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
Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and...Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and charge distribution by introducing relatively weak electronegative atoms into the first/second shell is an efficient way,but it remains challenging for elucidating the underlying mechanism of interaction.Herein,a practical strategy was reported to rationally design single cobalt atoms coordinated with both phosphorus and nitrogen atoms in a hierarchically porous carbon derived from metal-organic frameworks.X-ray absorption spectrum reveals that atomically dispersed Co sites are coordinated with four N atoms in the first shell and varying numbers of P atoms in the second shell(denoted as Co-N/P-C).The prepared catalyst exhibits excellent oxygen reduction reaction(ORR)activity as well as zinc-air battery performance.The introduction of P atoms in the Co-SACs weakens the interaction between Co and N,significantly promoting the adsorption process of ^(*)OOH,resulting in the acceleration of reaction kinetics and reduction of thermodynamic barrier,responsible for the increased intrinsic activity.Our discovery provides insights into an ultimate design of single-atom catalysts with adjustable electrocatalytic activities for efficient electrochemical energy conversion.展开更多
Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage...Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.展开更多
In an integrated energy system(IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other ...In an integrated energy system(IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other subsystems.The energy supply should be globally optimized during the IES energy supply restoration process to produce the highest restoration net income. Mobile emergency sources can be quickly and flexibly connected to supply energy after an energy outage to ensure a reliable supply to the system, which adds complexity to the decision. This study focuses on a powergas IES with mobile emergency sources and analyzes the coupling relationship between the gas distribution system and the power distribution system in terms of sources, networks, and loads, and the influence of mobile emergency source transportation. The influence of the transient process caused by the restoration operation of the gas distribution system on the power distribution system is also discussed. An optimization model for power-gas IES restoration was established with the objective of maximizing the net income. The coordinated restoration optimization decision-making process was also built to realize the decoupling iteration of the power-gas IES, including system status recognition, mobile emergency source dispatching optimization, gas-to-power gas flow optimization, and parallel intra-partition restoration scheme optimization for both the power and gas distribution systems. A simulation test power-gas IES consisting of an 81-node medium-voltage power distribution network, an 89-node medium-pressure gas distribution network, and four mobile emergency sources was constructed. The simulation analysis verified the efficiency of the proposed coordinated restoration optimization method.展开更多
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance i...A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.展开更多
Inspired by Model Predictive Interaction Control(MPIC),this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with mult...Inspired by Model Predictive Interaction Control(MPIC),this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid-soft heterogeneous contact tasks.Within the MPIC,robot dynamics are linearized,and Extended Kalman Filters are used for the online estimation of geometry-aware parameters.Meanwhile,a geometry-aware Hertz contact model is introduced for the online estimation of contact forces.We then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization MPC.Experimental validations were designed for two contact modes:“single-point contact”and“continuous contact”,involving materials with four different Young’s moduli and tested in human arm“relaxation-contraction”task.Results indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee safety.Our method reduces the maximum impact force by 50%and decreases the average force error by 42%.The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid,soft,and deformable objects.展开更多
Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate ener...Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.展开更多
Chitosan–metal complexes have been widely studied in wastewater treatment, but there are still various factors in complex preparation which are collectively responsible for improving the adsorption capacity need to b...Chitosan–metal complexes have been widely studied in wastewater treatment, but there are still various factors in complex preparation which are collectively responsible for improving the adsorption capacity need to be further studied. Thus, this study investigates the factors affecting the adsorption ability of chitosan–metal complex adsorbents, including various kinds of metal centers, different metal salts and crosslinking degree. The results show that the chitosan–Fe（ Ⅲ） complex prepared by sulfate salts exhibited the best adsorption efficiency（100%） for various dyes in very short time duration（10 min）, and its maximum adsorption capacity achieved 349.22 mg/g. The anion of the metal salt which was used in preparation played an important role to enhance the adsorption ability of chitosan–metal complex. SO4^（2-） ions not only had the effect of crosslinking through electrostatic interaction with amine group of chitosan polymer, but also could facilitate the chelation of metal ions with chitosan polymer during the synthesis process.Additionally, the p H sensitivity and the sensitivity of ionic environment for chitosan–metal complex were analyzed. We hope that these factors affecting the adsorption of the chitosan–metal complex can help not only in optimizing its use but also in designing new chitosan–metal based complexes.展开更多
Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuratio...Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.展开更多
Temperature prediction plays an important role in ring die granulator control,which can influence the quantity and quality of production. Temperature prediction modeling is a complicated problem with its MIMO, nonline...Temperature prediction plays an important role in ring die granulator control,which can influence the quantity and quality of production. Temperature prediction modeling is a complicated problem with its MIMO, nonlinear, and large time-delay characteristics. Support vector machine( SVM) has been successfully based on small data. But its accuracy is not high,in contrast,if the number of data and dimension of feature increase,the training time of model will increase dramatically. In this paper,a linear SVM was applied combing with cyclic coordinate descent( CCD) to solving big data regression. It was mathematically strictly proved and validated by simulation. Meanwhile,real data were conducted to prove the linear SVM model's effect. Compared with other methods for big data in simulation, this algorithm has apparent advantage not only in fast modeling but also in high fitness.展开更多
Regional integrated energy system(RIES)cluster,i.e.,multi-source integration and multi-region coordination,is an effective approach for increasing energy utilization efficiency.The hierarchical architecture and limite...Regional integrated energy system(RIES)cluster,i.e.,multi-source integration and multi-region coordination,is an effective approach for increasing energy utilization efficiency.The hierarchical architecture and limited information sharing of RIES cluster make it difficult for traditional game theory to accurately describe their game behavior.Thus,a hierarchical game approach considering bounded rationality is proposed in this paper to balance the interests of optimizing RIES cluster under privacy protection.A Stackelberg game with the cluster operator(CO)as the leader and multiple RIES as followers is developed to simultaneously optimize leader benefit and RIES utilization efficiency.Concurrently,a slight altruistic function is introduced to simulate the game behavior of each RIES agent on whether to cooperate or not.By introducing an evolutionary game based on bounded rationality in the lower layer,the flaw of the assumption that participants are completely rational can be avoided.Specially,for autonomous optimal dispatching,each RIES is treated as a prosumer,fexibly switching its market participation role to achieve cluster coordination optimization.Case studies on a RIES cluster verify effectiveness of the proposed approach.展开更多
Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low ...Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.展开更多
The coordinated Bayesian optimization algorithm（CBOA） is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure（ECM） and the firep...The coordinated Bayesian optimization algorithm（CBOA） is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure（ECM） and the firepower attack systems.The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome.Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations,but also maintain the population multiplicity,and enhance the algorithm performance.The simulation result confirms the algorithm validity.展开更多
As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve t...As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.展开更多
A mismatch between the rapid growth of grid-connected offshore wind farms(OWFs)and the de-lay of onshore transmission expansion(OTE)planning has caused significant wind curtailment in power systems.To alleviate this p...A mismatch between the rapid growth of grid-connected offshore wind farms(OWFs)and the de-lay of onshore transmission expansion(OTE)planning has caused significant wind curtailment in power systems.To alleviate this problem,a coordinated planning(CP)model of multiple inner networks of OWFs(INOWFs)and OTE is established in this paper.In the proposed CP model,the explicit connection topology constraints of a new double-sided ring topology for INOWFs are defined,and the connection topologies and electrical components of both INOWFs and OTE are coordinately optimized.In addition,a parallel random search method is proposed to obtain the set of feasible connection topology schemes of each INOWF,which can contract the feasible region of the CP model and reduce the difficulty in obtaining the optimal solution.Finally,a decomposition and coordina-tion planning algorithm is developed to decompose the original complex optimization model into two tractable sub-models for INOWF and OTE planning.This ap-proach efficiently obtains the optimal CP scheme for multiple INOWFs and OTE through alternating itera-tions.Case studies on the modified IEEE 39-bus system with two OWFs and an actual provincial power system with six OWFs demonstrate the correctness and efficiency of the proposed model and algorithm.展开更多
The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry.Therefore,it is extremely urgent to transform energy production methods...The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry.Therefore,it is extremely urgent to transform energy production methods and vigorously develop renewable energy sources.It is therefore important to ensure the stability and operation of a large multi-energy complementary system,and provide theoretical support for the world’s largest single complementary demonstration project with hydro-wind-PV power-battery storage in Qinghai Province.Considering all the multiple power supply constraints,an optimization scheduling model is established with the objective of minimizing the volatility of output power.As particle swarm optimization(PSO)has a problem of premature convergence and slow convergence in the latter half,combined with niche technology in evolution,a niche particle swarm optimization(NPSO)is proposed to determine the optimal solution of the model.Finally,the multiple stations’coordinated operation is analyzed taking the example of 10 million kilowatt complementary power stations with hydropower,wind power,PV power,and battery storage in the Yellow River Company Hainan prefecture.The case verifies the rationality and feasibility of the model.It shows that complementary operations can improve the utilization rate of renewable energy and reduce the impact of wind and PV power’s volatility on the power grid.展开更多
