Thermally integrated Carnot battery(TI-CB)systems offer unique advantages for industrial waste heat recovery,but their performance under fluctuating,off-design conditions remains poorly understood.To address this gap,...Thermally integrated Carnot battery(TI-CB)systems offer unique advantages for industrial waste heat recovery,but their performance under fluctuating,off-design conditions remains poorly understood.To address this gap,this study proposes a quasi-dynamic mathematical model with solution methodologies applicable to both design and off-design operating conditions.A dynamic evaluation framework is also developed to account for the temporal mismatch between energy storage and release processes.A multi-operating-condition set constructed via multivariable sampling is used to enable systematic analysis of key design parameters under both design and off-design conditions.The results reveal that heat source utilization parameters and heat pump temperature rise are dominant factors affecting TI-CB performance,while off-design analysis shows that ORC mass flow rate variations have a more significant impact on system performance than heat pump fluctuations.Due to irreversible heat losses,an increase in the heat source temperature difference leads to a decrease in round-trip efficiency(ηrt)from 62.6%to 45.8%,whileηorc andηex also exhibit downward trends.A higher temperature lift in the heat pump results a decrease in the mean COP from 7.6 to 4.8,whereasηorc increases from 7.0%to 10.2%.Among working fluids evaluated,R1336mzz(Z)demonstrates superior performance but exhibits nonlinear behavior,while R1233zd(E)provides optimal stability across operating ranges,making it suitable for practical engineering applications.展开更多
Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To addre...Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.展开更多
Fibre electronics is redefining the role of conventional fibres,extending them from textile substrates for wearing and weaving to functional carriers for energy,sensing,display,and information processing.Remarkable ad...Fibre electronics is redefining the role of conventional fibres,extending them from textile substrates for wearing and weaving to functional carriers for energy,sensing,display,and information processing.Remarkable advances have recently been achieved in fibre-based energy harvesting,energy storage,sensing,and display technologies[1],[2],[3],[4].展开更多
With the intensification of the energy crisis and the worsening greenhouse effect,the development of sustainable integrated energy systems(IES)has become a crucial direction for energy transition.In this context,this ...With the intensification of the energy crisis and the worsening greenhouse effect,the development of sustainable integrated energy systems(IES)has become a crucial direction for energy transition.In this context,this paper proposes a low-carbon economic dispatch strategy under the green hydrogen certificate trading(GHCT)and the ladder-type carbon emission trading(CET)mechanism,enabling the coordinated utilization of green and blue hydrogen.Specifically,a proton exchange membrane electrolyzer(PEME)model that accounts for dynamic efficiency characteristics,and a steam methane reforming(SMR)model incorporating waste heat recovery,are developed.Based on these models,a hydrogen production–storage–utilization framework is established to enable the coordinated deployment of green and blue hydrogen.Furthermore,the gas turbine(GT)unit are retrofitted using oxygenenriched combustion carbon capture(OCC)technology,wherein the oxygen produced by PEME is employed to create an oxygen-enriched combustion environment.This approach reduces energy waste and facilitates low-carbon power generation.In addition,the GHCT mechanism is integrated into the system alongside the ladder-type CET mechanism,and their complementary effects are investigated.A comprehensive optimization model is then formulated to simultaneously achieve carbon reduction and economic efficiency across the system.Case study results show that the proposed strategy reduces wind curtailment by 7.77%,carbon emissions by 65.98%,and total cost by 12.57%.This study offers theoretical reference for the low-carbon,economic,and efficient operation of future energy systems.展开更多
This paper presents a geometric perspective that connects reciprocal transformations with multidimensional integrable deformations.By interpreting conservation laws as closed 1-forms,we formalize reciprocal transforma...This paper presents a geometric perspective that connects reciprocal transformations with multidimensional integrable deformations.By interpreting conservation laws as closed 1-forms,we formalize reciprocal transformations as induced local diffeomorphisms on the jet bundle.This allows us to characterize higher-dimensional deformations as systematic fiber bundle extensions,where fiber coordinates are generated by potential functions of the conservation laws.This perspective provides an interpretation for the covariant lifting of Lax pairs to higher dimensions and reveals that auto-Bäcklund transformations are composite diffeomorphisms.These results are applied to several classical integrable models.展开更多
Seamless integration and high-performance operation,including ultra-long transmission distance,high-speed communication capabilities,and high-precision event localization,are essential for advancing integrated sensing...Seamless integration and high-performance operation,including ultra-long transmission distance,high-speed communication capabilities,and high-precision event localization,are essential for advancing integrated sensing and communication(ISAC)systems over optical fiber.However,achieving all these attributes simultaneously remains a challenge in current systems.In this work,we propose a residual carrier-assisted,ultra-long ISAC scheme that enables high-speed data transmission and high-accuracy distributed vibration sensing with low complexity.展开更多
