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油纸绝缘扩展德拜等效模型时域微分法峰值特性分析
期刊论文 | 2025 , 44 (1) , 128-134 | 电气应用
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Abstract :

针对变压器油纸绝缘扩展德拜模型时域微分法存在的峰值覆盖现象,导致无法准确判断模型弛豫支路数,首先推导出去极化电流函数的n次微分形式,并通过两条微分子谱线研究微分法峰值覆盖因素;然后计算前一条微分谱线在后一条微分谱线峰值点的比例,作为微分子谱线一对微分子谱线二峰值点影响程度,同理计算谱线二对谱线一峰值点影响程度;接着研究弛豫贡献度与微分次数对微分谱线峰值覆盖的影响;最后通过仿真验证了弛豫贡献度越大,其子谱线峰值点越明显,相邻两个子谱线峰值点越容易被其覆盖,微分次数越高,各微分子谱线峰值点越明显.研究结果论证了峰值覆盖现象存在的原因,为后续有效降低峰值覆盖现象、准确可靠地判断变压器油纸绝缘扩展德拜弛豫支路数提供理论基础.

Keyword :

去极化电流 去极化电流 变压器 变压器 峰值点覆盖 峰值点覆盖 扩展德拜模型 扩展德拜模型 时域微分法 时域微分法 油纸绝缘 油纸绝缘

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GB/T 7714 汪洋洋 , 宋福根 , 刘庆珍 . 油纸绝缘扩展德拜等效模型时域微分法峰值特性分析 [J]. | 电气应用 , 2025 , 44 (1) : 128-134 .
MLA 汪洋洋 等. "油纸绝缘扩展德拜等效模型时域微分法峰值特性分析" . | 电气应用 44 . 1 (2025) : 128-134 .
APA 汪洋洋 , 宋福根 , 刘庆珍 . 油纸绝缘扩展德拜等效模型时域微分法峰值特性分析 . | 电气应用 , 2025 , 44 (1) , 128-134 .
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改进雪融优化器在多目标优化问题上的应用
期刊论文 | 2025 , 46 (6) , 1772-1779 | 计算机工程与设计
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针对雪融优化器(snow ablation optimizer,SAO)在求解部分复杂优化问题时存在的寻优效果不稳定、易陷入局部最优等缺陷,提出一种改进算法——改进雪融优化器(improved snow ablation optimizer,ISAO).该算法基于改进Tent混沌映射提高种群的多样性,引入折射镜像学习改善寻优方向,并结合莱维飞行策略与贪婪策略增强跳出局部最优的能力.同时,选取了 5种目前被广泛应用的智能优化算法作为对照组,在10个基准测试函数上和2个多目标优化问题上进行对比实验,其结果显示ISAO相比于SAO具备更强的优化性能.进一步地,将ISAO和SAO分别应用于实际的工程优化问题,其结果验证了 ISAO在解决实际工程优化问题上具有显著优势.

Keyword :

工程优化问题 工程优化问题 折射镜像学习 折射镜像学习 改进Tent混沌映射 改进Tent混沌映射 智能优化算法 智能优化算法 莱维飞行 莱维飞行 贪婪策略 贪婪策略 雪融优化器 雪融优化器

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GB/T 7714 周宇含 , 刘庆珍 . 改进雪融优化器在多目标优化问题上的应用 [J]. | 计算机工程与设计 , 2025 , 46 (6) : 1772-1779 .
MLA 周宇含 等. "改进雪融优化器在多目标优化问题上的应用" . | 计算机工程与设计 46 . 6 (2025) : 1772-1779 .
APA 周宇含 , 刘庆珍 . 改进雪融优化器在多目标优化问题上的应用 . | 计算机工程与设计 , 2025 , 46 (6) , 1772-1779 .
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Transformer oil insulation aging based on Raman spectral data processing and peak identification EI CSCD PKU
期刊论文 | 2024 , 52 (8) , 158-166 | Power System Protection and Control
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Abstract :

There are problems in that the Raman analysis of transformer oil is usually interfered with by noise and fluorescent background, and it is difficult to identify the position of the spectral peak. Thus this paper proposes an improved data processing and spectral peak recognition algorithm for the Raman analysis of transformer oil aging evaluation. An adaptive Savitzky-Golay filtering method is proposed, and adaptive window-size Raman spectral data is introduced for denoising. An improved polynomial fitting algorithm is used to remove the fluorescence background processing of the de-noised data to reduce its influence on the fitting results. Each data point is weighted according to the distance between the data point and the expected Raman signal, so as to achieve more accurate de-fluorescence background processing. The aging degree of transformer oil is identified by spectral peak recognition technology, and the spectral peak is identified by the Gaussian window discrimination method with two scales, and the authenticity of the suspected Raman spectral peak is judged by the local weighted signal-to-noise ratio (LW_SNR). Finally, the effectiveness of the proposed algorithm in transformer oil aging evaluation is proved by experiment. © 2024 Power System Protection and Control Press. All rights reserved.

