Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways Hi...In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.展开更多
This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessme...This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity.To enable more accurate predictions of the optimal wind-solar ratio,a comprehensive complementarity rate is proposed,which allows for the optimization of wind-solar capacity based on this measure.Initially,the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power,enabling the calculation of the comprehensive complementarity rate.Following this,a joint planning model is developed to enhance the system’s economy and reliability.The goal is to minimize total costs,load deficit rates,and curtailment rates by applying an ImprovedMulti-Objective Particle SwarmOptimization algorithm(IMOPSO).Results show that when the proportion of wind power reaches 70%,the comprehensive complementarity rate is optimized.This optimization leads to a 14.83%reduction in total costs and a 9.27%decrease in curtailment rates.Compared to existing studies,this paper offers a multidimensional analysis of the relationship between the comprehensive complementarity rate and the optimal wind-solar ratio,thereby improving predictive accuracy and providing a valuable reference for research on the correlation between wind and solar power.展开更多
The configuration of a hybrid energy storage system(HESS)plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation,thereby enhancing the active power support capability of wi...The configuration of a hybrid energy storage system(HESS)plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation,thereby enhancing the active power support capability of wind power integration systems.However,most existing studies on HESS capacity configuration overlook the selfrecovery control of the state of charge(SOC),creating challenges in sustaining capacity during long-term operation.This omission can impair frequency regulation performance,increase capacity requirements,and shorten battery lifespan.To address these challenges,this study proposes a bi-level planning–operation capacity configuration model that explicitly incorporates SOC self-recovery control.In the operation layer,a variable-baseline charging/discharging strategy is developed to restore SOC by balancing positive and negative energy over a 24-h period,with the goal of maximizing daily operational benefits.In the planning layer,the annualized net life-cycle cost of the HESS isminimized by configuring storage capacity based on feedback fromthe operation layer.Thetwo layers operate iteratively to achieve coordinated optimization of capacity sizing and control strategy.Case study results demonstrate the effectiveness of the proposed method.Compared with a configuration without considering SOC self-recovery,the proposed approach reduces the 1-min wind power fluctuation rate to 3.53%,lowers the mean squared frequency error to 0.000084,and decreases the annualized net life-cycle cost by 545,000 CNY/MWh.展开更多
To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved...To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.展开更多
To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that ...To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that integrates the laddered carbon trading mechanism with demand response.Firstly,a dual dimensional DR model is constructed based on the characteristics of load elasticity.The alternativeDRenables flexible substitution of energy loads through complementary conversion of electricity/heat/cold multi-energy sources,while the price DR relies on timeof-use electricity price signals to guide load spatiotemporal migration;Secondly,the LCT mechanism is introduced to achieve optimal carbon emission costs through a tiered carbon quota allocation mechanism.On this basis,an optimization decision model is established with the core objective of maximizing the annual net profit of the park.The objective function takes into account energy sales revenue,generator unit costs,and investment and operation costs of multiple types of energy storage facilities.Themodel constraint system covers three key dimensions:dynamic operation constraints of power generation units,including unit output limits,ramping capability,and minimum start-stop time;the physical boundary of an electric/hot/cold multi-energy storage system involves energy storage capacity and charge/discharge efficiency;The multi-energy network coupling balance equation ensures that the energy conversion and transmission process satisfies the law of conservation of energy.Using CPLEX mathematical programming solver for simulation verification,construct an energy storage capacity configuration decision process that includes LCT-DR synergistic effect.The research results show that compared with the traditional single energy storage configuration mode,this strategy effectively enhances the economic feasibility and engineering practicality of industrial park operation by coordinating demand side resource scheduling and finely controlling carbon costs,while maintaining stable system operation.Its methodological framework provides a technical path that combines theoretical rigor and practical operability for the low-carbon transformation of regional integrated energy systems.展开更多
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed...Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.展开更多
Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connect...Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods.In this paper,a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation.A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance.The power forecast errors in different weather types are analyzed,and an energy storage system is used to compensate for the errors.The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system;the power and capacity of the energy storage unit are calculated at different confidence levels.The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction.The proposed method was validated using actual operating data from a PV power station.The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.展开更多
Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we p...Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.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
Spark is the most popular in-memory processing framework for big data analytics.Memory is the crucial resource for workloads to achieve performance acceleration on Spark.The extant memory capacity configuration approa...Spark is the most popular in-memory processing framework for big data analytics.Memory is the crucial resource for workloads to achieve performance acceleration on Spark.The extant memory capacity configuration approach in Spark is to statically configure the memory capacity for workloads based on user’s specifications.However,without the deep knowledge of the workload’s system-level characteristics,users in practice often conservatively overestimate the memory utilizations of their workloads and require resource manager to grant more memory share than that they actually need,which leads to the severe waste of memory resources.To address the above issue,SMConf,an automated memory capacity configuration solution for in-memory computing workloads in Spark is proposed.SMConf is designed based on the observation that,though there is not one-size-fit-all proper configuration,the one-size-fit-bunch configuration can be found for in-memory computing workloads.SMConf classifies typical Spark workloads into categories based on metrics across layers of Spark system stack.For each workload category,an individual memory requirement model is learned from the workload’s input data size and the strong-correlated configuration parameters.For an ad-hoc workload,SMConf matches its memory requirement signature to one of the workload categories with small-sized input data and determines its proper memory capacity configuration with the corresponding memory requirement model.Experimental results demonstrate that,compared to the conservative default configuration,SMConf can reduce the memory resource provision to Spark workloads by up to 69%with the slight performance degradation,and reduce the average turnaround time of Spark workloads by up to 55%in the multi-tenant environments.展开更多
Unified power quality conditioner(UPQC)with energy storage is commonly based on conventional capacity configuration strategy with power angle control.It has problems such as phase jumping before and after compensation...Unified power quality conditioner(UPQC)with energy storage is commonly based on conventional capacity configuration strategy with power angle control.It has problems such as phase jumping before and after compensation.DC-link cannot continuously emit active power externally.Therefore,this paper presents the compensation strategy of full load voltage magnitude and phase in capacity configuration of UPQC.The topology of UPQC is integrated a series active power filter(SAPF),a shunt active power filter(PAPF)and a photovoltaic-battery energy storage system(PV-BESS).The principle of full load voltage compensation is analyzed based on the PV-BESS-UPQC topology.Themagnitude constant of load voltage ismaintained by controlling the appropriate shunt compensation current.Then the UPQC capacity configuration is carried out using the full load voltage compensation strategy.The compensation capacity of UPQC series and shunt units are reduced.Finally,the simulation results show that the proposed compensation strategy reduces the capacity configuration by 5.11 kVA(36.4%)compared to the conventional compensation strategy.The proposed strategy can achieve full compensation of the load voltage,which can effectively reduce the capacity allocation and improve the economy of UPQC.It also has the PV-BESS units’ability of providing active power and can stabilize the DC-link voltage.展开更多
HOMER(Hybrid OptimizationModel for Electric Renewables)is an effective simulation and optimization platform for hybrid renewable energy.By inputting specific users’energy resource data(such as wind speed,solar radiat...HOMER(Hybrid OptimizationModel for Electric Renewables)is an effective simulation and optimization platform for hybrid renewable energy.By inputting specific users’energy resource data(such as wind speed,solar radiation,etc.)and load data,and by determining the types and models of components selected by the user,HOMER calculates and simulates the operational status of each component at every time step.Ultimately,it computes the energy balance of the system within specified constraints to simulate the overall system operation.This approach enables the reasonable determination of system component capacities,the evaluation of system feasibility,and the calculation of costs over the entire lifecycle of the system.In response to the challenges of matching capacities and high construction costs in wind-solar-storage multi-energy complementary power generation systems,This paper addresses issues such as difficulty in matching component capacities,high construction costs,and low system reliability in multi-energy complementary power generation systems.Using the HOMER hybrid renewable energy simulation and optimization platform,we constructed various hybrid energy systems for a specific region and considered multiple power supply modes.Thesoftware was used to solve for the optimal capacities and costs of each system.Four scenarios were analyzed:grid-only,grid-connected(purchase-sale)wind-solar-storage system,grid-connected(sale)wind-solar-storage system,and off-grid wind-solar-storage system.The results were compared and analyzed.HOMER can assess systemfeasibility and calculate the cost over its entire lifecycle.By inputting 8760 h of wind and solar resource data and load data for a specific region,and considering multiple system structures and power supply modes,the configuration results were evaluated using indicators such as cost and renewable energy utilization ratio.The simulation results indicate that the Net Present Cost(NPC)values across four different scenarios range from 1,877,292 CNY to 3,222,724 CNY,demonstrating significant cost differences.Among these scenarios,the grid-connected(purchase-sell)wind-solarstorage system exhibited the lowest NPC and the highest renewable energy utilization rate.Compared to a system relying solely on the grid,the NPC was reduced by 305,695 CNY,and the renewable energy utilization rate reached 74.7%.展开更多
