Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become...Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.展开更多
Distributed energy systems(DES),as an integrated energy system with coupled distributed energy resources,have great potential in reducing carbon dioxide emissions and improving energy efficiencies.Considering the back...Distributed energy systems(DES),as an integrated energy system with coupled distributed energy resources,have great potential in reducing carbon dioxide emissions and improving energy efficiencies.Considering the background of urbanization and the energy revolution in China,the study investigates the renewable-based DESs supply modes and their application in China.A new method is proposed to classify DESs supply modes into three categories considering the renewable resource in domination,and their application domains are discussed.A comprehensive model is given for economic and environmental evaluation.Typical case studies show that the renewable-based DES systems can supply the energy in a cost-effective and environment-friendly way.Among them,the biomass waste dominated supply mode can not only achieve"zero"carbon emissions but also"zero"energy consumption,even though not yet economically attractive under the present policy and market conditions.Thus,recommendations are given to promote the further deployment of renewable-based DESs,regarding their supply modes,policy requirements,and issues to be addressed.展开更多
On June 2,2023,the China Electric Power Planning&Engineering Institute hosted the launch of the“New Power System Development Blue Book”(hereinafter referred to as the“Blue Book”)in Beijing sponsored by the Nat...On June 2,2023,the China Electric Power Planning&Engineering Institute hosted the launch of the“New Power System Development Blue Book”(hereinafter referred to as the“Blue Book”)in Beijing sponsored by the National Energy Administration.The“Blue Book”comprehen-sively expounds the development concept and connotative char-acteristics of the new power system,formulates a“three-step”development path,and proposes the overall structure and key tasks of building a new power system.Yu Bing,a member of a group and deputy director of the National Energy Administration,delivered a speech at the meet.In addition,Huang Xuenong,the supervisory director of the National Energy Administration,released the“Blue Book.”展开更多
Numerous countries worldwide have committed to the decarbonization of their economies.These countries include both developed nations such as the United States,United Kingdom,and European Union member states,as well as...Numerous countries worldwide have committed to the decarbonization of their economies.These countries include both developed nations such as the United States,United Kingdom,and European Union member states,as well as recently developed nations like China.A commonly adopted strategy among these countries involves initiating the decar-bonization process within the power sector.This adoption is pri-marily motivated by two factors:first,the existence of well-estab-lished low-carbon power supply technologies,such as wind and solar PV second,the potential for extensive electrification of fossil fuel energy demand through rapidly advancing technologies,such as electric vehicles and heat pumps.Thus,decarbonizing the power sector represents the most logical starting point in the jour-ney toward a low-carbon future.展开更多
With the increasing emphasis on sustainable energy and the advancements in modern agriculture,flexible agricultural power loads present challenges to the reliable operation of the agricultural energy internet.However,...With the increasing emphasis on sustainable energy and the advancements in modern agriculture,flexible agricultural power loads present challenges to the reliable operation of the agricultural energy internet.However,research on the coupling of energy system security with agricultural security is insufficient and fails to consider the impacts of meteorological elements on agricultural power loads.To address these gaps,this paper establishes load models for irrigation and light supplementation based on the actual cultivation demands of winter dragon fruit in Guangxi province.A static security index system is developed to analyze the security,considering the unique features of agricultural power demands.The condition of the distribution network is assessed by comparing the indexes with predefined limits,using a China 41-bus distribution network.Finally,the optimal scheme for nocturnal supplemental lighting treatment and irrigation is determined based on the method for maintaining secure operation of the distribution network.This study serves as a guide for simulating current farming power loads and demonstrates how security analysis of the agricultural energy internet contributes to the large-scale and sophisticated development of modern agriculture.展开更多
Introducing methane at the anode side of a solid oxide electrolysis cell(SOEC)has been proven to effectively suppress the oxygen evolution reaction(OER),thereby enabling hydrogen production at significantly lower volt...Introducing methane at the anode side of a solid oxide electrolysis cell(SOEC)has been proven to effectively suppress the oxygen evolution reaction(OER),thereby enabling hydrogen production at significantly lower voltages.In this work,a double perovskite oxide,Sr_(2)Fe_(1.4)Pt_(0.1)Mo_(0.5)O_(6-δ)(abbreviated as Pt-SFM),was successfully synthesized by a liquid-phase method and employed as both an electronic conductor and a catalyst for methane oxidation at the SOEC anode.Following high-temperature treatment under a reducing atmosphere,platinum(Pt)nanoparticles were exsolved from the perovskite lattice and uniformly dispersed on the oxide surface.These exsolved Pt nanoparticles act as highly active sites for methane adsorption and oxidation.Electrochemical performance tests were conducted at 1123.15 K,and the results demonstrated that the Pt-SFM cell treated for 20 h(Pt-SFM 20 h)achieved a current density of 0.85 A·cm^(-2)at an applied voltage of 1.40 V.This performance corresponds to a 102.4%enhancement compared to the undoped SFM 20 h cell.The superior performance is attributed to the presence of exsolved Pt,which significantly improves the catalyst's ability to adsorb and dissociate methane molecules.Electrochemical impedance spectroscopy(EIS)analysis under open-circuit conditions revealed that the polarization impedance of the Pt-SFM 20 h cell was 1.25Ω·cm^(2),which is 49.2%lower than that of the SFM 20 h cell.Furthermore,a 45-h long-term stability test showed that the Pt-SFM 20 h cell maintained a stable performance,with a low voltage degradation rate of only 0.67 mV·h^(-1).展开更多
