposed resonance prevention measure is verified under both light load and heavy load conditions using a simulation platform and a hardware-in-the-loop experimental platform.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
The rapid growth in the proportion of renewable-energy gener-ation,such as wind and solar power,has significantly heightened the power system’s dependence on climate.Global climate change will profoundly impact vario...The rapid growth in the proportion of renewable-energy gener-ation,such as wind and solar power,has significantly heightened the power system’s dependence on climate.Global climate change will profoundly impact various aspects of the system,including renewable-energy resource potential,power-system planning and operation,and electricity markets.The Intergovernmental Panel on Climate Change(IPCC)has pointed out that as climate change accelerates,extreme weather events will continue to become more frequent and severe.展开更多
Grid-forming(GFM)control is a key technology for ensuring the safe and stable operation of renewable power systems dominated by converter-interfaced generation(CIG),including wind power,photovoltaic,and battery energy...Grid-forming(GFM)control is a key technology for ensuring the safe and stable operation of renewable power systems dominated by converter-interfaced generation(CIG),including wind power,photovoltaic,and battery energy storage.In this paper,we challenge the traditional approach of emulating a synchronous generator by proposing a frequency-fixed GFM control strategy.The CIG endeavors to regulate itself as a constant voltage source without control dynamics due to its capability limitation,denoted as the frequency-fixed zone.With the proposed strategy,the system frequency is almost always fixed at its rated value,achieving system active power balance independent of frequency,and intentional power flow adjustments are implemented through direct phase angle control.This approach significantly reduces the frequency dynamics and safety issues associated with frequency variations.Furthermore,synchronization dynamics are significantly diminished,and synchronization stability is enhanced.The proposed strategy has the potential to realize a renewable power system with a fixed frequency and robust stability.展开更多
New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed s...New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed switching of power converters.To address this situation,this paper offers an in-depth review of HF interference problems and challenges originating from power electronic devices.First,the root cause of HF electromagnetic interference,i.e.,the resonant response of the parasitic parameters of the system to high-speed switching transients,is analyzed,and various scenarios of HF interference in power systems are highlighted.Next,the types of HF interference are summarized,with a focus on common-mode interference in grounding systems.This paper thoroughly reviews and compares various suppression methods for conducted HF interference.Finally,the challenges involved and suggestions for addressing emerging HF interference problems from the perspective of both power electronics equipment and power systems are discussed.This review aims to offer a structured understanding of HF interference problems and their suppression techniques for researchers and practitioners.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
基金supported by the Science and Technology Project of China Southern Power Grid Co.,Ltd.(ZBKTM20232244)the Project of National Natural of Science Foundation of China(52477103).
文摘The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.
文摘The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
基金supported by the Science and Technology Project of the State Grid Corporation of China“Research on Comprehensive Value Evaluation Method of Flexible Adjusting Resources under Carbon-electricity-certificate Market Coupling Environment”(No.5108-202455038A-1-1-ZN).
文摘The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource allocation model to determine the type,number and location of flexible resources to increase the values of resilience,carbon reduction and renewable energy consumption.To evaluate the values of resilience,a restoration model for transmission systems is established that considers the coordination of fossil-fuel generators,energy storage systems(ESSs)and renewable energy generators in building restoration paths.The collaborative power-carbon-tradable green certificate(TGC)market model is then applied to evaluate the resource values in terms of carbon reduction and renewable energy consumption.Finally,the model is formulated as a mixed-integer linear programming(MILP)with a nonconvex feasible domain,and the normalized normal constraint(NNC)method is applied to obtain approximate Pareto frontiers for decision makers.Case studies validate the effectiveness of the proposed model in improving multi-factor values and analyze the impact of resource regulation capacity on values of restoration and carbon reduction.
文摘Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
基金supported by Science and Technology Project of the headquarters of the State Grid Corporation of China(No.5500-202324492A-3-2-ZN).
文摘To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.
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.
基金State Grid Gansu Electric Power Company Science and Technology Program(Grant No.W24FZ2730008)National Natural Science Foundation of China(Grant No.51767017).
文摘In the background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems(IES)is becoming increasingly obvious.In this case,to promote the low-carbon operation of IES and renewable energy consumption,and to improve the IES anti-interference ability,this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power(CSP)station.Firstly,CSP station,gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES,and combined with CCS-P2G coupling model,the IES low-carbon economic dispatch model is established.Secondly,the stepped carbon trading mechanism is applied,and the sensitivity analysis of IES carbon trading is carried out.Finally,an IES optimal scheduling strategy based on fuzzy opportunity constraints and an IES risk assessment strategy based on CVaR theory are established.The simulation shows that the gas-hydrogen doping model proposed in this paper reduces the operating cost and carbon emission of IES by 1.32%and 7.17%,and improves the carbon benefit by 5.73%;variable hydrogen doping ratio model reduces the operating cost and carbon emission of IES by 3.75%and 1.70%,respectively;CSP stations reduce 19.64%and 38.52%of the operating costs of IES and 1.03%and 1.80%of the carbon emissions of IES respectively compared to equal-capacity photovoltaic and wind turbines;the baseline price of carbon trading of IES and its rate of change jointly affect the carbon emissions of IES;evaluating the anti-interference capability of IES through trapezoidal fuzzy number and weighting coefficients,enabling IES to guarantee operation at the lowest cost.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIP)(No.2018R1A6A1A03025708)partly supported by the GRRC program of Gyeonggi province(GRRCKyungHee2023-B03).