This paper is concerned with the problem of distributed coordination energy management of integrated energy systems(IESs). First, an energy management model for IESs is established and formulated as a distributed cons...This paper is concerned with the problem of distributed coordination energy management of integrated energy systems(IESs). First, an energy management model for IESs is established and formulated as a distributed constrained optimization problem. Then, an accelerated distributed event-triggered algorithm is developed to solve the problem. Compared with the existing algorithms, the developed algorithm simultaneously offers two advantages. On the one hand, the convergence speed of the algorithm is improved greatly by incorporating the second-order information. On the other hand, the algorithm is implemented with asynchronous communication by an eventtriggered mechanism, effectively reducing communication interact. Furthermore, the convergence and optimality of the algorithm are analyzed rigorously based on Lyapunov method.Finally, simulation studies are provided to validate the effectiveness of the algorithm.展开更多
Further investigation is warranted into the collaborative function of carbon capture and electrolysis-to-gas conversion technologies within integrated electro-gas energy systems,as well as optimized scheduling that ad...Further investigation is warranted into the collaborative function of carbon capture and electrolysis-to-gas conversion technologies within integrated electro-gas energy systems,as well as optimized scheduling that addresses the variability of wind and solar energy,to promote multi-energy complementarity and energy decarbonization while enhancing the capacity to absorb new energy.This work presents an optimized scheduling model for electro-gas integrated energy systems that include hydrogen storage,utilizing information gap decision theory(IGDT).A model is constructed that integrates the synergistic functions of carbon capture and storage(CCS),power-to-gas(P2G),and gas turbine units through electrical coupling.A carbon ladder trading mechanism is implemented to mitigate carbon emissions inside the system.A day-ahead optimization scheduling model is subsequently built to maximize system operational profit and ensure hydrogen storage safety,while considering economic viability,low-carbon performance,and safety.Secondly,the trinitrotoluene(TNT)equivalent approach and the half-lethal range were employed to quantify the safety concerns associated with hydrogen storage tanks,offering the model optimization guidance and conservative management.Ultimately,the CCS-P2G integrated operation accounted for the unpredictability in wind and solar energy production through the application of information gap decision theory.The model was solved using the GUROBI solver.The findings indicate that the proposed approach diminishes system carbon emissions by 66%,attains complete integration of wind and solar energy,and eliminates hazardous working time for hydrogen storage tanks,reducing it from 10 h to zero.It ensures system safety while guaranteeing profits of at least 90%of the anticipated value,accounting for changes in wind and solar output within±14%.This confirms the model’s efficacy in improving renewable energy integration rates,facilitating low-carbon,cost-effective,and secure system operation,while mitigating the unpredictability of renewable energy production.展开更多
Background:Diabetic cardiomyopathy(DCM)is a type of cardiomyopathy caused by long-term diabetes,characterized by abnormal myocardial structure and function,which can lead to heart failure.Berberine(BBR),a quaternary a...Background:Diabetic cardiomyopathy(DCM)is a type of cardiomyopathy caused by long-term diabetes,characterized by abnormal myocardial structure and function,which can lead to heart failure.Berberine(BBR),a quaternary ammonium alkaloid isolated from Coptidis Rhizoma,a traditional Chinese medicine,has superior anti-diabetic and heart-protective properties.The purpose of this study is to assess the impact of BBR on DCM.Methods:This study used a systems pharmacology approach to evaluate the related proteins and signalling pathways between BBR and DCM targets,combined with experimental validation using diabetic mouse heart sections.Microstructural and pathological changes were observed using Hematoxylin-eosin,Masson’s trichrome stain and wheat germ agglutinin staining.Immunofluorescence and western blot were used to determine protein expression.Results:The results indicate that BBR and DCM share 21 core relevant targets,with cross-targets predominantly located in mitochondrial,endoplasmic reticulum,and plasma membrane components.BBR exerts its main effects in improving DCM by maintaining mitochondrial integrity,particularly involving the PI3K-AKT-GSK3βand apoptosis signalling pathways.In addition,post-treatment changes in the key targets of BBR,including cysteine aspartate specific protease(Caspase)-3,phosphoinositide 3-kinase(PI3K)and mitochondria-related proteins,are suggestive of its efficacy.Conclusion:BBR crucially improves DCM by maintaining mitochondrial integrity,inhibiting apoptosis,and modulating PI3K-AKT-GSK3βsignaling.Further studies must address animal model limitations and validate clinical efficacy to understand BBR’s mechanisms fully and its potential clinical use.展开更多