The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial car...The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial carbon emissions.To mitigate these emissions,future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands.This paper aims to investigate how much carbon emission reduction can be achieved by using a carbonoriented demand response to guide the optimal planning and operation of data centers.A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load.In the planning model,future operation simulations comprehensively coordinate the temporal‒spatial flexibility of computational loads and the quality of service(QoS).An empirical study based on the proposed models is conducted on real-world data from China.The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province,Ningxia Hui Autonomous Region,Sichuan Province,Inner Mongolia Autonomous Region,and Qinghai Province,accounting for 57%of the total national increase in server capacity.33%of the computational load from Eastern China should be transferred to the West,which could reduce the overall load carbon emissions by 26%.展开更多
The Arctic and Antarctic regions are sensitive to global climate change.Monitoring climatological and ecological changes in such areas has become urgently necessary to address climate change and ensure sustainable hum...The Arctic and Antarctic regions are sensitive to global climate change.Monitoring climatological and ecological changes in such areas has become urgently necessary to address climate change and ensure sustainable human development.Therefore,it is important to develop automatic monitoring technology for polar regions and to produce air-ice-sea long-period,multiscale,and unmanned monitoring equipment.This paper describes an unmanned ice station observation system,the autonomous observation platform of a polar unmanned aerial vehicle,dual-use ice-sea buoys,temperature chain buoys,and a wind-solar-hydrogen storage clean energy system suitable for use in the extreme polar environment.Additionally,a coupled air-ice-sea autonomous observation station currently under development is also introduced.展开更多
As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inve...As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.展开更多
The realization of high-Q resonances in a silicon metasurface with various broken-symmetry blocks is reported. Theoretical analysis reveals that the sharp resonances in the metasurfaces originate from symmetry-protect...The realization of high-Q resonances in a silicon metasurface with various broken-symmetry blocks is reported. Theoretical analysis reveals that the sharp resonances in the metasurfaces originate from symmetry-protected bound in the continuum(BIC) and the magnetic dipole dominates these peculiar states. A smaller size of the defect in the broken-symmetry block gives rise to the resonance with a larger Q factor. Importantly, this relationship can be tuned by changing the structural parameter, resulting from the modulation of the topological configuration of BICs. Consequently, a Q factor of more than 3,000 can be easily achieved by optimizing dimensions of the nanostructure. At this sharp resonance, the intensity of the third harmonic generation signal in the patterned structure can be 368 times larger than that of the flat silicon film. The proposed strategy and underlying theory can open up new avenues to realize ultrasharp resonances, which may promote the development of the potential meta-devices for nonlinearity, lasing action, and sensing.展开更多
Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power grids.Existing deep-learning-based methods can perform well if there are s...Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power grids.Existing deep-learning-based methods can perform well if there are sufficient training data and enough computational resources.However,there are challenges in building models through centralized shared data due to data privacy concerns and industry competition.Federated learning is a new distributed machine learning approach which enables training models across edge devices while data reside locally.In this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM model.We design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting approach.Thorough evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.展开更多
Power transformer is one of the most crucial devices in power grid.It is significant to determine incipient faults of power transformers fast and accurately.Input features play critical roles in fault diagnosis accura...Power transformer is one of the most crucial devices in power grid.It is significant to determine incipient faults of power transformers fast and accurately.Input features play critical roles in fault diagnosis accuracy.In order to further improve the fault diagnosis performance of power trans-formers,a random forest feature selection method coupled with optimized kernel extreme learning machine is presented in this study.Firstly,the random forest feature selection approach is adopted to rank 42 related input features derived from gas concentration,gas ratio and energy-weighted dissolved gas analysis.Afterwards,a kernel extreme learning machine tuned by the Aquila optimization algorithm is implemented to adjust crucial parameters and select the optimal feature subsets.The diagnosis accuracy is used to assess the fault diagnosis capability of concerned feature subsets.Finally,the optimal feature subsets are applied to establish fault diagnosis model.According to the experimental results based on two public datasets and comparison with 5 conventional approaches,it can be seen that the average accuracy of the pro-posed method is up to 94.5%,which is superior to that of other conventional approaches.Fault diagnosis performances verify that the optimum feature subset obtained by the presented method can dramatically improve power transformers fault diagnosis accuracy.展开更多