The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of...The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.展开更多
The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
Secure and high-speed optical communications are of primary focus in information transmission.Although it is widely accepted that chaotic secure communication can provide superior physical layer security,it is challen...Secure and high-speed optical communications are of primary focus in information transmission.Although it is widely accepted that chaotic secure communication can provide superior physical layer security,it is challenging to meet the demand for high-speed increasing communication rate.We theoretically propose and experimentally demonstrate a conceptual paradigm for orbital angular momentum(OAM)configured chaotic laser(OAM-CCL)that allows access to high-security and massivecapacity optical communications.Combining 11 OAM modes and an all-optical feedback chaotic laser,we are able to theoretically empower a well-defined optical communication system with a total transmission capacity of 100 Gb∕s and a bit error rate below the forward error correction threshold 3.8×10^(-3).Furthermore,the OAM-CCL-based communication system is robust to 3D misalignment by resorting to appropriate mode spacing and beam waist.Finally,the conceptual paradigm of the OAM-CCL-based communication system is verified.In contrast to existing systems(traditional free-space optical communication or chaotic optical communication),the OAM-CCL-based communication system has threein-one characteristics of high security,massive capacity,and robustness.The findings demonstrate that this will promote the applicable settings of chaotic laser and provide an alternative promising route to guide high-security and massive-capacity optical communications.展开更多
Locomotion performance degradation after carrying payloads is a significant challenge for insect-scale microrobots.Previously,a legged microrobot named BHMbot with a high load-carrying capacity based on front-leg actu...Locomotion performance degradation after carrying payloads is a significant challenge for insect-scale microrobots.Previously,a legged microrobot named BHMbot with a high load-carrying capacity based on front-leg actuation configuration and efficient running gait was proposed.However,insects,mammals and reptiles in nature typically use their powerful rear legs to achieve rapid running gaits for predation or risk evasion.In this work,the load-carrying capacity of the BHMbots with front-leg actuation and rear-leg actuation configurations is comparatively studied.Simulations based on a dynamic model with four degrees of freedom,along with experiments,have been conducted to analyze the locomotion characteristics of the two configurations under different payload masses.Both simulation and experimental results indicate that the load-carrying capacity of the microrobots is closely related to their actuation configurations,which leads to different dynamic responses of the microrobots after carrying varying payload masses.For microrobots with body lengths of 15 mm,the rear-leg actuation configuration exhibits a 31.2%enhancement in running speed compared to the front-leg actuation configuration when unloaded.Conversely,when carrying payloads exceeding 5.7 times the body mass(350 mg),the rear-leg actuation configuration demonstrates an 80.1%reduction in running speed relative to the front-leg actuation configuration under the same payload conditions.展开更多
Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an importan...Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an important impact on operation efficiency and sortie rate.However,the resource station configuration is determined during the aircraft carrier design phase and is rarely modified as required,which may not be suitable for some pre-flight preparation missions.In order to solve the above defects,the joint optimization of flight deck resource station configuration and aircraft carrier pre-flight preparation scheduling is studied in this paper,which is formulated as a two-tier optimization decision-making framework.An improved variable neighborhood search algorithm with four original neighborhood structures is presented.Dispatch mission experiment and algorithm performance comparison experiment are carried out in the computational experiment section.The correlation between the pre-flight preparation time(makespan)and flight deck cabin occupancy percentage is given,and advantages of the proposed algorithm in solving the mathematical model are verified.展开更多
The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish bet...The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish between the events of low probability but high damage and the events of high probability but low damage.In order to ov+rcome these shortcomings,this paper proposes an extended risk analysis framework for the power system based on the partitioned multi-objective risk method(PMRM).展开更多
