在电池管理系统中为了使荷电状态量SOC(state of charge)估计精确,提出以遗传算法优化最小二乘支持向量机(LS-SVM)的方法对电池的SOC进行预测的模型。在电池变流情况下对SOC进行研究,以标准工况下的实验数据作为样本,以电池的电流、电...在电池管理系统中为了使荷电状态量SOC(state of charge)估计精确,提出以遗传算法优化最小二乘支持向量机(LS-SVM)的方法对电池的SOC进行预测的模型。在电池变流情况下对SOC进行研究,以标准工况下的实验数据作为样本,以电池的电流、电压及温度作为训练模型的输入,SOC作为输出建立模型,使之能很好地适用于混合动力汽车用电池在变电流状态下的实时SOC估计。研究结果表明:该预测模型预测精度高,其最大相对误差小于3%,平均相对误差小于2%,且与神经网络预测结果相比具有更强的实用性。展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
In order to coordinate automatic voltage control (AVC) systems of a large interconnected system, a multi-level multi-area hybrid automatic voltage control (MLMA-HAVC) system was constructed. This system began its ...In order to coordinate automatic voltage control (AVC) systems of a large interconnected system, a multi-level multi-area hybrid automatic voltage control (MLMA-HAVC) system was constructed. This system began its trial operation in the Northeast China Grid in January 2010, and for the first time in China and abroad it realized automatic close-loop control of multi-area and multi-level interconnected power grid and multi-objective self-approaching optimization in aspects of security, high quality and economic operation. This system has three breakthroughs in theory and engineering application: l) Established the MLMA-HAVC theory to solve multi-objective optimization of large-scale system; 2) proposed reactive power/voltage coordination control method to inhibit or further eliminate regional oscillations; 3) presented advanced state estimation algorithm to guarantee acquisition of high reliability data. This paper summarizes the basic principle of MLMA-HAVC, and reports engineering realization of MI ,MA-HAVC system in tha Northeast China Grid.展开更多
Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required fo...Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.展开更多
The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note tha...The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be updated.As such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states possible.However,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 s.In this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local states.Moreover,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring recalculation.In particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE problem.The timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems.展开更多
作为大规模储能系统的重要组成,混合型超级电容器的荷电状态(state of charge,SOC)估计是能量管理系统必不可少的部分。该文提出一种基于动态容值修正的超级电容器SOC预估方法。首先,利用参数辨识方法求解超级电容器实时电动势,定义不...作为大规模储能系统的重要组成,混合型超级电容器的荷电状态(state of charge,SOC)估计是能量管理系统必不可少的部分。该文提出一种基于动态容值修正的超级电容器SOC预估方法。首先,利用参数辨识方法求解超级电容器实时电动势,定义不同初始电压放电至相同终止电压的容值为动态容值。其次,设计不同温度、不同电流倍率的实验得到超级电容器不同工况下特性。再次,建立基于动态容值修正的全工况预测模型,修正电动势归一化和电荷再分配现象导致的SOC估计的误差。最后,通过多个温度下的随机变电流放电实验数据,将基于动态容值修正的SOC估计值和电流Ah积分法得到的SOC参考值进行对比,证明该SOC估计方法的准确性。展开更多
文摘在电池管理系统中为了使荷电状态量SOC(state of charge)估计精确,提出以遗传算法优化最小二乘支持向量机(LS-SVM)的方法对电池的SOC进行预测的模型。在电池变流情况下对SOC进行研究,以标准工况下的实验数据作为样本,以电池的电流、电压及温度作为训练模型的输入,SOC作为输出建立模型,使之能很好地适用于混合动力汽车用电池在变电流状态下的实时SOC估计。研究结果表明:该预测模型预测精度高,其最大相对误差小于3%,平均相对误差小于2%,且与神经网络预测结果相比具有更强的实用性。
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金supported by the Science and Technology Project of Northeast China Grid Company(Grant No.2009ZB1048)the National Natural Science Foundation of China(Grant Nos.50907038,50977047)
文摘In order to coordinate automatic voltage control (AVC) systems of a large interconnected system, a multi-level multi-area hybrid automatic voltage control (MLMA-HAVC) system was constructed. This system began its trial operation in the Northeast China Grid in January 2010, and for the first time in China and abroad it realized automatic close-loop control of multi-area and multi-level interconnected power grid and multi-objective self-approaching optimization in aspects of security, high quality and economic operation. This system has three breakthroughs in theory and engineering application: l) Established the MLMA-HAVC theory to solve multi-objective optimization of large-scale system; 2) proposed reactive power/voltage coordination control method to inhibit or further eliminate regional oscillations; 3) presented advanced state estimation algorithm to guarantee acquisition of high reliability data. This paper summarizes the basic principle of MLMA-HAVC, and reports engineering realization of MI ,MA-HAVC system in tha Northeast China Grid.
文摘Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.
基金supported by the National Key Research and Development Program of China under Grant 2018YFB0904500。
文摘The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be updated.As such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states possible.However,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 s.In this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local states.Moreover,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring recalculation.In particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE problem.The timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems.
文摘作为大规模储能系统的重要组成,混合型超级电容器的荷电状态(state of charge,SOC)估计是能量管理系统必不可少的部分。该文提出一种基于动态容值修正的超级电容器SOC预估方法。首先,利用参数辨识方法求解超级电容器实时电动势,定义不同初始电压放电至相同终止电压的容值为动态容值。其次,设计不同温度、不同电流倍率的实验得到超级电容器不同工况下特性。再次,建立基于动态容值修正的全工况预测模型,修正电动势归一化和电荷再分配现象导致的SOC估计的误差。最后,通过多个温度下的随机变电流放电实验数据,将基于动态容值修正的SOC估计值和电流Ah积分法得到的SOC参考值进行对比,证明该SOC估计方法的准确性。