A polyethylene oxide （PEO）-coated polyimide （PI） membrane was prepared by electrospinning method followed by a dip-coating and drying process for high-performance lithium-ion batteries （LIB）. 8emicrystal PEO was...A polyethylene oxide （PEO）-coated polyimide （PI） membrane was prepared by electrospinning method followed by a dip-coating and drying process for high-performance lithium-ion batteries （LIB）. 8emicrystal PEO was covered on the surface of the fibers and partially enmeshed in PI matrix, which formed unique porous structures. The pores with an average size of 4.1 μm and a porosity of 90% served as ion transport channels. Compared with the cell with Celgard 2400 membrane, the half-cell using PEO-coated P1 membrane as a separator exhibits excellent electrochemical performance both at room temperature and at low temperature. The electrolyte uptaking rate of PEO-coated PI membrane was 170% and the ionic conductivity was 3.83 × 10^-3 S cm^-1. PEO-coated PI membrane possessed 5.3 V electrochemical window. The electrode-electrolyte interfacial resistance was 62.4 Ω. The capacity retention ratios with PEO- coated PI membrane were 86.4% at 5 C and 73.5% at 10 C at 25 ℃ and 75% at 5 C at 0 ℃. Furthermore, the cell using the separator demonstrates excellent capacity retention over cycling. These advanced characteristics would boost the application of the PEO-coated PI membrane for high-power lithium ion battery.展开更多
To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of re...To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power.By studying the mathematical model of wind power output and calculating surplus wind power,as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank,an innovative capacity optimization allocation model was established.The objective of the model was to achieve the lowest total net present value over the entire life cycle.The model took into account the cost-benefit breakdown of equipment end-of-life cost,replacement cost,residual value gain,wind abandonment penalty,hydrogen transportation,and environmental value.The MATLAB-based platform invoked the CPLEX commercial solver to solve the model.Combined with the analysis of the annual average wind speed data from an offshore wind farm in Guangdong Province,the optimal capacity configuration results and the actual operation of the hydrogen production system were obtained.Under the calculation scenario,this hydrogen production system could consume 3,800 MWh of residual electricity from offshore wind power each year.It could achieve complete consumption of residual electricity from wind power without incurring the penalty cost of wind power.Additionally,it could produce 66,500 kg of green hydrogen from wind power,resulting in hydrogen sales revenue of 3.63 million RMB.It would also reduce pollutant emissions from coal-based hydrogen production by 1.5 tons and realize an environmental value of 4.83 million RMB.The annual net operating income exceeded 6 million RMB and the whole life cycle NPV income exceeded 50 million RMB.These results verified the feasibility and rationality of the established capacity optimization allocation model.The model could help advance power system planning and operation research and assist offshore wind farm operators in improving economic and environmental benefits.展开更多
The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers.These setups present various operational modes:independe...The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers.These setups present various operational modes:independent operation and multi-electrolyzer parallelization,each with distinct advantages and challenges.This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers,establishing a weakly coupled system that combines the advantages of two modes.This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection,while preserving the option for independent operation after decoupling.A specialized thermal exchange model is developed for this topology,according to the dynamics of the lye mixer.The study further details startup procedures and proposes optimized control strategies tailored to this structural design.Waste heat from the caustic fully heats up the multiple electrolyzers connected to the lye mixing system,enabling a rapid hot start to enhance the system’s ability to track renewable energy.A control strategy is established to reduce heat loss and increase startup speed,and the optimal valve openings of the diverter valve and the manifold valve are determined.Simulation results indicate a considerable enhancement in operational efficiency,marked by an 18.28%improvement in startup speed and a 6.11%reduction in startup energy consumption inmulti-electrolyzer cluster systems,particularlywhen the systems are synchronized with photovoltaic energy sources.The findings represent a significant stride toward efficient and sustainable hydrogen production,offering a promising path for large-scale integration of renewable energy.展开更多
Producing renewable e-methanol from e-hydrogen and diverse carbon sources is an essential way for clean methanol preparation.Despite this,the technical and economic feasibility of different e-methanols has yet to be t...Producing renewable e-methanol from e-hydrogen and diverse carbon sources is an essential way for clean methanol preparation.Despite this,the technical and economic feasibility of different e-methanols has yet to be thoroughly compared,leaving the most promising pathway to achieve commercialization yet evident.This paper reports a preliminary analysis of the lifecycle greenhouse gas(GHG)emissions and costs of four renewable e-methanols with different carbon sources:bio-carbon,direct air capture(DAC),fossil fuel carbon capture(FFCC),and fossil.The results indicate that renewable e-methanol costs(4167−10250 CNY/tonne)2−4 times the market rate of grey methanol.However,with the carbon tax and the projected decline in e-H2 costs,blue e-methanol may initially replace diesel in inland navigation,followed by a shift from heavy fuel oil(HFO)to green e-methanol in ocean ship-ping.Furthermore,the e-H2 cost and the availability of green carbon are vital factors affecting cost-effectiveness.A reduction in e-H2 cost from 2.1 CNY/Nm3 to 1.1 CNY/Nm3 resulting from a transition from an annual to a daily scheduling period,could lower e-methanol costs by 1200 to 2100 CNY.This paper also provides an in-depth discussion on the challenges and opportunities associated with the various green carbon sources.展开更多
After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and de...After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.展开更多