Using the theories of population carrying capacity and ecological elasticity in other fields for reference, the connotation of regional human settlement system was defined from the viewpoint of the complex relationshi...Using the theories of population carrying capacity and ecological elasticity in other fields for reference, the connotation of regional human settlement system was defined from the viewpoint of the complex relationship among the factors such as regional population, resources, environment and economic and social development in the context of China′s rapid urbanization. Then the concept and characterization methods of the regional human settlement carrying capacity were proposed by means of population scale. Furthermore, a model of carrying capacity-pressure-state-response(CPSR) on regional human settlement system was established by referencing pressure-state-response(PSR) model, and the Catastrophe Theory was introduced to determine the corresponding standards of multi-criteria programming and evaluation. Taking Dalian City, Liaoning Province, China as an example, an empirical analysis on evaluation of human settlement system from 2000 to 2012 was carried out. The results showed that the carrying capacity of human settlement system in Dalian was fluctuating between 9.6 × 106 to 10 × 106 persons with a quantitative stage of the dynamic regulation. During the research period the load index of human settlement system in Dalian dropped from 0.96 to 0.84 with a lower pressure of human settlement system than the national average level. And the emergency response grades of human settlement system in Dalian were kept in grade Ⅱ(orange warning) or grade Ⅲ(yellow warning). Human settlement system of Dalian was in slight security state as a whole, but the load had a tendency of increase in recent years. The related departments should pay close attention to regional human settlement system and take active measures to improve human settlement by both intensity control and total quantity control. By comparison, analysis and discussion, it was considered that the results were basically accordded with the current situations of human settlement in Dalian, and the evaluation results were more reliable, visualized and easily applied in practice. Therefore, the above-mentioned concepts, characterization and evaluation methods of the regional human settlement system and carrying capacity could provide a new thought and method for quantitative evaluation of human settlement.展开更多
基金supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.
基金This work was supported by Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity.To enable more accurate predictions of the optimal wind-solar ratio,a comprehensive complementarity rate is proposed,which allows for the optimization of wind-solar capacity based on this measure.Initially,the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power,enabling the calculation of the comprehensive complementarity rate.Following this,a joint planning model is developed to enhance the system’s economy and reliability.The goal is to minimize total costs,load deficit rates,and curtailment rates by applying an ImprovedMulti-Objective Particle SwarmOptimization algorithm(IMOPSO).Results show that when the proportion of wind power reaches 70%,the comprehensive complementarity rate is optimized.This optimization leads to a 14.83%reduction in total costs and a 9.27%decrease in curtailment rates.Compared to existing studies,this paper offers a multidimensional analysis of the relationship between the comprehensive complementarity rate and the optimal wind-solar ratio,thereby improving predictive accuracy and providing a valuable reference for research on the correlation between wind and solar power.
基金supported by Graduate Research and Innovation Program Project of Nanjing Institute of Technology(No.TB202517022).
文摘The configuration of a hybrid energy storage system(HESS)plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation,thereby enhancing the active power support capability of wind power integration systems.However,most existing studies on HESS capacity configuration overlook the selfrecovery control of the state of charge(SOC),creating challenges in sustaining capacity during long-term operation.This omission can impair frequency regulation performance,increase capacity requirements,and shorten battery lifespan.To address these challenges,this study proposes a bi-level planning–operation capacity configuration model that explicitly incorporates SOC self-recovery control.In the operation layer,a variable-baseline charging/discharging strategy is developed to restore SOC by balancing positive and negative energy over a 24-h period,with the goal of maximizing daily operational benefits.In the planning layer,the annualized net life-cycle cost of the HESS isminimized by configuring storage capacity based on feedback fromthe operation layer.Thetwo layers operate iteratively to achieve coordinated optimization of capacity sizing and control strategy.Case study results demonstrate the effectiveness of the proposed method.Compared with a configuration without considering SOC self-recovery,the proposed approach reduces the 1-min wind power fluctuation rate to 3.53%,lowers the mean squared frequency error to 0.000084,and decreases the annualized net life-cycle cost by 545,000 CNY/MWh.
基金by National Natural Science Foundation of China(62373142,62033014)Natural Science Foundation of Hunan Province(2025JJ70017,2022JJ50074).
文摘To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.
基金funded by Science and Technology Projects from State Grid Corporation of China,(Research on Adaptive Balance Optimization and Simulation Technology of Industrial community Energy System with High Proportion of Distributed Energy,No.:5100-202355752A-3-4-SY).
