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Hierarchical Coordinated Optimization Control Strategy for Electricity-Hydrogen DC Microgrid System 认领 引用
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作者 Xinhao Lin Lei Yu +4 位作者 Shuyin Duan Yinliang Liu Lvzerui Yuan Xiao Chen Yiqing Lian 《Energy Engineering》 EI 2026年第6期247-269,共23页
To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids,this paper proposes a hierarchical coordinated optimization control strategy for electricit... To address the operational challenges posed by renewable energy generation uncertainty and load fluctuations in DC microgrids,this paper proposes a hierarchical coordinated optimization control strategy for electricity-hydrogen hybrid DC microgrids(EH-DC-MG).The strategy aims to leverage the synergistic advantages of hybrid electricity-hydrogen energy storage to simultaneously achieve multiple objectives,including economic system operation,efficient utilization of renewable energy,and reliable power supply.The upper optimization scheduling layer formulates a mixed-integer linear programming model with the objective of minimizing the total system cost,which incorporates equipment operation and maintenance expenses,battery depreciation,penalties for renewable energy curtailment,and power/hydrogen supply shortages.By solving this model,optimal power reference signals are generated for devices.The lower device control layer employs designed DC/DC converter control strategies to ensure fast and accurate tracking of the optimization commands while maintaining DC bus voltage stability.Simulation results demonstrate that the proposed strategy can effectively coordinate electricity-hydrogen energy conversion and storage.Under various typical and extreme scenarios,the system maintains a high renewable energy utilization rate—remaining above 97.572%even under extreme conditions—while keeping the power shortage rate and hydrogen load curtailment rate at low levels.Specifically,under extreme power deficit scenarios,these rates are limited to 2.003%and 5.081%,respectively,which are significantly below the 10%quality constraint threshold,thereby ensuring a high degree of supply reliability.In addition,the DC bus voltage fluctuation is stabilized within 0.37%,far below the 5%safety operation threshold,validating the effectiveness of the control strategy.This study confirms that the proposed hierarchical coordinated optimization control strategy can support electricity-hydrogen hybrid DC microgrids in achieving economical,reliable,and resilient operation,providing a key technical reference for the optimized management of microgrids with high penetration of renewable energy. 展开更多
关键词 Electric-hydrogen DC microgrid coordinated optimization control strategy
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Bi-level Coordinated Scheduling and Optimization of Power Systems Based on Stackelberg-GMO 认领 引用
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作者 Zhang Yuanxing Li Jianfeng +3 位作者 Li Taoyong Zhang Linjuan Liu Jincheng Li Bin 《系统仿真学报》 EI CAS CSCD 北大核心 2026年第8期2132-2151,共20页
,To balance the interests of the power grid and the demand side,and achieve coordinated improvements in system economic efficiency,environmental friendliness,and renewable energy accommodation capacity,this paper prop... ,To balance the interests of the power grid and the demand side,and achieve coordinated improvements in system economic efficiency,environmental friendliness,and renewable energy accommodation capacity,this paper proposes a bi-level coordinated scheduling model based on the Stackelberg game and the GMO.A leader-follower game model incorporating carbon emission constraints and multi-scenario stochastic constraints for photovoltaic generation is constructed,with the grid operator as the leader and EVs/V2G and energy storage as the followers,resolving the core contradiction between global optimization and individual rationality.The spatio-temporal stochastic characteristics of EV travel,the cycle life of energy storage systems,and user travel comfort constraints are carefully incorporated to reduce the deviation between the model and actual operation.The GMO algorithm is closely adapted to the sequential decision-making logic of the Stackelberg game,and a dedicated solution framework is designedto reliably obtain a SPNE.A virtual electricity price incentive mechanism integrating carbon emission costs and curtailment penalties is designed to guide demand-side resources to match the output characteristics of renewable energy.Results show that the optimization performance of the GMO algorithm is significantly superior to that of the PSO and the GA.Compared with the traditional uncoordinated operation mode,the proposed scheme reduces the total operating cost by up to 50.25%,increases the photovoltaic power accommodation rate to 96.5%,and reduces carbon emissions by up to 51.46%.This research can serve as a theoretical and engineering reference for the coordinated scheduling of flexible resources in new-type power systems. 展开更多
关键词 new-type power system coordinated scheduling Stackelberg game geometric mean optimizer demand response electric vehicle
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Optimization and Scheduling of Green Power System Consumption Based on Multi-Device Coordination and Multi-Objective Optimization 认领 引用 被引量：1
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作者 Liang Tang Hongwei Wang +2 位作者 Xinyuan Zhu Jiying Liu Kaiyue Li 《Energy Engineering》 EI 2025年第6期2257-2289,共33页
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