With the development of integrated power and gas distribution systems(IPGS)incorporating renewable energy sources(RESs),coordinating the restoration processes of the power distribution system(PS)and the gas distributi...With the development of integrated power and gas distribution systems(IPGS)incorporating renewable energy sources(RESs),coordinating the restoration processes of the power distribution system(PS)and the gas distribution system(GS)by utilizing the benefits of RESs enhances service restoration.In this context,this paper proposes a coordinated service restoration framework that considers the uncertainty in RESs and the bi-directional restoration interactions between the PS and GS.Additionally,a coordinated service restoration model is developed considering the two systems’interdependency and the GS’s dynamic characteristics.The objective is to maximize the system resilience index while adhering to operational,dynamic,restoration logic,and interdependency constraints.A method for managing uncertainties in RES output is employed,and convexification techniques are applied to address the nonlinear constraints arising from the physical laws of the IPGS,thereby reducing solution complexity.As a result,the service restoration optimization problem of the IPGS can be formulated as a computationally tractable mixed-integer second-order cone programming problem.The effectiveness and superiority of the proposed framework are demonstrated through numerical simulations conducted on the interdependent IEEE 13-bus PS and 9-node GS.The comparative results show that the proposed framework improves the system resilience index by at least 65.07%compared to traditional methods.展开更多
The ability to simulate physical systems is essential for an understanding of their physical properties and advancing related technologies.However,simulating certain complex systems at scale,including many-body spin m...The ability to simulate physical systems is essential for an understanding of their physical properties and advancing related technologies.However,simulating certain complex systems at scale,including many-body spin models,is often a significant challenge for conventional computing approaches.Quantum simulators,employing controlled quantum systems that mimic the dynamics of a target system,can offer a more efficient approach.This work demonstrates the use of photonic circuits for quantum simulation of disordered spin systems,where quantum properties such as superposition and interference can be leveraged for a more efficient simulation.We fabricate and characterize a low-loss silicon-on-insulator chip with a buried aluminum mirror and a reconfigurable interferometer,which is employed in conjunction with two input photons to map the dynamics of a spin Hamiltonian with four-body interactions.Our results demonstrate several characteristics associated with the target system,such as spin-degenerate ground states and phase transitions,confirming the device's functionality as a quantum simulator of the spin system.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Integrated silicon photonics has emerged as a transformative technology for post-Moore’s law computing,offering intrinsic advantages of high bandwidth,ultralow latency and low energy consumption that far exceed tradi...Integrated silicon photonics has emerged as a transformative technology for post-Moore’s law computing,offering intrinsic advantages of high bandwidth,ultralow latency and low energy consumption that far exceed traditional electronic computing architectures[1−4].As artificial intelligence(AI)models continue to grow in complexity and scale,the demand for high-speed,energy-efficient computing has spurred intensive research into photonic computing as a promising alternative to electronic accelerators[5−7].Matrix multiply−accumulate(MAC)operations,the core of deep learning and combinatorial optimization algorithms,are particularly amenable to photonic implementation,as light enables parallel multiplication and accumulation with minimal data movement[8,9].However,the practical application of photonic computing has long been hindered by critical challenges including large-scale integration of photonic components,electro-optical co-packaging,guaranteed computation accuracy of analog photonic systems,and compatibility with mainstream AI models and algorithms[10,11].展开更多
Recently the integrated modular avionics (IMA) architecture which introduces the concept of resource partitions becomes popular as an alternative to the traditional federated architecture. This study investigates th...Recently the integrated modular avionics (IMA) architecture which introduces the concept of resource partitions becomes popular as an alternative to the traditional federated architecture. This study investigates the problem of designing hierarchical scheduling for IMA systems. The proposed scheduler model enables strong temporal partitioning, so that multiple hard real-time applications can be easily integrated into an uniprocessor platform. This paper derives the mathematic relationships among parti- tion cycle, partition capacity and schedulability under the real-time condition, and then proposes an algorithm for optimizing partition parameters. Real-time tasks with arbitrary deadlines are considered for generality. To further improve the basic algo- rithm and reduce the energy consumption for embedded systems in aircraft, a power optimization approach is also proposed by exploiting the slack time. Experimental results show that the designed system can guarantee the hard real-time requirement and reduce the power consumption by at least 14%.展开更多
In micro-electro-mechanical system based inertial navigation system(MEMS-INS)/global position system(GPS) integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obta...In micro-electro-mechanical system based inertial navigation system(MEMS-INS)/global position system(GPS) integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation(RE) and fault detection(FD). A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.展开更多