Currently, the power electronics-based devices, includinglarge-scale non-synchronized generators and reactivepower compensators, are widely used in power grids. This helpsintroduce the coupling interactions between th...Currently, the power electronics-based devices, includinglarge-scale non-synchronized generators and reactivepower compensators, are widely used in power grids. This helpsintroduce the coupling interactions between the devices andthe power grid, resulting in a new sub-synchronous oscillationphenomenon. It is a critical element for the stability operation ofthe power grid and its devices. In this paper, the sub-synchronousoscillation phenomenon of the power grid connected with largescalewind power generation is analyzed in detail. Then, inorder to damp the sub-synchronous oscillation, a coordinateddamping optimization control strategy for wind power generatorsand their reactive power compensators is proposed. The proposedcoordinated control strategy tracks the sub-synchronousoscillation current signal to correct the corresponding controlsignal, which increases the damping of power electronics. Theresponse characteristics of the proposed control strategy areanalyzed, and a self-optimization parameter tuning method basedon sensitivity analysis is proposed. The simulation results validatethe effectiveness and the availability of the proposed controlstrategy.展开更多
In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the...In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the regulation equipment,and the current of the shunt capacitor of the cables are not considered.In this paper,a multi-period two-stage robust scheduling strategy that aims to minimize the total cost of the power supply is developed.This strategy considers the time-ofuse price,the capability of the DGs to regulate the active and reactive power,the action costs of the regulation equipment,and the current of the shunt capacitors of the cables in a radial distribution system.Furthermore,the numbers of variables and constraints in the first-stage model remain constant during the iteration to enhance the computation efficiency.To solve the second-stage model,only the model of each period needs to be solved.Then,their objective values are accumulated,revealing that the computation rate using the proposed method is much higher than that of existing methods.The effectiveness of the proposed method is validated by actual 4-bus,IEEE 33-bus,and PG 69-bus distribution systems.展开更多
To optimize the placement of soft open points(SOPs)in active distribution networks(ADNs),many aspects should be considered,including the adjustment of transmission power,integration of distributed generations(DGs),coo...To optimize the placement of soft open points(SOPs)in active distribution networks(ADNs),many aspects should be considered,including the adjustment of transmission power,integration of distributed generations(DGs),coordination with conventional control methods,and maintenance of economic costs.To address this multi-objective planning problem,this study proposes a multi-stage coordinated robust optimization model for the SOP allocation in ADNs with photovoltaic(PV).First,two robust technical indices based on a robustness index are proposed to evaluate the operation conditions and robust optimality of the solutions.Second,the proposed coordinated allocation model aims to optimize the total cost,robust voltage offset index,robust utilization index,and voltage collapse proximity index.Third,the optimization methods of the multiand single-objective models are coordinated to solve the proposed multi-stage problem.Finally,the proposed model is implemented on an IEEE 33-node distribution system to verify its effectiveness.Numerical results show that the proposed index can better reveal voltage offset conditions as well as the SOP utilization,and the proposed model outperforms conventional ones in terms of robustness of placement plans and total cost.展开更多
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supported by the National Natural Science Foundation of China(51872115,12234018 and 52101256)Beijing Synchrotron Radiation Facility(BSRF,4B9A)。
文摘Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and charge distribution by introducing relatively weak electronegative atoms into the first/second shell is an efficient way,but it remains challenging for elucidating the underlying mechanism of interaction.Herein,a practical strategy was reported to rationally design single cobalt atoms coordinated with both phosphorus and nitrogen atoms in a hierarchically porous carbon derived from metal-organic frameworks.X-ray absorption spectrum reveals that atomically dispersed Co sites are coordinated with four N atoms in the first shell and varying numbers of P atoms in the second shell(denoted as Co-N/P-C).The prepared catalyst exhibits excellent oxygen reduction reaction(ORR)activity as well as zinc-air battery performance.The introduction of P atoms in the Co-SACs weakens the interaction between Co and N,significantly promoting the adsorption process of ^(*)OOH,resulting in the acceleration of reaction kinetics and reduction of thermodynamic barrier,responsible for the increased intrinsic activity.Our discovery provides insights into an ultimate design of single-atom catalysts with adjustable electrocatalytic activities for efficient electrochemical energy conversion.