Keyword :

Data handling Data handling Fluorescence Fluorescence Oil filled transformers Oil filled transformers Raman spectroscopy Raman spectroscopy Signal denoising Signal denoising Signal to noise ratio Signal to noise ratio Transformer protection Transformer protection

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GB/T 7714 Liu, Qingzhen , Zhang, Yi , Yan, Renwu . Transformer oil insulation aging based on Raman spectral data processing and peak identification [J]. | Power System Protection and Control , 2024 , 52 (8) : 158-166 .
MLA Liu, Qingzhen 等. "Transformer oil insulation aging based on Raman spectral data processing and peak identification" . | Power System Protection and Control 52 . 8 (2024) : 158-166 .
APA Liu, Qingzhen , Zhang, Yi , Yan, Renwu . Transformer oil insulation aging based on Raman spectral data processing and peak identification . | Power System Protection and Control , 2024 , 52 (8) , 158-166 .
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复合电压薄弱性指标及以其为导向的无功优化策略 CSCD PKU
期刊论文 | 2024 , 44 (1) , 147-152,159 | 电力自动化设备
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Abstract :

提出了一种新的电力系统薄弱环节确定指标,并提出以系统薄弱环节分析为导向的多目标函数无功优化方法.首先,融合薄弱性指标电压和功率两方面的特点和优势,定义了新的薄弱环节复合裕度判定指标,综合描述负荷正常工作点与电压崩溃点的距离;以该指标为判定标准识别出系统的电压薄弱环节点集,由此点集构成无功优化的待补偿节点集.然后,建立多目标无功优化模型,采用改进自适应遗传算法,在算法选择环节采用确定式选择原则替换传统轮盘赌法,进而完成多目标无功优化模型求解.最后,以IEEE 30节点系统和新英格兰IEEE 39节点系统为仿真试验案例,通过优化后多项系统运行指标与传统方法计算结果的对比,验证了以新的薄弱环节判定指标为无功优化策略的有效性和优越性,同时也证明了改进后的自适应遗传算法在多目标无功优化计算中的高效性.

Keyword :

复合裕度指标 复合裕度指标 多目标无功优化 多目标无功优化 确定式选择原则 确定式选择原则 自适应遗传算法 自适应遗传算法 薄弱环节 薄弱环节

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GB/T 7714 刘庆珍 , 黄君莹 , 王少芳 . 复合电压薄弱性指标及以其为导向的无功优化策略 [J]. | 电力自动化设备 , 2024 , 44 (1) : 147-152,159 .
MLA 刘庆珍 等. "复合电压薄弱性指标及以其为导向的无功优化策略" . | 电力自动化设备 44 . 1 (2024) : 147-152,159 .
APA 刘庆珍 , 黄君莹 , 王少芳 . 复合电压薄弱性指标及以其为导向的无功优化策略 . | 电力自动化设备 , 2024 , 44 (1) , 147-152,159 .
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Compounding voltage weakness indicator and reactive power optimization strategy oriented to it EI CSCD PKU
期刊论文 | 2024 , 44 (1) , 147-152 and 159 | Electric Power Automation Equipment
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A new weak link determination indicator of power system is proposed and a multi-objective function reactive power optimization method oriented to system weak link analysis is proposed. The characteristics and advantages of both voltage and power aspects of the weakness indicator are fused. A new weak link compounding margin determination indicator is defined,which comprehensively describes the distance between the load normal operating point and the voltage collapse point. This indicator can be used as the determination criterion to identify the voltage weak link point set of system,which constitutes the set of nodes to be compensated for reactive power optimization. A multi-objective reactive power optimization model is established,and an improved adaptive genetic algorithm is used to replace the traditional roulette wheel method with deterministic selection principle in the algorithm selection process,and then the multi-objective reactive power optimization model is solved. Taking the IEEE 30-bus system and the New England IEEE 39-bus system as simulative testing cases,by comparing several system operation indicators and the calculative results of traditional method,the efficiency and superiority of reactive power optimization strategy according to the new weak link determination indicator is verified,as well as the high efficiency of the improved adaptive genetic algorithm in the multi-objective reactive power optimization calculation is verified. © 2024 Electric Power Automation Equipment Press. All rights reserved.