关键词 Multi-objective optimization scheduling model multi-objective particle swarm optimization algorithm consumption capacity of green power wind and solar curtailment coordinated optimization of multiple devices
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Integrated optimization and coordination of cascaded reservoir operations:Balancing flood control,sediment transport and ecosystem service 认领 引用
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作者 Xinmiao Cao Teng Lin +1 位作者 Jiahui Li Ting Zhou 《River》 EI CSCD 2025年第1期55-69,共15页
Exploring optimal operational schemes for synergistic development is crucial for sustainable management in river basins.This study introduces a multi-objective synergistic optimization framework aimed at analyzing the... Exploring optimal operational schemes for synergistic development is crucial for sustainable management in river basins.This study introduces a multi-objective synergistic optimization framework aimed at analyzing the interplay among flood control,ecological integrity,and desilting objectives under varying watersediment conditions.The framework encompasses multi-objective reservoir optimal operation,scheme decision,and trade-off analysis among competing objectives.To address the optimization model,an elite mutation-based multiobjective particle swarm optimization(MOPSO)algorithm that integrates genetic algorithms(GA)is developed.The coupling coordination degree is employed for optimal scheme decision-making,allowing for the adjustment of weight ratios to investigate the trade-offs between objectives.This research focuses on the Sanmenxia and Xiaolangdi cascade reservoirs in the Yellow River,utilizing three representative hydrological years:1967,1969,and 2002.The findings reveal that:(1)the proposed model effectively generates Pareto fronts for multi-objective operations,facilitating the recommendation of optimal schemes based on coupling coordination degrees;(2)as water-sediment conditions shift from flooding to drought,competition intensifies between the flood control and desilting objectives.While flood control and ecological objectives compete during flood and dry years,they demonstrate synergies in normal years(r=0.22);conversely,ecological and desilting objectives are consistently competitive across all three typical years,with the strongest competition observed in the normal year(r=-0.95);(3)the advantages conferred to ecological objectives increase as water-sediment conditions shift from flooding to drought.However,the promotion of the desilting objective requires more complex trade-offs.This study provides a model and methodological approach for the multi-objective optimization of flood control,sediment management,and ecological considerations in reservoir clusters.Moreover,the methodologies presented herein can be extended to other water resource systems for multi-objective optimization and decision-making. 展开更多
关键词 coupling coordination flood and sediment transport multi-objective reservoir optimization Pareto front Yellow River basin
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Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy 认领 引用 被引量：23
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作者 Yingxun WANG Tian ZHANG +2 位作者 Zhihao CAI Jiang ZHAO Kun WU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第11期2877-2897,共21页
The paper proposes a new swarm intelligence-based distributed Model Predictive Control(MPC)approach for coordination control of multiple Unmanned Aerial Vehicles(UAVs).First,a distributed MPC framework is designed and... The paper proposes a new swarm intelligence-based distributed Model Predictive Control(MPC)approach for coordination control of multiple Unmanned Aerial Vehicles(UAVs).First,a distributed MPC framework is designed and each member only shares the information with neighbors.The Chaotic Grey Wolf Optimization(CGWO)method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem(FHOCP).Then,the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint.Further,an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach,which considers the predicted state errors and the convergence of cost function.Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method. 展开更多
关键词 Chaotic Grey Wolf Optimization(CGWO) Coordination control Distributed Model Predictive Control(MPC) Event-triggered strategy Multi-UAV
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Coordinated restoration optimization of power-gas integrated energy system with mobile emergency sources 认领 引用 被引量：6
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作者 Lili Hao Wangyu Hu +4 位作者 Chuan Wang Guangzong Wang Yue Sun Jun Chen Xueping Pan 《Global Energy Interconnection》 EI CSCD 2023年第2期205-227,共23页
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
关键词 Coordinated restoration optimization Integrated energy system Power-gas decoupling Gas-to-power flow optimization Mobile emergency source
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Optimizing high-coordination shell of Co-based single-atom catalysts for efficient ORR and zinc-air batteries 认领 引用 被引量：6
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作者 Yugang Qi Qing Liang +9 位作者 Kexin Song Xinyan Zhou Meiqi Liu Wenwen Li Fuxi Liu Zhou Jiang Xu Zou Zhongjun Chen Wei Zhang Weitao Zheng 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第8期306-314,I0007,共9页
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
关键词 Electrocatalytic Oxygen reduction reaction Single atom catalyst Shell coordination optimization
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Coordinated optimization setting of reagent dosages in roughing-scavenging process of antimony flotation 认领 引用 被引量：3