文摘To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that integrates the laddered carbon trading mechanism with demand response.Firstly,a dual dimensional DR model is constructed based on the characteristics of load elasticity.The alternativeDRenables flexible substitution of energy loads through complementary conversion of electricity/heat/cold multi-energy sources,while the price DR relies on timeof-use electricity price signals to guide load spatiotemporal migration;Secondly,the LCT mechanism is introduced to achieve optimal carbon emission costs through a tiered carbon quota allocation mechanism.On this basis,an optimization decision model is established with the core objective of maximizing the annual net profit of the park.The objective function takes into account energy sales revenue,generator unit costs,and investment and operation costs of multiple types of energy storage facilities.Themodel constraint system covers three key dimensions:dynamic operation constraints of power generation units,including unit output limits,ramping capability,and minimum start-stop time;the physical boundary of an electric/hot/cold multi-energy storage system involves energy storage capacity and charge/discharge efficiency;The multi-energy network coupling balance equation ensures that the energy conversion and transmission process satisfies the law of conservation of energy.Using CPLEX mathematical programming solver for simulation verification,construct an energy storage capacity configuration decision process that includes LCT-DR synergistic effect.The research results show that compared with the traditional single energy storage configuration mode,this strategy effectively enhances the economic feasibility and engineering practicality of industrial park operation by coordinating demand side resource scheduling and finely controlling carbon costs,while maintaining stable system operation.Its methodological framework provides a technical path that combines theoretical rigor and practical operability for the low-carbon transformation of regional integrated energy systems.
基金Project(3502Z20179026)supported by Xiamen Science and Technology Project,China。
文摘Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.
基金supported by Nation Key R&D Program of China(2021YFE0102400).
文摘Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods.In this paper,a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation.A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance.The power forecast errors in different weather types are analyzed,and an energy storage system is used to compensate for the errors.The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system;the power and capacity of the energy storage unit are calculated at different confidence levels.The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction.The proposed method was validated using actual operating data from a PV power station.The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.
基金funded by Major Science and Technology Projects in Gansu Province(19ZD2GA003).
文摘Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.
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National Key R&D Program of China(No.2017YFC0803300)the National Natural Science of Foundation of China(No.61703013).
文摘Spark is the most popular in-memory processing framework for big data analytics.Memory is the crucial resource for workloads to achieve performance acceleration on Spark.The extant memory capacity configuration approach in Spark is to statically configure the memory capacity for workloads based on user’s specifications.However,without the deep knowledge of the workload’s system-level characteristics,users in practice often conservatively overestimate the memory utilizations of their workloads and require resource manager to grant more memory share than that they actually need,which leads to the severe waste of memory resources.To address the above issue,SMConf,an automated memory capacity configuration solution for in-memory computing workloads in Spark is proposed.SMConf is designed based on the observation that,though there is not one-size-fit-all proper configuration,the one-size-fit-bunch configuration can be found for in-memory computing workloads.SMConf classifies typical Spark workloads into categories based on metrics across layers of Spark system stack.For each workload category,an individual memory requirement model is learned from the workload’s input data size and the strong-correlated configuration parameters.For an ad-hoc workload,SMConf matches its memory requirement signature to one of the workload categories with small-sized input data and determines its proper memory capacity configuration with the corresponding memory requirement model.Experimental results demonstrate that,compared to the conservative default configuration,SMConf can reduce the memory resource provision to Spark workloads by up to 69%with the slight performance degradation,and reduce the average turnaround time of Spark workloads by up to 55%in the multi-tenant environments.
基金Supported by Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12)Supported by Talent Projects of Jiangsu University of Technology(KYY20018)Supported by Graduate Practice Innovation Program of Jiangsu University of Technology(XSJCX21_32).
文摘Unified power quality conditioner(UPQC)with energy storage is commonly based on conventional capacity configuration strategy with power angle control.It has problems such as phase jumping before and after compensation.DC-link cannot continuously emit active power externally.Therefore,this paper presents the compensation strategy of full load voltage magnitude and phase in capacity configuration of UPQC.The topology of UPQC is integrated a series active power filter(SAPF),a shunt active power filter(PAPF)and a photovoltaic-battery energy storage system(PV-BESS).The principle of full load voltage compensation is analyzed based on the PV-BESS-UPQC topology.Themagnitude constant of load voltage ismaintained by controlling the appropriate shunt compensation current.Then the UPQC capacity configuration is carried out using the full load voltage compensation strategy.The compensation capacity of UPQC series and shunt units are reduced.Finally,the simulation results show that the proposed compensation strategy reduces the capacity configuration by 5.11 kVA(36.4%)compared to the conventional compensation strategy.The proposed strategy can achieve full compensation of the load voltage,which can effectively reduce the capacity allocation and improve the economy of UPQC.It also has the PV-BESS units’ability of providing active power and can stabilize the DC-link voltage.
