The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-obj...The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.展开更多
In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this stud...In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.展开更多
The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting obj...The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.展开更多
Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into p...Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.展开更多
Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the...Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.展开更多
Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the sched...Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.展开更多
为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束...为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。展开更多
为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统...为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统电压-无功特性,建立直流电流、SVG无功输出与换相电压的耦合数学模型,推导得到SVG与VDCOL共同作用抑制换相失败存在参数可行域;进而,考虑换相失败恢复过程,提出二者协同时多馈入后续换相失败的临界电压指标,指导优化过程;然后,综合所提指标及系统有功传输、无功补偿力度设置奖励函数,并利用深度确定性策略梯度算法自适应求解最优参数组合。最后,仿真验证了所提策略能够有效抑制多直流输电系统的后续换相失败。展开更多
基金Projects(51005115, 51005248) supported by the National Natural Science Foundation of ChinaProject(SKLMT-KFKT-201105)supported by the Visiting Scholar Foundation of State Key Laboratory of Mechanical Transmission in Chongqing University, ChinaProject(QC201101) supported by Visiting Scholar Foundation of the Automobile Engineering Key Laboratory of Jiangsu Province, China
文摘The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.
基金Supported by China Postdoctoral Science Foundation(20090460873)
文摘In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.
基金Projects(61105067,61174164)supported by the National Natural Science Foundation of China
文摘The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
文摘Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.
基金Projects(51908388,51508315,51905320)supported by the National Natural Science Foundation of ChinaProject(2019 JZZY 010911)supported by the Key R&D Program of Shandong Province,China+1 种基金Project supported by the Shandong University of Technology&Zibo City Integration Develo pment Project,ChinaProject(ZR 2021 MG 012)supported by Shandong Provincial Natural Science Foundation,China。
文摘Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.
基金supported by the National Natural Science Foundation of China(7180121871701067+3 种基金72071075)the Research Project of National University of Defense Technology(ZK18-03-16)the Natural Science Foundation of Hunan Province,China(2020JJ46722019JJ50039)。
文摘Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.
文摘为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。
文摘随着配电网中分布式光伏(distributed photovoltaic,DPV)大量并网,电压越限和电压波动越来越严重,考虑新型电能质量治理装置的电压无功优化协调控制方法需要进一步完善,以适应电网的新变化。该文考虑了新型柔性有载调压变压器(on-load tap changer,OLTC)的电能质量调节作用,提出一种两阶段电压无功优化协调控制方法,其中一阶段为日前小时级调度阶段,根据分布式光伏和负荷的预测数据,通过潮流计算和迭代优化,获取DPV的有功出力结果、柔性OLTC分接头和电容器组的投切结果;二阶段为分钟级无功优化阶段,在第一阶段的基础上,考虑柔性OLTC和DPV的无功出力特性,调节装备无功出力的同时修正第一阶段电容器组投切组合,进一步降低各个节点最大电压偏差,使配电网电压分布更合理。搭建了IEEE33节点配电系统仿真模型,所提出的考虑柔性OLTC的两阶段电压无功优化协调控制方法能够在常规经济性最优目标下的88.07%DPV消纳水平基础上提高9.29%,同时满足全节点全时段电压偏差小于0.1pu,综合经济性提高7.8%,结果证明了所提方法的合理性和有效性。
文摘为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统电压-无功特性,建立直流电流、SVG无功输出与换相电压的耦合数学模型,推导得到SVG与VDCOL共同作用抑制换相失败存在参数可行域;进而,考虑换相失败恢复过程,提出二者协同时多馈入后续换相失败的临界电压指标,指导优化过程;然后,综合所提指标及系统有功传输、无功补偿力度设置奖励函数,并利用深度确定性策略梯度算法自适应求解最优参数组合。最后,仿真验证了所提策略能够有效抑制多直流输电系统的后续换相失败。