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作者 CAO Bin-fang XIE Yong-fang +2 位作者 GUI Wei-hua YANG Chun-hua LI Jian-qi 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第1期95-106,共12页
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
关键词 froth flotation image features optimization setting coordinated optimization
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Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model 认领 引用 被引量：5
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作者 王雅琳 马杰 +2 位作者 桂卫华 阳春华 张传福 《Journal of Central South University of Technology》 2006年第5期552-557,共6页
A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism a... A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability. 展开更多
关键词 Pb-Zn sintering blending process qualitative and quantitative synthetic model multi-objectiveoptimization area optimization intelligent coordination
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Coordinated Controller Tuning of a Boiler Turbine Unit with New Binary Particle Swarm Optimization Algorithm 认领 引用 被引量：2
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作者 Muhammad Ilyas Menhas Ling Wang +1 位作者 Min-Rui Fei Cheng-Xi Ma 《International Journal of Automation and computing》 2011年第2期185-192,共8页
Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system.In this paper,a new variant of binary particle swarm optimization （PSO） ... Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system.In this paper,a new variant of binary particle swarm optimization （PSO） algorithm,called probability based binary PSO （PBPSO）,is presented to tune the parameters of a coordinated controller.The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO,modified binary PSO,and standard continuous PSO. 展开更多
关键词 Coordinated control boiler turbine unit particle swarm optimization （PSO） probability based binary particle swarm optimization （PBPSO） controller tuning.
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Multi-objective coordination optimal model for new power intelligence center based on hybrid algorithm 认领 引用 被引量：1
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作者 刘吉成 牛东晓 乞建勋 《Journal of Central South University》 SCIE EI CAS 2009年第4期683-689,共7页
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
关键词 power intelligence center （PIC） coordination optimal model power network planning hybrid algorithm
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Incorporating delay propagation into decision-making for optimizing prefabricated building supply chain networks under uncertainty 认领 引用
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作者 Qiang DU Qian CHEN +3 位作者 Jing YANG Jiajie ZHOU Libiao BAI Xixi LUO 《ENGINEERING Management》 CSCD 2026年第2期363-385,共23页
Prefabricated buildings are crucial for the transformation of the construction industry,while the Prefabricated Building Supply Chain Network(PBSCN)that supports their implementation is subject to uncertainties in pro... Prefabricated buildings are crucial for the transformation of the construction industry,while the Prefabricated Building Supply Chain Network(PBSCN)that supports their implementation is subject to uncertainties in production,transportation,and installation.These uncertainties lead to schedule delays and cost increases,which significantly hinder the widespread adoption of prefabricated buildings.To address these issues,this paper develops a three-tier optimization model that integrates component factories,logistics providers,and contractors to improve resource allocation and reduce total costs.This model explicitly accounts for uncertainty-induced delay propagation across stages and incorporates its impacts into the decision-making process through work stoppage cost at the construction site.A Scenario-Based Stochastic Programming(SBSP)approach is employed to determine optimal decisions,while Monte Carlo Simulation(MCS)is utilized to generate representative scenarios.Furthermore,the proposed model is extended to incorporate a carbon trading mechanism to examine the interaction between environmental regulation and supply chain decisions.The model's effectiveness is validated through a hypothetical case adapted from a real-world project,in which the optimal solutions involved concentrating approximately 6%of orders in the baseline case and 33.0%35.5%in the largescale experiment.Results show that proactively accounting for uncertainties not only reduced costs but also strengthened coordination among entities to improve resource utilization.This paper provides practical decision support for PBSCN stakeholders,helping them mitigate risks,optimize order allocation,and improve overall supply chain performance in an uncertain environment. 展开更多
关键词 prefabricated buildings supply chain network coordination uncertainty management scenariobased stochastic programming cost optimization
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A Novel Multi-Objective Topology Optimization Method for Stiffness and Strength-Constrained Design Using the SIMP Approach 认领 引用 被引量：1
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作者 Jianchang Hou Zhanpeng Jiang +4 位作者 Fenghe Wu Hui Lian Zhaohua Wang Zijian Liu Weicheng Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第8期1545-1572,共28页