Purpose-With the development of railway systems towards intelligence,informatization and networking,their architecture design becomes increasingly complex.Traditional safety analysis methods(such as failure mode and e...Purpose-With the development of railway systems towards intelligence,informatization and networking,their architecture design becomes increasingly complex.Traditional safety analysis methods(such as failure mode and effects analysis(FMEA),fault tree analysis(FTA)and event tree analysis)can no longer realise integrated safety analysis across disciplines,domains and life cycles amid requirement drift,architecture iteration and operational scenario evolution.This paper aims to introduce a systematic,integrated,model-driven safety analysis framework for the entire life cycle of railway systems to address these complex safety challenges and improve the overall safety level of railway systems.Design/methodology/approach-First,the paper conducts a literature review of traditional railway safety analysis techniques and their applications,and analyzes the technical framework,core elements(modelling languages,methods,and tools),and advantages of Model-Based Systems Engineering(MBSE).Then,it studies the integration of MBSE and system safety analysis,focusing on typical international research cases(e.g.,the Methodology for the Description and Safety Analysis of Interoperable Systems(MeDISIS),the European Train Control System(ETCS)safety verification project SafeSysE,and the Reference Architecture for Model-Based System and Software Engineering in the Railway Domain(RAMSAS),etc.)and domestic research progress,and summarizes the core idea of integrating MBSE with safety analysis in the design process.Finally,it explores the key technologies of MBSE-based railway system safety analysis,including automatic mapping of architecture models to Fault Tree Analysis(FTA),dynamic linkage between behaviour models and Failure Mode and Effects Analysis(FMEA),multi-model collaboration and dynamic update,as well as technologies in three aspects:safety requirement analysis driven by railway operational tasks,integrated safety-function design analysis,and simulation-based safety verification via train-fleet operation modelling.The development and validation platform Platform for Integrated Systems and Mechatronic Engineering(PRISME)and tools such as the Dependability Engineering and Innovation System(DEIS),Behavior-Driven Development(BDD)frameworks,and International Business Machines(IBM)engineering suites were also utilized to support this research.Findings-The MBSE-based railway system safety analysis technique embeds safety activities into the forward-engineering workflow of MBSE-driven development,enabling concurrent safety and functional design.It solves the problems of model heterogeneity,data silos and process discontinuities in traditional safety analysis and realises end-to-end traceability and consistency from system requirements to safety analysis results.This technique not only provides a rigorous foundation for standardised,efficient and accurate safety assessment of railway systems but also offers technical support for early identification of potential safety issues,reduction of late-stage design changes and continuous optimisation of system safety performance.Originality/value-The innovation of this paper mainly includes three aspects:(1)It breaks the limitations of traditional document-driven safety analysis methods,constructs an MBSE-based integrated safety analysis framework covering the entire life cycle of railway systems and turns safety work from an ad-hoc add-on into a systematic,goal-oriented activity.(2)It proposes key integration technologies such as automatic mapping of SysML-based architecture models to FTA,dynamic linkage between behaviour models(state machine diagram/activity diagram)and FMEA and multi-model(FTA/FMEA/hazard and operability analysis)collaborative dynamic update,which guarantee the consistency and traceability of safety analysis data and improve the efficiency of safety analysis iteration.(3)It develops a set of MBSE-based railway safety analysis implementation paths,including task-driven safety requirement decomposition,integrated safety function failure propagation modelling and train-fleet operation simulation-based verification,providing a practical technical solution for the safety design and analysis of complex railway systems.展开更多
Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable e...Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.展开更多
An optimal structure design of the lattice mismatched GaInP/GaInAs/Ge solar cell with high photoelectric conversion efficiency was proposed. Two-dimensional Bi2Te3/Sb2Te3 nanosheets were prepared by solvothermal synth...An optimal structure design of the lattice mismatched GaInP/GaInAs/Ge solar cell with high photoelectric conversion efficiency was proposed. Two-dimensional Bi2Te3/Sb2Te3 nanosheets were prepared by solvothermal synthesis method used as thermoelectric(TE) functional materials, which is further hybrid with high conductive reduced graphene oxide(rGO) and carbon nanotubes(CNTs). TE film was then fabricated based on above materials. The power factor of the n-type TE film is 19.31 μW/mK2, and the power factor of the p-type TE film is 97.40 μW/mK2. The flexible TE device was integrated with flexible solar cell. Compared with the single photovoltaic(PV) cell, the efficiency of the as-prepared flexible integrated device measured under the AM1.5 illumination is significantly improved. The efficiency of the two parallel tests is increased from 27.26% and 26.59%, to 29.11% and 28.92%, respectively. The increasing ratio reaches 6.7%-8.8%.展开更多
To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hyd...To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.展开更多
Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally inte...Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52576234)a grant from the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(Grant No.LAPS25016)the National Key R&D Program of China(Grant No.2023YFE0108600).