基金Project(61725306)supported by the National Science Foundation for Distinguished Young Scholars of ChinaProjects(61473318,61403136,61703157,61751312)supported by the National Natural Science Foundation of ChinaProject(16C0940)supported by Foundation of Hunan Educational Committee,China
文摘Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.
基金supported by the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network (XTCX202001)National Natural Science Foundation of China (52077061)。
文摘In an integrated energy system(IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other subsystems.The energy supply should be globally optimized during the IES energy supply restoration process to produce the highest restoration net income. Mobile emergency sources can be quickly and flexibly connected to supply energy after an energy outage to ensure a reliable supply to the system, which adds complexity to the decision. This study focuses on a powergas IES with mobile emergency sources and analyzes the coupling relationship between the gas distribution system and the power distribution system in terms of sources, networks, and loads, and the influence of mobile emergency source transportation. The influence of the transient process caused by the restoration operation of the gas distribution system on the power distribution system is also discussed. An optimization model for power-gas IES restoration was established with the objective of maximizing the net income. The coordinated restoration optimization decision-making process was also built to realize the decoupling iteration of the power-gas IES, including system status recognition, mobile emergency source dispatching optimization, gas-to-power gas flow optimization, and parallel intra-partition restoration scheme optimization for both the power and gas distribution systems. A simulation test power-gas IES consisting of an 81-node medium-voltage power distribution network, an 89-node medium-pressure gas distribution network, and four mobile emergency sources was constructed. The simulation analysis verified the efficiency of the proposed coordinated restoration optimization method.
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
基金This work was supported by the Provincial Natural Science Foundation of Hunan(No.04JJ6033) the Research Foundation of Hunan Education Bureau (No.03C066).
文摘A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.
基金supported in part by the National Natural Science Foundation of China(62203126)the Science and Technology Plan Project of Guangdong Province(2023A0505010014)+1 种基金the Innovation and Technology Commission of the HKSAR Government under the InnoHK Initiative,and in part by the Key Areas R&D Program of Dongguan City(20201200300062)the GDAS’Project of Science and Technology Development(2022GDASZH-2022010108).
文摘Inspired by Model Predictive Interaction Control(MPIC),this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid-soft heterogeneous contact tasks.Within the MPIC,robot dynamics are linearized,and Extended Kalman Filters are used for the online estimation of geometry-aware parameters.Meanwhile,a geometry-aware Hertz contact model is introduced for the online estimation of contact forces.We then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization MPC.Experimental validations were designed for two contact modes:“single-point contact”and“continuous contact”,involving materials with four different Young’s moduli and tested in human arm“relaxation-contraction”task.Results indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee safety.Our method reduces the maximum impact force by 50%and decreases the average force error by 42%.The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid,soft,and deformable objects.
基金supported financially by InnerMongoliaKey Lab of Electrical Power Conversion,Transmission,and Control under Grant IMEECTC2022001the S&TMajor Project of Inner Mongolia Autonomous Region in China(2021ZD0040).
文摘Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.
基金supported by the National Natural Science Foundation of China (No. 21407021)the Shanghai Yang-Fan Program of Science and Technology Commission of Shanghai (No. 14YF1405000)+1 种基金the National Key Research and Development Program of China (No. 2016YFC0400501)the Fundamental Research Funds for the Central Universities and DHU Distinguished Young Professor Program
文摘Chitosan–metal complexes have been widely studied in wastewater treatment, but there are still various factors in complex preparation which are collectively responsible for improving the adsorption capacity need to be further studied. Thus, this study investigates the factors affecting the adsorption ability of chitosan–metal complex adsorbents, including various kinds of metal centers, different metal salts and crosslinking degree. The results show that the chitosan–Fe（ Ⅲ） complex prepared by sulfate salts exhibited the best adsorption efficiency（100%） for various dyes in very short time duration（10 min）, and its maximum adsorption capacity achieved 349.22 mg/g. The anion of the metal salt which was used in preparation played an important role to enhance the adsorption ability of chitosan–metal complex. SO4^（2-） ions not only had the effect of crosslinking through electrostatic interaction with amine group of chitosan polymer, but also could facilitate the chelation of metal ions with chitosan polymer during the synthesis process.Additionally, the p H sensitivity and the sensitivity of ionic environment for chitosan–metal complex were analyzed. We hope that these factors affecting the adsorption of the chitosan–metal complex can help not only in optimizing its use but also in designing new chitosan–metal based complexes.