基金supported in part by the Inner Mongolia Autonomous Region Science and Technology Project Fund(2021GG0336)Inner Mongolia Natural Science Fund(2023ZD20).
文摘HOMER(Hybrid OptimizationModel for Electric Renewables)is an effective simulation and optimization platform for hybrid renewable energy.By inputting specific users’energy resource data(such as wind speed,solar radiation,etc.)and load data,and by determining the types and models of components selected by the user,HOMER calculates and simulates the operational status of each component at every time step.Ultimately,it computes the energy balance of the system within specified constraints to simulate the overall system operation.This approach enables the reasonable determination of system component capacities,the evaluation of system feasibility,and the calculation of costs over the entire lifecycle of the system.In response to the challenges of matching capacities and high construction costs in wind-solar-storage multi-energy complementary power generation systems,This paper addresses issues such as difficulty in matching component capacities,high construction costs,and low system reliability in multi-energy complementary power generation systems.Using the HOMER hybrid renewable energy simulation and optimization platform,we constructed various hybrid energy systems for a specific region and considered multiple power supply modes.Thesoftware was used to solve for the optimal capacities and costs of each system.Four scenarios were analyzed:grid-only,grid-connected(purchase-sale)wind-solar-storage system,grid-connected(sale)wind-solar-storage system,and off-grid wind-solar-storage system.The results were compared and analyzed.HOMER can assess systemfeasibility and calculate the cost over its entire lifecycle.By inputting 8760 h of wind and solar resource data and load data for a specific region,and considering multiple system structures and power supply modes,the configuration results were evaluated using indicators such as cost and renewable energy utilization ratio.The simulation results indicate that the Net Present Cost(NPC)values across four different scenarios range from 1,877,292 CNY to 3,222,724 CNY,demonstrating significant cost differences.Among these scenarios,the grid-connected(purchase-sell)wind-solarstorage system exhibited the lowest NPC and the highest renewable energy utilization rate.Compared to a system relying solely on the grid,the NPC was reduced by 305,695 CNY,and the renewable energy utilization rate reached 74.7%.
基金funded by the National Key Research and Development Program of China(2024YFE0106800)Natural Science Foundation of Shandong Province(ZR2021ME199).
文摘The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
基金supported by the National Natural Science Foundation of China(Grant Nos.61927811,62035009,and 11974258)the Fundamental Research Program of Shanxi Province(Grant No.202103021224038)+3 种基金the Development Fund in Science and Technology of Shanxi Province(Grant No.YDZJSX2021A009)the Open Fund of State Key Laboratory of Applied Optics(Grant No.SKLAO2022001A09)the Science and Technology Foundation of Guizhou Province(Grant Nos.ZK[2021]031 and ZK[2023]049)the Program for Guangdong Introducing Innovative and Entrepreneurial Teams.
文摘Secure and high-speed optical communications are of primary focus in information transmission.Although it is widely accepted that chaotic secure communication can provide superior physical layer security,it is challenging to meet the demand for high-speed increasing communication rate.We theoretically propose and experimentally demonstrate a conceptual paradigm for orbital angular momentum(OAM)configured chaotic laser(OAM-CCL)that allows access to high-security and massivecapacity optical communications.Combining 11 OAM modes and an all-optical feedback chaotic laser,we are able to theoretically empower a well-defined optical communication system with a total transmission capacity of 100 Gb∕s and a bit error rate below the forward error correction threshold 3.8×10^(-3).Furthermore,the OAM-CCL-based communication system is robust to 3D misalignment by resorting to appropriate mode spacing and beam waist.Finally,the conceptual paradigm of the OAM-CCL-based communication system is verified.In contrast to existing systems(traditional free-space optical communication or chaotic optical communication),the OAM-CCL-based communication system has threein-one characteristics of high security,massive capacity,and robustness.The findings demonstrate that this will promote the applicable settings of chaotic laser and provide an alternative promising route to guide high-security and massive-capacity optical communications.
基金supported in part by Beijing Natural Science Foundation under Grant 3232010in part by the National Natural Science Foundation of China under Grant 12002017+2 种基金in part by AECC Industry-university Collocation Fund under Grant HFZL2023CXY026in part by Beihang Outstanding Young Scholars Project under Grant YWF-23-L-1201in part by 111 Project under Grant B08009.