Keyword :

Efficiency Efficiency Electric loads Electric loads Genetic algorithms Genetic algorithms Multiobjective optimization Multiobjective optimization Reactive power Reactive power Well testing Well testing

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GB/T 7714 Liu, Qingzhen , Huang, Junying , Wang, Shaofang . Compounding voltage weakness indicator and reactive power optimization strategy oriented to it [J]. | Electric Power Automation Equipment , 2024 , 44 (1) : 147-152 and 159 .
MLA Liu, Qingzhen 等. "Compounding voltage weakness indicator and reactive power optimization strategy oriented to it" . | Electric Power Automation Equipment 44 . 1 (2024) : 147-152 and 159 .
APA Liu, Qingzhen , Huang, Junying , Wang, Shaofang . Compounding voltage weakness indicator and reactive power optimization strategy oriented to it . | Electric Power Automation Equipment , 2024 , 44 (1) , 147-152 and 159 .
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Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory SCIE
期刊论文 | 2024 , 10 (6) , 2657-2666 | CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
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In order to effectively utilize the dielectric response characteristics of transformers to diagnose the insulation state, this paper proposes a two-level hybrid optimization method for analyzing time-domain dielectric response characteristics. The optimization algorithm is based on the combined statistical indicators (CSI) and random forest (RF) theory. The initial feature space set is formed with 23 time-domain characteristics. In the first-level stage, statistical indices correlation, distance, and information indicators are integrated to assess the synthesis score of the characteristics, while highly redundant and low-class discrimination characteristics are eliminated from the initial space set. In the second-level stage, the Random Forest based outside bagging data theory is introduced to evaluate the least important characteristics, and the characteristics with low importance indices are excluded to obtain the final optimal feature space set. The proposed method is carried out on 82 sets of data from actual dielectric response tests on oil-paper insulation transformers. Finally, the final optimal feature space set, along with several other data sets, is tested via different diagnosis methods. The results show that the optimal feature space set obtained via the proposed method outperforms other feature space sets in terms of better adaptability and diagnosis accuracy.

Keyword :

Aging Aging Correlation Correlation Decision trees Decision trees Feature space optimization Feature space optimization integrated statistical indicators integrated statistical indicators Oil insulation Oil insulation oil-paper insulation state oil-paper insulation state Optimization methods Optimization methods Power transformer insulation Power transformer insulation random forest random forest Time-domain analysis Time-domain analysis time domain characteristic time domain characteristic two-level algorithm two-level algorithm

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GB/T 7714 Liu, Qingzhen , Cai, Chao , Wu, Lei et al. Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory [J]. | CSEE JOURNAL OF POWER AND ENERGY SYSTEMS , 2024 , 10 (6) : 2657-2666 .
MLA Liu, Qingzhen et al. "Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory" . | CSEE JOURNAL OF POWER AND ENERGY SYSTEMS 10 . 6 (2024) : 2657-2666 .
APA Liu, Qingzhen , Cai, Chao , Wu, Lei , Yan, Renwu . Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory . | CSEE JOURNAL OF POWER AND ENERGY SYSTEMS , 2024 , 10 (6) , 2657-2666 .
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基于多策略融合粒子群算法的油纸绝缘参数辨识
期刊论文 | 2024 , 25 (9) , 14-21 | 电气技术
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Abstract :

针对粒子群优化算法收敛速度较慢、易陷入局部最优、收敛结果不够稳定等问题,本文从初始种群、边界处理、惯性权重三个方面对传统粒子群算法进行改进,提出多策略融合粒子群算法(MSF-PSO),并通过测试函数证明了MSF-PSO可大幅提高计算速度和计算效率.将MSF-PSO应用于变压器油纸绝缘介电响应的德拜等效电路参数辨识中,计算结果表明,与其他粒子群优化算法相比,该算法获得的回复电压极化谱能更好地与现场测试获得的回复电压极化谱相吻合,进一步验证了本文所提改进算法的准确性,可为诊断变压器油纸绝缘设备老化情况提供参考.

Keyword :

参数辨识 参数辨识 回复电压 回复电压 回复电压极化谱 回复电压极化谱 油纸绝缘 油纸绝缘 粒子群优化 粒子群优化

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GB/T 7714 徐晨展 , 刘庆珍 . 基于多策略融合粒子群算法的油纸绝缘参数辨识 [J]. | 电气技术 , 2024 , 25 (9) : 14-21 .
MLA 徐晨展 et al. "基于多策略融合粒子群算法的油纸绝缘参数辨识" . | 电气技术 25 . 9 (2024) : 14-21 .
APA 徐晨展 , 刘庆珍 . 基于多策略融合粒子群算法的油纸绝缘参数辨识 . | 电气技术 , 2024 , 25 (9) , 14-21 .
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基于改进雪融优化算法的油纸绝缘扩展德拜模型参数辨识
期刊论文 | 2024 , 37 (9) , 80-87 | 广东电力
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基于回复电压法求解变压器油纸绝缘扩展德拜模型等效电路参数,是典型的非线性多目标优化问题.为了提高扩展德拜模型参数辨识的效率和准确度,提出一种新颖的改进雪融优化(improved snow ablation optimizer,ISAO)算法,旨在有效解决扩展德拜模型参数辨识问题.ISAO算法融合了多种改进策略,运用Tent混沌映射和折射镜像学习机制提高搜索效率,引入莱维飞行策略和贪婪策略增强优化性能,并提出参数预设机制,进一步简化辨识流程、提高求解效率.将ISAO算法应用于油纸绝缘扩展德拜等效电路参数的优化求解,并与几种常用的智能优化算法进行对比,结果表明该算法在扩展德拜模型参数辨识问题上具有显著优势.