摘要Thermally integrated Carnot battery(TI-CB)systems offer unique advantages for industrial waste heat recovery,but their performance under fluctuating,off-design conditions remains poorly understood.To address this gap,this study proposes a quasi-dynamic mathematical model with solution methodologies applicable to both design and off-design operating conditions.A dynamic evaluation framework is also developed to account for the temporal mismatch between energy storage and release processes.A multi-operating-condition set constructed via multivariable sampling is used to enable systematic analysis of key design parameters under both design and off-design conditions.The results reveal that heat source utilization parameters and heat pump temperature rise are dominant factors affecting TI-CB performance,while off-design analysis shows that ORC mass flow rate variations have a more significant impact on system performance than heat pump fluctuations.Due to irreversible heat losses,an increase in the heat source temperature difference leads to a decrease in round-trip efficiency(ηrt)from 62.6%to 45.8%,whileηorc andηex also exhibit downward trends.A higher temperature lift in the heat pump results a decrease in the mean COP from 7.6 to 4.8,whereasηorc increases from 7.0%to 10.2%.Among working fluids evaluated,R1336mzz(Z)demonstrates superior performance but exhibits nonlinear behavior,while R1233zd(E)provides optimal stability across operating ranges,making it suitable for practical engineering applications.
基金supported by the State Grid Corporation of China under Grant for Science and Technology Projects(No.SGNXJYOOZWJS2500029).
摘要Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.
基金supported by the National Natural Science Foundation of China(52125201)Beijing Natural Science Foundation(Z240025),and China Postdoctoral Science Foundation(2024M751613).
摘要Fibre electronics is redefining the role of conventional fibres,extending them from textile substrates for wearing and weaving to functional carriers for energy,sensing,display,and information processing.Remarkable advances have recently been achieved in fibre-based energy harvesting,energy storage,sensing,and display technologies[1],[2],[3],[4].
基金supported by National Natural Science Foundation of China(52477101)Natural Science Foundation of Jiangsu Province(BK20210932).
摘要With the intensification of the energy crisis and the worsening greenhouse effect,the development of sustainable integrated energy systems(IES)has become a crucial direction for energy transition.In this context,this paper proposes a low-carbon economic dispatch strategy under the green hydrogen certificate trading(GHCT)and the ladder-type carbon emission trading(CET)mechanism,enabling the coordinated utilization of green and blue hydrogen.Specifically,a proton exchange membrane electrolyzer(PEME)model that accounts for dynamic efficiency characteristics,and a steam methane reforming(SMR)model incorporating waste heat recovery,are developed.Based on these models,a hydrogen production–storage–utilization framework is established to enable the coordinated deployment of green and blue hydrogen.Furthermore,the gas turbine(GT)unit are retrofitted using oxygenenriched combustion carbon capture(OCC)technology,wherein the oxygen produced by PEME is employed to create an oxygen-enriched combustion environment.This approach reduces energy waste and facilitates low-carbon power generation.In addition,the GHCT mechanism is integrated into the system alongside the ladder-type CET mechanism,and their complementary effects are investigated.A comprehensive optimization model is then formulated to simultaneously achieve carbon reduction and economic efficiency across the system.Case study results show that the proposed strategy reduces wind curtailment by 7.77%,carbon emissions by 65.98%,and total cost by 12.57%.This study offers theoretical reference for the low-carbon,economic,and efficient operation of future energy systems.
基金sponsored by the National Natural Science Foundation of China(Nos.12235007,11975131)。
摘要This paper presents a geometric perspective that connects reciprocal transformations with multidimensional integrable deformations.By interpreting conservation laws as closed 1-forms,we formalize reciprocal transformations as induced local diffeomorphisms on the jet bundle.This allows us to characterize higher-dimensional deformations as systematic fiber bundle extensions,where fiber coordinates are generated by potential functions of the conservation laws.This perspective provides an interpretation for the covariant lifting of Lax pairs to higher dimensions and reveals that auto-Bäcklund transformations are composite diffeomorphisms.These results are applied to several classical integrable models.
基金National Natural Science Foundation of China(62571030,62271010)Beijing Natural Science Foundation(L247023,4242006,4222009)+1 种基金Basic and Applied Basic Research Foundation of Guangdong Province(2024A1515012248)High-performance Computing Platform of Peking University。
摘要Seamless integration and high-performance operation,including ultra-long transmission distance,high-speed communication capabilities,and high-precision event localization,are essential for advancing integrated sensing and communication(ISAC)systems over optical fiber.However,achieving all these attributes simultaneously remains a challenge in current systems.In this work,we propose a residual carrier-assisted,ultra-long ISAC scheme that enables high-speed data transmission and high-accuracy distributed vibration sensing with low complexity.