文摘Locomotion performance degradation after carrying payloads is a significant challenge for insect-scale microrobots.Previously,a legged microrobot named BHMbot with a high load-carrying capacity based on front-leg actuation configuration and efficient running gait was proposed.However,insects,mammals and reptiles in nature typically use their powerful rear legs to achieve rapid running gaits for predation or risk evasion.In this work,the load-carrying capacity of the BHMbots with front-leg actuation and rear-leg actuation configurations is comparatively studied.Simulations based on a dynamic model with four degrees of freedom,along with experiments,have been conducted to analyze the locomotion characteristics of the two configurations under different payload masses.Both simulation and experimental results indicate that the load-carrying capacity of the microrobots is closely related to their actuation configurations,which leads to different dynamic responses of the microrobots after carrying varying payload masses.For microrobots with body lengths of 15 mm,the rear-leg actuation configuration exhibits a 31.2%enhancement in running speed compared to the front-leg actuation configuration when unloaded.Conversely,when carrying payloads exceeding 5.7 times the body mass(350 mg),the rear-leg actuation configuration demonstrates an 80.1%reduction in running speed relative to the front-leg actuation configuration under the same payload conditions.
文摘Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an important impact on operation efficiency and sortie rate.However,the resource station configuration is determined during the aircraft carrier design phase and is rarely modified as required,which may not be suitable for some pre-flight preparation missions.In order to solve the above defects,the joint optimization of flight deck resource station configuration and aircraft carrier pre-flight preparation scheduling is studied in this paper,which is formulated as a two-tier optimization decision-making framework.An improved variable neighborhood search algorithm with four original neighborhood structures is presented.Dispatch mission experiment and algorithm performance comparison experiment are carried out in the computational experiment section.The correlation between the pre-flight preparation time(makespan)and flight deck cabin occupancy percentage is given,and advantages of the proposed algorithm in solving the mathematical model are verified.
文摘The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish between the events of low probability but high damage and the events of high probability but low damage.In order to ov+rcome these shortcomings,this paper proposes an extended risk analysis framework for the power system based on the partitioned multi-objective risk method(PMRM).
基金Under the auspices of Project of Humanities and Social Sciences,Ministry of Education of China(No.14YJAZH112)Social Sciences Planning Project of Liaoning Province(No.L13BJL019)+1 种基金Economic and Social Development Project of Liaoning Province(No.2014lslktzixxjx-06)Specialized Research Fund for Doctoral Program of Higher Education,Ministry of Education of China(No.20122136110003)
文摘Using the theories of population carrying capacity and ecological elasticity in other fields for reference, the connotation of regional human settlement system was defined from the viewpoint of the complex relationship among the factors such as regional population, resources, environment and economic and social development in the context of China′s rapid urbanization. Then the concept and characterization methods of the regional human settlement carrying capacity were proposed by means of population scale. Furthermore, a model of carrying capacity-pressure-state-response(CPSR) on regional human settlement system was established by referencing pressure-state-response(PSR) model, and the Catastrophe Theory was introduced to determine the corresponding standards of multi-criteria programming and evaluation. Taking Dalian City, Liaoning Province, China as an example, an empirical analysis on evaluation of human settlement system from 2000 to 2012 was carried out. The results showed that the carrying capacity of human settlement system in Dalian was fluctuating between 9.6 × 106 to 10 × 106 persons with a quantitative stage of the dynamic regulation. During the research period the load index of human settlement system in Dalian dropped from 0.96 to 0.84 with a lower pressure of human settlement system than the national average level. And the emergency response grades of human settlement system in Dalian were kept in grade Ⅱ(orange warning) or grade Ⅲ(yellow warning). Human settlement system of Dalian was in slight security state as a whole, but the load had a tendency of increase in recent years. The related departments should pay close attention to regional human settlement system and take active measures to improve human settlement by both intensity control and total quantity control. By comparison, analysis and discussion, it was considered that the results were basically accordded with the current situations of human settlement in Dalian, and the evaluation results were more reliable, visualized and easily applied in practice. Therefore, the above-mentioned concepts, characterization and evaluation methods of the regional human settlement system and carrying capacity could provide a new thought and method for quantitative evaluation of human settlement.