In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are reg... In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are regulated through sensitivity filtering tomitigate numerical instabilities associatedwith stress concentrations.Ap-norm aggregation function is employed to globalize local stress constraints,and a normalization technique linearly weights strain energy and stress,transforming the multi-objective problem into a single-objective formulation.The sensitivity of the objective function with respect to design variables is rigorously derived.Three numerical examples are presented,comparing the optimized structures in terms of strain energy,mass,and stress across five different mathematical models with varying combinations of optimization objectives.The results validate the effectiveness and feasibility of the proposed method for achieving a balanced design between structural stiffness and strength.This approach offers a new perspective for future research on stiffness-strength coordinated structural optimization. 展开更多
关键词 Topology optimization stiffness-strength coordination SIMP method stress constraints p-norm aggregation sensitivity analysis
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Multi-Objective optimization for stable and efficient cargo transportation of partial space elevator 认领 引用 被引量：1
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作者 Gefei Shi Zheng H.Zhu 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2025年第2期17-29,共13页
This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration s... This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function. 展开更多
关键词 Partial space elevator Stable transportation Libration decoupling analytical speed function Coordinate game Model predictive control Pareto optimization
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Arterial Coordinated Optimization with Time-of-Day Control in Urban Areas+ 认领 引用
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作者 YAO Jiao XU Jie-qiong NI Yi-ling 《Journal of Highway and Transportation Research and Development(English Edition)》 2018年第3期60-70,共11页
This study combined the coordinated control and time-of-day strategy to improve the stability and benefit cost ratio of the control strategy in the context of China's traffic condition.The coordination boundary wa... This study combined the coordinated control and time-of-day strategy to improve the stability and benefit cost ratio of the control strategy in the context of China's traffic condition.The coordination boundary was determined by the coordinatability model of intersections.The traffic volumes of intersections in the research area were dealt with the mixed clustering method to obtain the corresponding time-of-day strategies.On the basis of the previous study,the multiple-objective particle swarm optimization is used for the average delay to find the best switching time for time-of-day control.Relevant simulation indicates that when compared with current traffic control plans and mixed clustering optimization,the proposed strategy shows more advantages in termsof bandwidth of traffic control plan and delay optimization.After minimizing the disturbance caused by switching traffic control plans,the resulting decrement rate of average vehicle delay is 12.63%for the current traffic control plan and 2.45%for the mixed clustering optimization;the increasing bandwidth rates of the traffic control plan are 0.98%and 23.51%,respectively. 展开更多
关键词 traffic engineering coordinatability calculation model multi-objective particle swarm optimization algorithm(MOPSO) time-of-day coordinated control mixed clustering
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Real-Time Video Target Tracking via Geometric Coordinate Mapping 认领 引用
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作者 Na Li Yashu Zhang +4 位作者 Fengpu Lin Liutao Zhao Zhongshan Zhu Chen Tom Tengfei Tu 《Computers, Materials & Continua》 SCIE EI 2026年第9期1877-1895,共19页
Accurate mapping of video imagery to physical space coordinates represents a fundamental challenge in dynamic target tracking and intelligent video analysis systems.Traditional methods struggle to maintain stable coor... Accurate mapping of video imagery to physical space coordinates represents a fundamental challenge in dynamic target tracking and intelligent video analysis systems.Traditional methods struggle to maintain stable coordinate mapping in real-time video streams due to imaging distortion variations and changing environmental conditions.This paper presents a real-time coordinate mapping approach that integrates geometric constraints with online distortion correction to achieve stable pixel-to-target coordinate transformation for video target tracking applications.The proposed method introduces a planar geometric consistency constraint and an online distortion parameter update mechanism within a unified optimization framework,enabling adaptive adjustment of the mapping relationship under dynamic imaging conditions.Experimental results show that in static scenes,the root mean square error and mean absolute error of this method reach 1.16 and 0.77 mm,respectively,which are lower than those of deep learning regression methods.Under distortion conditions,the root mean square error remains stable at 0.22±0.02 px,and the distortion parameter error is approximately 2×10⁻³.In dynamic translation and rotational perturbation scenarios,the method still maintains low error and an accuracy of 84.5%.Furthermore,even with a feature point scale increased to 1000,the method still achieves real-time operation at 36 FPS with a count accuracy of 96.9%,validating its ability to support continuous tracking and counting of dynamic targets.This research contributes an engineering-feasible solution for real-time geometric coordinate mapping in video-based target tracking and intelligent monitoring applications. 展开更多
关键词 Video target tracking geometric coordinate mapping geometric constraints distortion correction online optimization real-time vision
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Complex coordinate rotation method based on gradient optimization 认领 引用