In-line inspection is one of the most effective technical measures to ensure the safety of oil and gas pipelines.However,the extensive application of oil and gas pipelines of high-carbon steel,large diameter,high pres...In-line inspection is one of the most effective technical measures to ensure the safety of oil and gas pipelines.However,the extensive application of oil and gas pipelines of high-carbon steel,large diameter,high pressure and high flow rate in recent years brings about new challenges to in-line inspection.In this paper,we investigated the engineering application of new technologies and equipment,including the in-line inspection technology based on electromagnetic detector array,the extremely low frequency transient weak signal detection technology and new in-line inspection equipment.Then,the new technology and equipment of electromagnetic detector array were developed by applying the active emission and receiving of electromagnetic signal to inspect the metallic defects.Finally,noisy signals were inspected on the basis of Duffing chaotic oscillator,and thus the inspection of extremely low frequency signals in the noise was realized.In addition,the new method and equipment of extremely low frequency transient weak signal detection were developed and verified in actual inspection engineering.And the following research results were obtained.First,the in-line inspection technology based on electromagnetic detector array uses the synergetic effect between DC exciting magnetic field and high-frequency exciting magnetic field,so a perturbation response can be realized even by small signal excitation.Second,with the introduction of a novel compressive sampling of acquisition information composition,the speed bottleneck of in-line detector is broken through,and a new world record of the inspection speed of the electromagnetic detector array is set up,i.e.,8 m/s.Third,under the condition of high-speed movement,the received signals of in-line detector are weak and temporary while tracking and positioning outside the pipeline.And by virtue of the extremely low frequency transient weak signal detection method based on chaos,this technical bottleneck is broken through,and the signal-to-noise ratio(SNR)of transient weak signal in the process of real-time inspection is decreased below−10 dB.In conclusion,the superior performance of these new equipment has already been verified in the inspection engineering of in-service oil and gas pipelines.These research results will provide technical and equipment support for the safe operation of domestic main oil and gas pipelines.展开更多
The difficulty in capital recovery for distributed re newable energy operators(DREOs)and the high charging costs at electric vehicle charging stations(EVCSs)have long been sig nificant challenges in power systems.Coll...The difficulty in capital recovery for distributed re newable energy operators(DREOs)and the high charging costs at electric vehicle charging stations(EVCSs)have long been sig nificant challenges in power systems.Collaborative operation of DREOs and EVCSs can effectively address these challenges,yet few studies have approached incentivizing collaboration from the perspective of profit allocation.Therefore,this paper pro poses a fair and efficient profit allocation method.Incorporat ing the Gauss-Legendre quadrature formula into the AumannShapley value(GL-AS)method enables efficient calculation of the profit allocation of cooperative members.However,existing literature only discusses the profit allocation method of conven tional power generation units,limiting its applicability.This pa per addresses the problem of energy storage system(ESS)switching between charging and discharging in any time inter val and the time-varying problem of renewable energy power output,thereby ensuring the efficiency of the solution process.Furthermore,a novel profit allocation adjustment model is pro vided through the adoption of triangular fuzzy comprehensive evaluation(TFCE).Finally,the effectiveness of the proposed profit allocation method is validated through numerical simula tions in various scenarios.展开更多
With the increasing proportion of renewable energy,power system dispatch and electricity market clearing face significant engineering challenges,including growing model complexity,heightened precision requirements for...With the increasing proportion of renewable energy,power system dispatch and electricity market clearing face significant engineering challenges,including growing model complexity,heightened precision requirements for solutions,and constrained computational time.These developments necessitate advancements in extra-high-speed approximate solution methods,techniques for solving strongly coupled problems,and largescale power system optimization techniques.This paper provides a comprehensive review of existing efficient optimization methodologies tailored to power systems with high proportion of renewable energy,analyzing their applicability to emerging challenges while outlining future research directions to address these complex operational problems.展开更多
文摘Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.
基金supported by National Key Research and Development Program of China(No.2016YFB0900100)Sate Grid of China(Research on the development potential evaluation of distributed generation and its management and control and operation optimization technology under scaleup development stage.No.1400-201927279A-0-0-00)
文摘Distributed energy systems(DES),as an integrated energy system with coupled distributed energy resources,have great potential in reducing carbon dioxide emissions and improving energy efficiencies.Considering the background of urbanization and the energy revolution in China,the study investigates the renewable-based DESs supply modes and their application in China.A new method is proposed to classify DESs supply modes into three categories considering the renewable resource in domination,and their application domains are discussed.A comprehensive model is given for economic and environmental evaluation.Typical case studies show that the renewable-based DES systems can supply the energy in a cost-effective and environment-friendly way.Among them,the biomass waste dominated supply mode can not only achieve"zero"carbon emissions but also"zero"energy consumption,even though not yet economically attractive under the present policy and market conditions.Thus,recommendations are given to promote the further deployment of renewable-based DESs,regarding their supply modes,policy requirements,and issues to be addressed.