文摘Herein,we report a simple self-charging hybrid power system(SCHPS)based on binder-free zinc copper selenide nanostructures(ZnCuSe_(2) NSs)deposited carbon fabric(CF)(i.e.,ZnCuSe_(2)/CF),which is used as an active material in the fabrication of supercapacitor(SC)and triboelectric nanogenerator(TENG).At first,a binder-free ZnCuSe_(2)/CF was synthesized via a simple and facial hydrothermal synthesis approach,and the electrochemical properties of the obtained ZnCuSe_(2)/CF were evaluated by fabricating a symmetric quasi-solid-state SC(SQSSC).The ZCS-2(Zn:Cu ratio of 2:1)material deposited CF-based SQSSC exhibited good electrochemical properties,and the obtained maximum energy and power densities were 7.5 Wh kg^(-1)and 683.3 W kg^(-1),respectively with 97.6%capacitance retention after 30,000 cycles.Furthermore,the ZnCuSe_(2)/CF was coated with silicone rubber elastomer using a doctor blade technique,which is used as a negative triboelectric material in the fabrication of the multiple TENG(M-TENG).The fabricated M-TENG exhibited excellent electrical output performance,and the robustness and mechanical stability of the device were studied systematically.The practicality and applicability of the proposed M-TENG and SQSSC were systematically investigated by powering various low-power portable electronic components.Finally,the SQSSC was combined with the M-TENG to construct a SCHPS.The fabricated SCHPS provides a feasible solution for sustainable power supply,and it shows great potential in self-powered portable electronic device applications.
文摘To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational parameters of key equipment in real-time.The collected data is uploaded to the monitoring center,allowing operation and maintenance personnel to access equipment information promptly.Data analysis is used to provide fault warning and diagnosis for critical equipment.The system employs the Pure Pursuit algorithm,which effectively avoids obstacles and ensures path continuity and stability.Simulation results show that the Pure Pursuit algorithm significantly improves the navigation accuracy and task efficiency of the inspection robot,ensuring the reliability of thermal power plant inspections.
基金supported by The National Key Research and Development Program of China(Grant No.2023YFB2604600).
文摘In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.
基金Supported by State Grid Zhejiang Electric Power Co.,Ltd.Science and Technology Project Funding(No.B311DS230005).
文摘To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.
基金supported in part by the National Natural Science Foundation of China under Grant No.52277126.
文摘The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the railway power supply system.To address these challenges,this paper proposes a novel harmonic resonance prevention measure for RPC-network-train interaction system.Firstly,a harmonic model,a parallel resonance impedance model,a series resonance admittance model,and a control stability model are each established for the RPC-network-train interaction system.Secondly,a comprehensive resonance impact factor(CRIF)is proposed to efficiently and accurately identify the key components affecting resonance,and to provide the selection results of optimization parameters for resonance prevention.Next,the initially selected parameters are constrained by the requirements of ripple current,reactive power and stability.Subsequently,the impedance parameters(control parameters and filter parameters)of the RPC are optimized with the objective of reshaping the parallel resonance impedance and series resonance admittance of the RPC-network-train interaction system,ensuring the output current har-monics of RPC meet standards to achieve resonance prevention,while ensuring the stable operation of the RPC.Finally,the proposed resonance prevention measure is verified under both light load and heavy load conditions using a simulation platform and a hardware-in-the-loop experimental platform.
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The rapid growth in the proportion of renewable-energy gener-ation,such as wind and solar power,has significantly heightened the power system’s dependence on climate.Global climate change will profoundly impact various aspects of the system,including renewable-energy resource potential,power-system planning and operation,and electricity markets.The Intergovernmental Panel on Climate Change(IPCC)has pointed out that as climate change accelerates,extreme weather events will continue to become more frequent and severe.
基金supported by the National Key Research&Development Program of China under Grant 2024YFB2408900.
文摘Grid-forming(GFM)control is a key technology for ensuring the safe and stable operation of renewable power systems dominated by converter-interfaced generation(CIG),including wind power,photovoltaic,and battery energy storage.In this paper,we challenge the traditional approach of emulating a synchronous generator by proposing a frequency-fixed GFM control strategy.The CIG endeavors to regulate itself as a constant voltage source without control dynamics due to its capability limitation,denoted as the frequency-fixed zone.With the proposed strategy,the system frequency is almost always fixed at its rated value,achieving system active power balance independent of frequency,and intentional power flow adjustments are implemented through direct phase angle control.This approach significantly reduces the frequency dynamics and safety issues associated with frequency variations.Furthermore,synchronization dynamics are significantly diminished,and synchronization stability is enhanced.The proposed strategy has the potential to realize a renewable power system with a fixed frequency and robust stability.
基金supported by the science and technology project of State Grid Shanghai Municipal Electric Power Company(No.52094023003L).
文摘New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed switching of power converters.To address this situation,this paper offers an in-depth review of HF interference problems and challenges originating from power electronic devices.First,the root cause of HF electromagnetic interference,i.e.,the resonant response of the parasitic parameters of the system to high-speed switching transients,is analyzed,and various scenarios of HF interference in power systems are highlighted.Next,the types of HF interference are summarized,with a focus on common-mode interference in grounding systems.This paper thoroughly reviews and compares various suppression methods for conducted HF interference.Finally,the challenges involved and suggestions for addressing emerging HF interference problems from the perspective of both power electronics equipment and power systems are discussed.This review aims to offer a structured understanding of HF interference problems and their suppression techniques for researchers and practitioners.
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.