基金supported by the National Key Research and Development Program(2016YFB0900100)。
文摘Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.
基金Nantong Research Program of Application Foundation,China(No.BK2012030)Key Project of Science and Technology Commission of Shanghai Municipality,China(No.10JC1405000)
文摘Temperature prediction plays an important role in ring die granulator control,which can influence the quantity and quality of production. Temperature prediction modeling is a complicated problem with its MIMO, nonlinear, and large time-delay characteristics. Support vector machine( SVM) has been successfully based on small data. But its accuracy is not high,in contrast,if the number of data and dimension of feature increase,the training time of model will increase dramatically. In this paper,a linear SVM was applied combing with cyclic coordinate descent( CCD) to solving big data regression. It was mathematically strictly proved and validated by simulation. Meanwhile,real data were conducted to prove the linear SVM model's effect. Compared with other methods for big data in simulation, this algorithm has apparent advantage not only in fast modeling but also in high fitness.
基金supported by the National Key R&D Program(No.2020YFB0905900)the National Natural Science Foundation of China(No.52277098)。
文摘Regional integrated energy system(RIES)cluster,i.e.,multi-source integration and multi-region coordination,is an effective approach for increasing energy utilization efficiency.The hierarchical architecture and limited information sharing of RIES cluster make it difficult for traditional game theory to accurately describe their game behavior.Thus,a hierarchical game approach considering bounded rationality is proposed in this paper to balance the interests of optimizing RIES cluster under privacy protection.A Stackelberg game with the cluster operator(CO)as the leader and multiple RIES as followers is developed to simultaneously optimize leader benefit and RIES utilization efficiency.Concurrently,a slight altruistic function is introduced to simulate the game behavior of each RIES agent on whether to cooperate or not.By introducing an evolutionary game based on bounded rationality in the lower layer,the flaw of the assumption that participants are completely rational can be avoided.Specially,for autonomous optimal dispatching,each RIES is treated as a prosumer,fexibly switching its market participation role to achieve cluster coordination optimization.Case studies on a RIES cluster verify effectiveness of the proposed approach.
基金National Natural Science Foundations of China(Nos.60872073,51075068,60975017,61301219)Doctoral Fund of Ministry of Education,China(No.20110092130004)
文摘Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.
基金supported by the National Natural Science Foundation of China (10377014)the Innovation Foundation of Northwestern Polytechnical university (2007KJ01027)
文摘The coordinated Bayesian optimization algorithm（CBOA） is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure（ECM） and the firepower attack systems.The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome.Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations,but also maintain the population multiplicity,and enhance the algorithm performance.The simulation result confirms the algorithm validity.
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.52107107).
文摘As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(No.2024B1515250007 and No.2023A1515240075)the Key Research and Development Project of Guang-dong Province(No.2021B0101230004).
文摘A mismatch between the rapid growth of grid-connected offshore wind farms(OWFs)and the de-lay of onshore transmission expansion(OTE)planning has caused significant wind curtailment in power systems.To alleviate this problem,a coordinated planning(CP)model of multiple inner networks of OWFs(INOWFs)and OTE is established in this paper.In the proposed CP model,the explicit connection topology constraints of a new double-sided ring topology for INOWFs are defined,and the connection topologies and electrical components of both INOWFs and OTE are coordinately optimized.In addition,a parallel random search method is proposed to obtain the set of feasible connection topology schemes of each INOWF,which can contract the feasible region of the CP model and reduce the difficulty in obtaining the optimal solution.Finally,a decomposition and coordina-tion planning algorithm is developed to decompose the original complex optimization model into two tractable sub-models for INOWF and OTE planning.This ap-proach efficiently obtains the optimal CP scheme for multiple INOWFs and OTE through alternating itera-tions.Case studies on the modified IEEE 39-bus system with two OWFs and an actual provincial power system with six OWFs demonstrate the correctness and efficiency of the proposed model and algorithm.