文摘On June 2,2023,the China Electric Power Planning&Engineering Institute hosted the launch of the“New Power System Development Blue Book”(hereinafter referred to as the“Blue Book”)in Beijing sponsored by the National Energy Administration.The“Blue Book”comprehen-sively expounds the development concept and connotative char-acteristics of the new power system,formulates a“three-step”development path,and proposes the overall structure and key tasks of building a new power system.Yu Bing,a member of a group and deputy director of the National Energy Administration,delivered a speech at the meet.In addition,Huang Xuenong,the supervisory director of the National Energy Administration,released the“Blue Book.”
文摘Numerous countries worldwide have committed to the decarbonization of their economies.These countries include both developed nations such as the United States,United Kingdom,and European Union member states,as well as recently developed nations like China.A commonly adopted strategy among these countries involves initiating the decar-bonization process within the power sector.This adoption is pri-marily motivated by two factors:first,the existence of well-estab-lished low-carbon power supply technologies,such as wind and solar PV second,the potential for extensive electrification of fossil fuel energy demand through rapidly advancing technologies,such as electric vehicles and heat pumps.Thus,decarbonizing the power sector represents the most logical starting point in the jour-ney toward a low-carbon future.
基金supported by Shanxi Energy Internet Research Institute(SXEI2023B003).
文摘With the increasing emphasis on sustainable energy and the advancements in modern agriculture,flexible agricultural power loads present challenges to the reliable operation of the agricultural energy internet.However,research on the coupling of energy system security with agricultural security is insufficient and fails to consider the impacts of meteorological elements on agricultural power loads.To address these gaps,this paper establishes load models for irrigation and light supplementation based on the actual cultivation demands of winter dragon fruit in Guangxi province.A static security index system is developed to analyze the security,considering the unique features of agricultural power demands.The condition of the distribution network is assessed by comparing the indexes with predefined limits,using a China 41-bus distribution network.Finally,the optimal scheme for nocturnal supplemental lighting treatment and irrigation is determined based on the method for maintaining secure operation of the distribution network.This study serves as a guide for simulating current farming power loads and demonstrates how security analysis of the agricultural energy internet contributes to the large-scale and sophisticated development of modern agriculture.
基金supported by the Key Program of National Natural Science Foundation of China(22138008)the financial support provided by the State Key Laboratory of Catalytic Materials and Reaction Engineering(RIPP,SINOPEC)+1 种基金the Program of National Natural Science Foundation of China(22478257)Sichuan Province Advanced Building Materials Production-Education Integration Innovation Demonstration Platform(Chuancaijiao[2022]No.106).
文摘Introducing methane at the anode side of a solid oxide electrolysis cell(SOEC)has been proven to effectively suppress the oxygen evolution reaction(OER),thereby enabling hydrogen production at significantly lower voltages.In this work,a double perovskite oxide,Sr_(2)Fe_(1.4)Pt_(0.1)Mo_(0.5)O_(6-δ)(abbreviated as Pt-SFM),was successfully synthesized by a liquid-phase method and employed as both an electronic conductor and a catalyst for methane oxidation at the SOEC anode.Following high-temperature treatment under a reducing atmosphere,platinum(Pt)nanoparticles were exsolved from the perovskite lattice and uniformly dispersed on the oxide surface.These exsolved Pt nanoparticles act as highly active sites for methane adsorption and oxidation.Electrochemical performance tests were conducted at 1123.15 K,and the results demonstrated that the Pt-SFM cell treated for 20 h(Pt-SFM 20 h)achieved a current density of 0.85 A·cm^(-2)at an applied voltage of 1.40 V.This performance corresponds to a 102.4%enhancement compared to the undoped SFM 20 h cell.The superior performance is attributed to the presence of exsolved Pt,which significantly improves the catalyst's ability to adsorb and dissociate methane molecules.Electrochemical impedance spectroscopy(EIS)analysis under open-circuit conditions revealed that the polarization impedance of the Pt-SFM 20 h cell was 1.25Ω·cm^(2),which is 49.2%lower than that of the SFM 20 h cell.Furthermore,a 45-h long-term stability test showed that the Pt-SFM 20 h cell maintained a stable performance,with a low voltage degradation rate of only 0.67 mV·h^(-1).
基金supported by the Scientific&Technical Project of the State Grid(5700--202490228A--1--1-ZN).