基金supported in part by the National Natural Science Foundation of China (62503128, U24B20184, 62373118)the National Key Research and Development Program of China (2023YFB3906403)
摘要This paper is concerned with the problem of distributed coordination energy management of integrated energy systems(IESs). First, an energy management model for IESs is established and formulated as a distributed constrained optimization problem. Then, an accelerated distributed event-triggered algorithm is developed to solve the problem. Compared with the existing algorithms, the developed algorithm simultaneously offers two advantages. On the one hand, the convergence speed of the algorithm is improved greatly by incorporating the second-order information. On the other hand, the algorithm is implemented with asynchronous communication by an eventtriggered mechanism, effectively reducing communication interact. Furthermore, the convergence and optimality of the algorithm are analyzed rigorously based on Lyapunov method.Finally, simulation studies are provided to validate the effectiveness of the algorithm.
摘要Further investigation is warranted into the collaborative function of carbon capture and electrolysis-to-gas conversion technologies within integrated electro-gas energy systems,as well as optimized scheduling that addresses the variability of wind and solar energy,to promote multi-energy complementarity and energy decarbonization while enhancing the capacity to absorb new energy.This work presents an optimized scheduling model for electro-gas integrated energy systems that include hydrogen storage,utilizing information gap decision theory(IGDT).A model is constructed that integrates the synergistic functions of carbon capture and storage(CCS),power-to-gas(P2G),and gas turbine units through electrical coupling.A carbon ladder trading mechanism is implemented to mitigate carbon emissions inside the system.A day-ahead optimization scheduling model is subsequently built to maximize system operational profit and ensure hydrogen storage safety,while considering economic viability,low-carbon performance,and safety.Secondly,the trinitrotoluene(TNT)equivalent approach and the half-lethal range were employed to quantify the safety concerns associated with hydrogen storage tanks,offering the model optimization guidance and conservative management.Ultimately,the CCS-P2G integrated operation accounted for the unpredictability in wind and solar energy production through the application of information gap decision theory.The model was solved using the GUROBI solver.The findings indicate that the proposed approach diminishes system carbon emissions by 66%,attains complete integration of wind and solar energy,and eliminates hazardous working time for hydrogen storage tanks,reducing it from 10 h to zero.It ensures system safety while guaranteeing profits of at least 90%of the anticipated value,accounting for changes in wind and solar output within±14%.This confirms the model’s efficacy in improving renewable energy integration rates,facilitating low-carbon,cost-effective,and secure system operation,while mitigating the unpredictability of renewable energy production.
基金supported by the National Natural Science Foundation of China(Grant No.82270892)Natural Science Foundation of Hubei Province(Grant No.2022CFB287)+2 种基金Xianning City Science and Technology Plan Project(Grant No.2022ZRKX052)School projects of Hubei University of Science and Technology(Grant No.2022T01,2021WG05,2021TNB01)Hubei University of Science and Technology School-level Fund(Grant No.BK202122).
摘要Background:Diabetic cardiomyopathy(DCM)is a type of cardiomyopathy caused by long-term diabetes,characterized by abnormal myocardial structure and function,which can lead to heart failure.Berberine(BBR),a quaternary ammonium alkaloid isolated from Coptidis Rhizoma,a traditional Chinese medicine,has superior anti-diabetic and heart-protective properties.The purpose of this study is to assess the impact of BBR on DCM.Methods:This study used a systems pharmacology approach to evaluate the related proteins and signalling pathways between BBR and DCM targets,combined with experimental validation using diabetic mouse heart sections.Microstructural and pathological changes were observed using Hematoxylin-eosin,Masson’s trichrome stain and wheat germ agglutinin staining.Immunofluorescence and western blot were used to determine protein expression.Results:The results indicate that BBR and DCM share 21 core relevant targets,with cross-targets predominantly located in mitochondrial,endoplasmic reticulum,and plasma membrane components.BBR exerts its main effects in improving DCM by maintaining mitochondrial integrity,particularly involving the PI3K-AKT-GSK3βand apoptosis signalling pathways.In addition,post-treatment changes in the key targets of BBR,including cysteine aspartate specific protease(Caspase)-3,phosphoinositide 3-kinase(PI3K)and mitochondria-related proteins,are suggestive of its efficacy.Conclusion:BBR crucially improves DCM by maintaining mitochondrial integrity,inhibiting apoptosis,and modulating PI3K-AKT-GSK3βsignaling.Further studies must address animal model limitations and validate clinical efficacy to understand BBR’s mechanisms fully and its potential clinical use.
基金funded by the Science and Technology Project of State Grid Shanxi Electric Power Company(5205E0230001).