文摘The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry.Therefore,it is extremely urgent to transform energy production methods and vigorously develop renewable energy sources.It is therefore important to ensure the stability and operation of a large multi-energy complementary system,and provide theoretical support for the world’s largest single complementary demonstration project with hydro-wind-PV power-battery storage in Qinghai Province.Considering all the multiple power supply constraints,an optimization scheduling model is established with the objective of minimizing the volatility of output power.As particle swarm optimization(PSO)has a problem of premature convergence and slow convergence in the latter half,combined with niche technology in evolution,a niche particle swarm optimization(NPSO)is proposed to determine the optimal solution of the model.Finally,the multiple stations’coordinated operation is analyzed taking the example of 10 million kilowatt complementary power stations with hydropower,wind power,PV power,and battery storage in the Yellow River Company Hainan prefecture.The case verifies the rationality and feasibility of the model.It shows that complementary operations can improve the utilization rate of renewable energy and reduce the impact of wind and PV power’s volatility on the power grid.
基金the NationalNatural Science Foundation of China under Grant No.51577174.
文摘Currently, the power electronics-based devices, includinglarge-scale non-synchronized generators and reactivepower compensators, are widely used in power grids. This helpsintroduce the coupling interactions between the devices andthe power grid, resulting in a new sub-synchronous oscillationphenomenon. It is a critical element for the stability operation ofthe power grid and its devices. In this paper, the sub-synchronousoscillation phenomenon of the power grid connected with largescalewind power generation is analyzed in detail. Then, inorder to damp the sub-synchronous oscillation, a coordinateddamping optimization control strategy for wind power generatorsand their reactive power compensators is proposed. The proposedcoordinated control strategy tracks the sub-synchronousoscillation current signal to correct the corresponding controlsignal, which increases the damping of power electronics. Theresponse characteristics of the proposed control strategy areanalyzed, and a self-optimization parameter tuning method basedon sensitivity analysis is proposed. The simulation results validatethe effectiveness and the availability of the proposed controlstrategy.
基金supported in part by the Fundamental Research Funds for the Central Universities of China(No.PA2021GDSK0083)in part by the State Key Program of National Natural Science of China(No.51637004)in part by the National Key Research and Development Plan“Important Scientific Instruments and Equipment Development”(No.2016YFF0102200)。
文摘In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the regulation equipment,and the current of the shunt capacitor of the cables are not considered.In this paper,a multi-period two-stage robust scheduling strategy that aims to minimize the total cost of the power supply is developed.This strategy considers the time-ofuse price,the capability of the DGs to regulate the active and reactive power,the action costs of the regulation equipment,and the current of the shunt capacitors of the cables in a radial distribution system.Furthermore,the numbers of variables and constraints in the first-stage model remain constant during the iteration to enhance the computation efficiency.To solve the second-stage model,only the model of each period needs to be solved.Then,their objective values are accumulated,revealing that the computation rate using the proposed method is much higher than that of existing methods.The effectiveness of the proposed method is validated by actual 4-bus,IEEE 33-bus,and PG 69-bus distribution systems.
基金supported in part by the National Natural Science Foundation of China(General Program)(No.52077017)the International Postdoctoral Exchange Fellowship Program(Talent-Introduction Program)(No.YJ20210337)。
文摘To optimize the placement of soft open points(SOPs)in active distribution networks(ADNs),many aspects should be considered,including the adjustment of transmission power,integration of distributed generations(DGs),coordination with conventional control methods,and maintenance of economic costs.To address this multi-objective planning problem,this study proposes a multi-stage coordinated robust optimization model for the SOP allocation in ADNs with photovoltaic(PV).First,two robust technical indices based on a robustness index are proposed to evaluate the operation conditions and robust optimality of the solutions.Second,the proposed coordinated allocation model aims to optimize the total cost,robust voltage offset index,robust utilization index,and voltage collapse proximity index.Third,the optimization methods of the multiand single-objective models are coordinated to solve the proposed multi-stage problem.Finally,the proposed model is implemented on an IEEE 33-node distribution system to verify its effectiveness.Numerical results show that the proposed index can better reveal voltage offset conditions as well as the SOP utilization,and the proposed model outperforms conventional ones in terms of robustness of placement plans and total cost.