文摘The rapid advancement of artificial intelligence(AI)has significantly increased the computational load on data centers.AI-related computational activities consume considerable electricity and result in substantial carbon emissions.To mitigate these emissions,future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands.This paper aims to investigate how much carbon emission reduction can be achieved by using a carbonoriented demand response to guide the optimal planning and operation of data centers.A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load.In the planning model,future operation simulations comprehensively coordinate the temporal‒spatial flexibility of computational loads and the quality of service(QoS).An empirical study based on the proposed models is conducted on real-world data from China.The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province,Ningxia Hui Autonomous Region,Sichuan Province,Inner Mongolia Autonomous Region,and Qinghai Province,accounting for 57%of the total national increase in server capacity.33%of the computational load from Eastern China should be transferred to the West,which could reduce the overall load carbon emissions by 26%.
基金supported by the National Key Research and Development Program of China(Grant no.2022YFC2807603)。
文摘The Arctic and Antarctic regions are sensitive to global climate change.Monitoring climatological and ecological changes in such areas has become urgently necessary to address climate change and ensure sustainable human development.Therefore,it is important to develop automatic monitoring technology for polar regions and to produce air-ice-sea long-period,multiscale,and unmanned monitoring equipment.This paper describes an unmanned ice station observation system,the autonomous observation platform of a polar unmanned aerial vehicle,dual-use ice-sea buoys,temperature chain buoys,and a wind-solar-hydrogen storage clean energy system suitable for use in the extreme polar environment.Additionally,a coupled air-ice-sea autonomous observation station currently under development is also introduced.
基金supported by the Key Scientific and Technological Projects(2024KJGG27)of Tianfu Yongxing Laboratorythe Experimental Platform Open Innovation Funding(209042025003)of Sichuan Energy Internet Research Institute,Tsinghua University.
文摘As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.
基金support from the National Key Research and Development Project (Grant No. 2018YFB2200500, 2018YFB2202800)National Natural Science Foundation of China (Grant No. 61534004, 91964202, 61874081, 61851406, 91950119, and 61905196)。
文摘The realization of high-Q resonances in a silicon metasurface with various broken-symmetry blocks is reported. Theoretical analysis reveals that the sharp resonances in the metasurfaces originate from symmetry-protected bound in the continuum(BIC) and the magnetic dipole dominates these peculiar states. A smaller size of the defect in the broken-symmetry block gives rise to the resonance with a larger Q factor. Importantly, this relationship can be tuned by changing the structural parameter, resulting from the modulation of the topological configuration of BICs. Consequently, a Q factor of more than 3,000 can be easily achieved by optimizing dimensions of the nanostructure. At this sharp resonance, the intensity of the third harmonic generation signal in the patterned structure can be 368 times larger than that of the flat silicon film. The proposed strategy and underlying theory can open up new avenues to realize ultrasharp resonances, which may promote the development of the potential meta-devices for nonlinearity, lasing action, and sensing.
基金The research is supported by the National Natural Science Foundation of China(62072469)the National Key R&D Program of China(2018AAA0101502)+2 种基金Shandong Natural Science Foundation(ZR2019MF049)West Coast artificial intelligence technology innovation center(2019-1-5,2019-1-6)the Opening Project of Shanghai Trusted Industrial Control Platform(TICPSH202003015-ZC).
文摘Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power grids.Existing deep-learning-based methods can perform well if there are sufficient training data and enough computational resources.However,there are challenges in building models through centralized shared data due to data privacy concerns and industry competition.Federated learning is a new distributed machine learning approach which enables training models across edge devices while data reside locally.In this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM model.We design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting approach.Thorough evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.
基金support of national natural science foundation of China(No.52067021)natural science foundation of Xinjiang(2022D01C35)+1 种基金excellent youth scientific and technological talents plan of Xinjiang(No.2019Q012)major science and technology special project of Xinjiang Uygur Autonomous Region(2022A01002-2).
文摘Power transformer is one of the most crucial devices in power grid.It is significant to determine incipient faults of power transformers fast and accurately.Input features play critical roles in fault diagnosis accuracy.In order to further improve the fault diagnosis performance of power trans-formers,a random forest feature selection method coupled with optimized kernel extreme learning machine is presented in this study.Firstly,the random forest feature selection approach is adopted to rank 42 related input features derived from gas concentration,gas ratio and energy-weighted dissolved gas analysis.Afterwards,a kernel extreme learning machine tuned by the Aquila optimization algorithm is implemented to adjust crucial parameters and select the optimal feature subsets.The diagnosis accuracy is used to assess the fault diagnosis capability of concerned feature subsets.Finally,the optimal feature subsets are applied to establish fault diagnosis model.According to the experimental results based on two public datasets and comparison with 5 conventional approaches,it can be seen that the average accuracy of the pro-posed method is up to 94.5%,which is superior to that of other conventional approaches.Fault diagnosis performances verify that the optimum feature subset obtained by the presented method can dramatically improve power transformers fault diagnosis accuracy.