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作者 Zhi-Da Bai Zhen-Xiang Zhong +1 位作者 Zong-Chao Yan Ting-Yun Shi 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第2期257-261,共5页
In atomic,molecular,and nuclear physics,the method of complex coordinate rotation is a widely used theoretical tool for studying resonant states.Here,we propose a novel implementation of this method based on the gradi... In atomic,molecular,and nuclear physics,the method of complex coordinate rotation is a widely used theoretical tool for studying resonant states.Here,we propose a novel implementation of this method based on the gradient optimization(CCR-GO).The main strength of the CCR-GO method is that it does not require manual adjustment of optimization parameters in the wave function;instead,a mathematically well-defined optimization path can be followed.Our method is proven to be very efficient in searching resonant positions and widths over a variety of few-body atomic systems,and can significantly improve the accuracy of the results.As a special case,the CCR-GO method is equally capable of dealing with bound-state problems with high accuracy,which is traditionally achieved through the usual extreme conditions of energy itself. 展开更多
关键词 complex coordinate rotation method resonant state metastable state gradient optimization
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A Review of AI-Driven Optimization Technologies for Distributed Photovoltaic Power Generation Systems 认领 引用 被引量：1
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作者 Nanting Li 《Journal of Electronic Research and Application》 2025年第5期132-142,共11页
The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addre... The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addressing these core bottlenecks.This paper provides a systematic review of the research background,technological evolution,core systems,key challenges,and future directions of AI technology in the field of distributed photovoltaic power generation system optimization.At the same time,this paper analyzes the current technical bottlenecks and cutting-edge response strategies.Finally,it explores fusion innovation directions such as quantum-classical hybrid algorithms and neural symbolic systems,as well as business model expansion paths such as carbon finance integration and community energy autonomy. 展开更多
关键词 AI optimization Distributed photovoltaic systems Virtual power plant coordination Community energy autonomy
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Application of Evolutionary Algorithm for Optimal Directional Overcurrent Relay Coordination 认领 引用 被引量：1
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作者 N. M. Stenane K. A. Folly 《Journal of Computer and Communications》 2014年第9期103-111,共9页
In this paper, two Evolutionary Algorithms (EAs) i.e., an improved Genetic Algorithms (GAs) and Population Based Incremental Learning (PBIL) algorithm are applied for optimal coordination of directional overcurrent re... In this paper, two Evolutionary Algorithms (EAs) i.e., an improved Genetic Algorithms (GAs) and Population Based Incremental Learning (PBIL) algorithm are applied for optimal coordination of directional overcurrent relays in an interconnected power system network. The problem of coordinating directional overcurrent relays is formulated as an optimization problem that is solved via the improved GAs and PBIL. The simulation results obtained using the improved GAs are compared with those obtained using PBIL. The results show that the improved GA proposed in this paper performs better than PBIL. 展开更多
关键词 Evolutionary Algorithms GA Learning Rate Optimal Relay Coordination PBIL
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A New Design of Robust H∞Load-Frequency Controller for Optimal Coordination of Energy Generation in Power System Stability Using LMI Approach 认领 引用 被引量：1
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作者 Chamni Jaipradidtham Chatchai U-thaiwasin 《Journal of Power and Energy Engineering》 2015年第4期146-154,共9页
This paper presents the problem of robust H&infin;?load frequency controller design and robust H￥ based approach called advanced frequency control (AFC). The objective is to split the task of balancing frequency ... This paper presents the problem of robust H&infin;?load frequency controller design and robust H￥ based approach called advanced frequency control (AFC). The objective is to split the task of balancing frequency deviations introduced by renewable energy source (RES) and load variations according to the capabilities of storage and generators. The problem we address is to design an output feedback controller such that, all admissible parameter uncertainties, the closed-loop system satisfies not only the prespecified H&infin;? norm constraint on the transfer function from the disturbance input to the system output. The conventional generators mainly balance the low-frequency components and load variations while the energy storage devices compensate the high- frequency components. In order to enable the controller design for storage devices located at buses with no generators, a model for the frequency at such a bus is developed. Then, AEC controllers are synthesized through decentralized static output feedback to reduce the complexity. The conditions for the existence of desired controllers are derived in terms of a linear matrix inequality (LMI) algorithm is improved. From the simulation results, the system responses with the proposed controller are the best transient responses. 展开更多
关键词 Optimal Coordination Robust H∞ Controller Load Frequency Control LMI Approach
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