Keyword :

参数辨识 参数辨识 参数预设机制 参数预设机制 回复电压法 回复电压法 扩展德拜模型 扩展德拜模型 油纸绝缘 油纸绝缘 非线性多目标优化 非线性多目标优化

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GB/T 7714 周宇含 , 刘庆珍 . 基于改进雪融优化算法的油纸绝缘扩展德拜模型参数辨识 [J]. | 广东电力 , 2024 , 37 (9) : 80-87 .
MLA 周宇含 et al. "基于改进雪融优化算法的油纸绝缘扩展德拜模型参数辨识" . | 广东电力 37 . 9 (2024) : 80-87 .
APA 周宇含 , 刘庆珍 . 基于改进雪融优化算法的油纸绝缘扩展德拜模型参数辨识 . | 广东电力 , 2024 , 37 (9) , 80-87 .
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基于等级云模型的油纸绝缘老化状态评估 CSCD PKU
期刊论文 | 2023 , 59 (1) , 176-184 | 高压电器
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Abstract :

针对油纸绝缘介电响应法中单一特征量老化评估不准确等问题,提出运用等级云模型进行多特征量的油纸绝缘老化状态评估.首先,运用矩阵束算法对等效电路进行参数辨识,提出两个能分别表征几何支路和极化支路老化状态的新时域特征量;然后,结合主、客观两种不同赋权方法进行综合权重的计算;最后,使用等级云模型来构建设备老化状态的评估模型:根据云模型理论和实测数据得到各标准等级云模型的数字特征,将待评估设备的各项指标与标准等级云模型进行关联度计算,从而得到设备的绝缘老化等级.经若干实例验证,该方法得到的评估结果能正确反映设备的真实情况,具备较高的应用可行性.

Keyword :

介电响应法 介电响应法 油纸绝缘 油纸绝缘 矩阵束算法 矩阵束算法 等级云模型 等级云模型 老化状态评估 老化状态评估

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GB/T 7714 刘庆珍 , 陈俊鸿 . 基于等级云模型的油纸绝缘老化状态评估 [J]. | 高压电器 , 2023 , 59 (1) : 176-184 .
MLA 刘庆珍 et al. "基于等级云模型的油纸绝缘老化状态评估" . | 高压电器 59 . 1 (2023) : 176-184 .
APA 刘庆珍 , 陈俊鸿 . 基于等级云模型的油纸绝缘老化状态评估 . | 高压电器 , 2023 , 59 (1) , 176-184 .
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基于多模型综合特征选择和LSTM-Attention的短期负荷预测
期刊论文 | 2022 , 7 (6) , 11-20 | 分布式能源
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为提高电力系统短期负荷预测精度和预测效率,提出一种基于多模型综合特征选择和长短期记忆单元(long short time memory,LSTM)-Attention的短期负荷预测方法.首先,利用随机森林算法、自适应集成(adaptive boosting,AdaBoost)算法及梯度提升树(gradient boosting decision tree,GBDT)算法对原始数据进行初步拟合预测,提取3种算法拟合后的结果来获取特征量与负荷大小的相关系数,从而建立综合相关系数.接着,根据综合相关系数的大小,剔除相关系数较小的特征量,将剩余的特征量与历史负荷大小数据结合构成新的数据集.最后,将新的数据集作为LSTM-Attention预测模型的输入,从而得到待预测日的负荷预测曲线.通过分析所提出的预测方法在某地区负荷数据集的预测结果可知,该方法优于其他预测方法.

Keyword :

LSTM-Attention LSTM-Attention 多模型 多模型 特征选择 特征选择 相关系数 相关系数 短期负荷预测 短期负荷预测

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GB/T 7714 彭泽森 , 刘庆珍 , 张溢 . 基于多模型综合特征选择和LSTM-Attention的短期负荷预测 [J]. | 分布式能源 , 2022 , 7 (6) : 11-20 .
MLA 彭泽森 et al. "基于多模型综合特征选择和LSTM-Attention的短期负荷预测" . | 分布式能源 7 . 6 (2022) : 11-20 .
APA 彭泽森 , 刘庆珍 , 张溢 . 基于多模型综合特征选择和LSTM-Attention的短期负荷预测 . | 分布式能源 , 2022 , 7 (6) , 11-20 .
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