摘要With the development of integrated power and gas distribution systems(IPGS)incorporating renewable energy sources(RESs),coordinating the restoration processes of the power distribution system(PS)and the gas distribution system(GS)by utilizing the benefits of RESs enhances service restoration.In this context,this paper proposes a coordinated service restoration framework that considers the uncertainty in RESs and the bi-directional restoration interactions between the PS and GS.Additionally,a coordinated service restoration model is developed considering the two systems’interdependency and the GS’s dynamic characteristics.The objective is to maximize the system resilience index while adhering to operational,dynamic,restoration logic,and interdependency constraints.A method for managing uncertainties in RES output is employed,and convexification techniques are applied to address the nonlinear constraints arising from the physical laws of the IPGS,thereby reducing solution complexity.As a result,the service restoration optimization problem of the IPGS can be formulated as a computationally tractable mixed-integer second-order cone programming problem.The effectiveness and superiority of the proposed framework are demonstrated through numerical simulations conducted on the interdependent IEEE 13-bus PS and 9-node GS.The comparative results show that the proposed framework improves the system resilience index by at least 65.07%compared to traditional methods.
基金supported by the Villum Fonden Young Investigator Project QUANPIC(Grant No.00025298)the Danish National Research Foundation Center of Excellence,SPOC(Grant No.DNRF123)。
摘要The ability to simulate physical systems is essential for an understanding of their physical properties and advancing related technologies.However,simulating certain complex systems at scale,including many-body spin models,is often a significant challenge for conventional computing approaches.Quantum simulators,employing controlled quantum systems that mimic the dynamics of a target system,can offer a more efficient approach.This work demonstrates the use of photonic circuits for quantum simulation of disordered spin systems,where quantum properties such as superposition and interference can be leveraged for a more efficient simulation.We fabricate and characterize a low-loss silicon-on-insulator chip with a buried aluminum mirror and a reconfigurable interferometer,which is employed in conjunction with two input photons to map the dynamics of a spin Hamiltonian with four-body interactions.Our results demonstrate several characteristics associated with the target system,such as spin-degenerate ground states and phase transitions,confirming the device's functionality as a quantum simulator of the spin system.
摘要This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
基金support from the National Natural Science Foundation of China(92573205,62235011,62505309,62535015)the Beijing Nova Program(20230484321)+2 种基金the Beijing Natural Science Foundation(4254116)the China Postdoctoral Science Foundation(2025M77082,2025T180231)the Postdoctoral Fellowship Program of CPSF(GZC20250559).
摘要Integrated silicon photonics has emerged as a transformative technology for post-Moore’s law computing,offering intrinsic advantages of high bandwidth,ultralow latency and low energy consumption that far exceed traditional electronic computing architectures[1−4].As artificial intelligence(AI)models continue to grow in complexity and scale,the demand for high-speed,energy-efficient computing has spurred intensive research into photonic computing as a promising alternative to electronic accelerators[5−7].Matrix multiply−accumulate(MAC)operations,the core of deep learning and combinatorial optimization algorithms,are particularly amenable to photonic implementation,as light enables parallel multiplication and accumulation with minimal data movement[8,9].However,the practical application of photonic computing has long been hindered by critical challenges including large-scale integration of photonic components,electro-optical co-packaging,guaranteed computation accuracy of analog photonic systems,and compatibility with mainstream AI models and algorithms[10,11].
基金Foundation item: National Natural Science Foundation of China (60879024)
摘要Recently the integrated modular avionics (IMA) architecture which introduces the concept of resource partitions becomes popular as an alternative to the traditional federated architecture. This study investigates the problem of designing hierarchical scheduling for IMA systems. The proposed scheduler model enables strong temporal partitioning, so that multiple hard real-time applications can be easily integrated into an uniprocessor platform. This paper derives the mathematic relationships among parti- tion cycle, partition capacity and schedulability under the real-time condition, and then proposes an algorithm for optimizing partition parameters. Real-time tasks with arbitrary deadlines are considered for generality. To further improve the basic algo- rithm and reduce the energy consumption for embedded systems in aircraft, a power optimization approach is also proposed by exploiting the slack time. Experimental results show that the designed system can guarantee the hard real-time requirement and reduce the power consumption by at least 14%.
基金co-supported by the National Natural Science Foundation of China(No.61153002)the Aeronautical Science Foundation of China(No.20130153002)
摘要In micro-electro-mechanical system based inertial navigation system(MEMS-INS)/global position system(GPS) integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation(RE) and fault detection(FD). A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.
基金supported by the Science and Technology Research and Development Program of China National Railway Corporation Limited(Grant No.N2024T008).