基金the financial support from the National Natural Science Foundation of China (Grant No. 51572174)
文摘A polyethylene oxide （PEO）-coated polyimide （PI） membrane was prepared by electrospinning method followed by a dip-coating and drying process for high-performance lithium-ion batteries （LIB）. 8emicrystal PEO was covered on the surface of the fibers and partially enmeshed in PI matrix, which formed unique porous structures. The pores with an average size of 4.1 μm and a porosity of 90% served as ion transport channels. Compared with the cell with Celgard 2400 membrane, the half-cell using PEO-coated P1 membrane as a separator exhibits excellent electrochemical performance both at room temperature and at low temperature. The electrolyte uptaking rate of PEO-coated PI membrane was 170% and the ionic conductivity was 3.83 × 10^-3 S cm^-1. PEO-coated PI membrane possessed 5.3 V electrochemical window. The electrode-electrolyte interfacial resistance was 62.4 Ω. The capacity retention ratios with PEO- coated PI membrane were 86.4% at 5 C and 73.5% at 10 C at 25 ℃ and 75% at 5 C at 0 ℃. Furthermore, the cell using the separator demonstrates excellent capacity retention over cycling. These advanced characteristics would boost the application of the PEO-coated PI membrane for high-power lithium ion battery.
基金supported by Manage Innovation Project of China Southern Power Grid Co.,Ltd.(No.GZHKJXM20210232).
文摘To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power.By studying the mathematical model of wind power output and calculating surplus wind power,as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank,an innovative capacity optimization allocation model was established.The objective of the model was to achieve the lowest total net present value over the entire life cycle.The model took into account the cost-benefit breakdown of equipment end-of-life cost,replacement cost,residual value gain,wind abandonment penalty,hydrogen transportation,and environmental value.The MATLAB-based platform invoked the CPLEX commercial solver to solve the model.Combined with the analysis of the annual average wind speed data from an offshore wind farm in Guangdong Province,the optimal capacity configuration results and the actual operation of the hydrogen production system were obtained.Under the calculation scenario,this hydrogen production system could consume 3,800 MWh of residual electricity from offshore wind power each year.It could achieve complete consumption of residual electricity from wind power without incurring the penalty cost of wind power.Additionally,it could produce 66,500 kg of green hydrogen from wind power,resulting in hydrogen sales revenue of 3.63 million RMB.It would also reduce pollutant emissions from coal-based hydrogen production by 1.5 tons and realize an environmental value of 4.83 million RMB.The annual net operating income exceeded 6 million RMB and the whole life cycle NPV income exceeded 50 million RMB.These results verified the feasibility and rationality of the established capacity optimization allocation model.The model could help advance power system planning and operation research and assist offshore wind farm operators in improving economic and environmental benefits.
基金supported by the Key Technology Research and Application Demonstration Project for Large-Scale Multi-Scenario Water Electrolysis Hydrogen Production(CTGTC/2023-LQ-06).
文摘The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers.These setups present various operational modes:independent operation and multi-electrolyzer parallelization,each with distinct advantages and challenges.This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers,establishing a weakly coupled system that combines the advantages of two modes.This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection,while preserving the option for independent operation after decoupling.A specialized thermal exchange model is developed for this topology,according to the dynamics of the lye mixer.The study further details startup procedures and proposes optimized control strategies tailored to this structural design.Waste heat from the caustic fully heats up the multiple electrolyzers connected to the lye mixing system,enabling a rapid hot start to enhance the system’s ability to track renewable energy.A control strategy is established to reduce heat loss and increase startup speed,and the optimal valve openings of the diverter valve and the manifold valve are determined.Simulation results indicate a considerable enhancement in operational efficiency,marked by an 18.28%improvement in startup speed and a 6.11%reduction in startup energy consumption inmulti-electrolyzer cluster systems,particularlywhen the systems are synchronized with photovoltaic energy sources.The findings represent a significant stride toward efficient and sustainable hydrogen production,offering a promising path for large-scale integration of renewable energy.
基金supported by the National Natural Science Foundation of China(U22A20220)the China Postdoctoral Science Foundation(2023M741887).
文摘Producing renewable e-methanol from e-hydrogen and diverse carbon sources is an essential way for clean methanol preparation.Despite this,the technical and economic feasibility of different e-methanols has yet to be thoroughly compared,leaving the most promising pathway to achieve commercialization yet evident.This paper reports a preliminary analysis of the lifecycle greenhouse gas(GHG)emissions and costs of four renewable e-methanols with different carbon sources:bio-carbon,direct air capture(DAC),fossil fuel carbon capture(FFCC),and fossil.The results indicate that renewable e-methanol costs(4167−10250 CNY/tonne)2−4 times the market rate of grey methanol.However,with the carbon tax and the projected decline in e-H2 costs,blue e-methanol may initially replace diesel in inland navigation,followed by a shift from heavy fuel oil(HFO)to green e-methanol in ocean ship-ping.Furthermore,the e-H2 cost and the availability of green carbon are vital factors affecting cost-effectiveness.A reduction in e-H2 cost from 2.1 CNY/Nm3 to 1.1 CNY/Nm3 resulting from a transition from an annual to a daily scheduling period,could lower e-methanol costs by 1200 to 2100 CNY.This paper also provides an in-depth discussion on the challenges and opportunities associated with the various green carbon sources.