摘要Purpose-With the development of railway systems towards intelligence,informatization and networking,their architecture design becomes increasingly complex.Traditional safety analysis methods(such as failure mode and effects analysis(FMEA),fault tree analysis(FTA)and event tree analysis)can no longer realise integrated safety analysis across disciplines,domains and life cycles amid requirement drift,architecture iteration and operational scenario evolution.This paper aims to introduce a systematic,integrated,model-driven safety analysis framework for the entire life cycle of railway systems to address these complex safety challenges and improve the overall safety level of railway systems.Design/methodology/approach-First,the paper conducts a literature review of traditional railway safety analysis techniques and their applications,and analyzes the technical framework,core elements(modelling languages,methods,and tools),and advantages of Model-Based Systems Engineering(MBSE).Then,it studies the integration of MBSE and system safety analysis,focusing on typical international research cases(e.g.,the Methodology for the Description and Safety Analysis of Interoperable Systems(MeDISIS),the European Train Control System(ETCS)safety verification project SafeSysE,and the Reference Architecture for Model-Based System and Software Engineering in the Railway Domain(RAMSAS),etc.)and domestic research progress,and summarizes the core idea of integrating MBSE with safety analysis in the design process.Finally,it explores the key technologies of MBSE-based railway system safety analysis,including automatic mapping of architecture models to Fault Tree Analysis(FTA),dynamic linkage between behaviour models and Failure Mode and Effects Analysis(FMEA),multi-model collaboration and dynamic update,as well as technologies in three aspects:safety requirement analysis driven by railway operational tasks,integrated safety-function design analysis,and simulation-based safety verification via train-fleet operation modelling.The development and validation platform Platform for Integrated Systems and Mechatronic Engineering(PRISME)and tools such as the Dependability Engineering and Innovation System(DEIS),Behavior-Driven Development(BDD)frameworks,and International Business Machines(IBM)engineering suites were also utilized to support this research.Findings-The MBSE-based railway system safety analysis technique embeds safety activities into the forward-engineering workflow of MBSE-driven development,enabling concurrent safety and functional design.It solves the problems of model heterogeneity,data silos and process discontinuities in traditional safety analysis and realises end-to-end traceability and consistency from system requirements to safety analysis results.This technique not only provides a rigorous foundation for standardised,efficient and accurate safety assessment of railway systems but also offers technical support for early identification of potential safety issues,reduction of late-stage design changes and continuous optimisation of system safety performance.Originality/value-The innovation of this paper mainly includes three aspects:(1)It breaks the limitations of traditional document-driven safety analysis methods,constructs an MBSE-based integrated safety analysis framework covering the entire life cycle of railway systems and turns safety work from an ad-hoc add-on into a systematic,goal-oriented activity.(2)It proposes key integration technologies such as automatic mapping of SysML-based architecture models to FTA,dynamic linkage between behaviour models(state machine diagram/activity diagram)and FMEA and multi-model(FTA/FMEA/hazard and operability analysis)collaborative dynamic update,which guarantee the consistency and traceability of safety analysis data and improve the efficiency of safety analysis iteration.(3)It develops a set of MBSE-based railway safety analysis implementation paths,including task-driven safety requirement decomposition,integrated safety function failure propagation modelling and train-fleet operation simulation-based verification,providing a practical technical solution for the safety design and analysis of complex railway systems.
基金supported in part by the Science and Technology Development Fund,Macao SAR(File no.SKL-IOTSC(UM)-2021-2023,File no.0003/2020/AKP,and File no.0117/2022/A3)the Natural Science Foundation of Jiangsu Province,China(Operational reliability evaluation of multi-source and heterogeneous urban multi-energy systems,BK20220261).
摘要Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.
摘要An optimal structure design of the lattice mismatched GaInP/GaInAs/Ge solar cell with high photoelectric conversion efficiency was proposed. Two-dimensional Bi2Te3/Sb2Te3 nanosheets were prepared by solvothermal synthesis method used as thermoelectric(TE) functional materials, which is further hybrid with high conductive reduced graphene oxide(rGO) and carbon nanotubes(CNTs). TE film was then fabricated based on above materials. The power factor of the n-type TE film is 19.31 μW/mK2, and the power factor of the p-type TE film is 97.40 μW/mK2. The flexible TE device was integrated with flexible solar cell. Compared with the single photovoltaic(PV) cell, the efficiency of the as-prepared flexible integrated device measured under the AM1.5 illumination is significantly improved. The efficiency of the two parallel tests is increased from 27.26% and 26.59%, to 29.11% and 28.92%, respectively. The increasing ratio reaches 6.7%-8.8%.
摘要To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.
基金King Saud University for funding this research through the Researchers Supporting Program Number(RSPD2024R704),King Saud University,Riyadh,Saudi Arabia.
摘要Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.