基金supported by the State Grid Henan Economic Research Institute Science and Technology Project“Calculation and Demonstration of Distributed Photovoltaic Open Capacity Based on Multi-Source Heterogeneous Data”(5217L0230013).
文摘After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.
基金supported by the Major Project of Scientific Instrument and Equipment under National Key R&D Program of China“Development and Pilot Application of Internal and External Detection and Fault Diagnosis Equipment for Deep sea Oil and Gas Pipelines”(No.:2017YFF0108800)the Major Project of Risk Prevention and Control and Emergency Response Technologies and Equipment for Public Security under National Key R&D Program of China“Inspection,Examination and Security Technologies for Long-distance Oil and Gas Pipelines and Storage&Transportation Facilities”(No.:2016YFC0802100).
文摘In-line inspection is one of the most effective technical measures to ensure the safety of oil and gas pipelines.However,the extensive application of oil and gas pipelines of high-carbon steel,large diameter,high pressure and high flow rate in recent years brings about new challenges to in-line inspection.In this paper,we investigated the engineering application of new technologies and equipment,including the in-line inspection technology based on electromagnetic detector array,the extremely low frequency transient weak signal detection technology and new in-line inspection equipment.Then,the new technology and equipment of electromagnetic detector array were developed by applying the active emission and receiving of electromagnetic signal to inspect the metallic defects.Finally,noisy signals were inspected on the basis of Duffing chaotic oscillator,and thus the inspection of extremely low frequency signals in the noise was realized.In addition,the new method and equipment of extremely low frequency transient weak signal detection were developed and verified in actual inspection engineering.And the following research results were obtained.First,the in-line inspection technology based on electromagnetic detector array uses the synergetic effect between DC exciting magnetic field and high-frequency exciting magnetic field,so a perturbation response can be realized even by small signal excitation.Second,with the introduction of a novel compressive sampling of acquisition information composition,the speed bottleneck of in-line detector is broken through,and a new world record of the inspection speed of the electromagnetic detector array is set up,i.e.,8 m/s.Third,under the condition of high-speed movement,the received signals of in-line detector are weak and temporary while tracking and positioning outside the pipeline.And by virtue of the extremely low frequency transient weak signal detection method based on chaos,this technical bottleneck is broken through,and the signal-to-noise ratio(SNR)of transient weak signal in the process of real-time inspection is decreased below−10 dB.In conclusion,the superior performance of these new equipment has already been verified in the inspection engineering of in-service oil and gas pipelines.These research results will provide technical and equipment support for the safe operation of domestic main oil and gas pipelines.
基金supported in part by the National Natural Science Foundation of China(No.52122706)in part by the Tsinghua University Initiative Scientific Research Program.
文摘The difficulty in capital recovery for distributed re newable energy operators(DREOs)and the high charging costs at electric vehicle charging stations(EVCSs)have long been sig nificant challenges in power systems.Collaborative operation of DREOs and EVCSs can effectively address these challenges,yet few studies have approached incentivizing collaboration from the perspective of profit allocation.Therefore,this paper pro poses a fair and efficient profit allocation method.Incorporat ing the Gauss-Legendre quadrature formula into the AumannShapley value(GL-AS)method enables efficient calculation of the profit allocation of cooperative members.However,existing literature only discusses the profit allocation method of conven tional power generation units,limiting its applicability.This pa per addresses the problem of energy storage system(ESS)switching between charging and discharging in any time inter val and the time-varying problem of renewable energy power output,thereby ensuring the efficiency of the solution process.Furthermore,a novel profit allocation adjustment model is pro vided through the adoption of triangular fuzzy comprehensive evaluation(TFCE).Finally,the effectiveness of the proposed profit allocation method is validated through numerical simula tions in various scenarios.
基金supported by the National Natural Science Foundation of China(U22B6007 and U24B2077).
文摘With the increasing proportion of renewable energy,power system dispatch and electricity market clearing face significant engineering challenges,including growing model complexity,heightened precision requirements for solutions,and constrained computational time.These developments necessitate advancements in extra-high-speed approximate solution methods,techniques for solving strongly coupled problems,and largescale power system optimization techniques.This paper provides a comprehensive review of existing efficient optimization methodologies tailored to power systems with high proportion of renewable energy,analyzing their applicability to emerging challenges while outlining future research directions to address these complex operational problems.
