| 引用本文: | 王学伟,王艳君,王磊,彭小娟.基于随机过程平均功率的量化误差影响分析[J].电力自动化设备,2018,(7): |
| WANG Xuewei,WANG Yanjun,WANG Lei,PENG Xiaojuan.Effect analysis of quantization errors based on stochastic process considering average power[J].Electric Power Automation Equipment,2018,(7): |
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| 摘要: |
| 针对数字化变电站电能计量系统中量化误差对功率测量误差的影响，从系统分析的角度出发，建立了数字化电能计量系统结构化模型和功率测量单元结构化模型，详细地揭示了数字化电能计量系统内部构成要素间的误差传递关系；给出了量化误差的随机过程表述，提出了基于随机过程平均功率的量化误差对功率测量误差的影响分析方法，推导了量化误差影响的功率测量误差数学模型，给出了功率测量相对误差数学解析式；通过对比分析理论推导极限值与蒙特卡罗仿真极限值，二者均在同一个数量级，且理论推导极限值大于仿真极限值，验证了所提方法的有效性。与传统的分析方法相比，所提出的分析方法具有普适性，对功率测量误差的估计具有理论指导意义。 |
| 关键词: 数字化电能表 结构化模型 量化误差 随机过程 功率测量误差 |
| DOI：10.16081/j.issn.1006-6047.2018.07.025 |
| 分类号:TM933 |
| 基金项目:国家高技术研究发展计划(863计划)资助项目(2015AA050404)；国家自然科学基金资助项目(51577006) |
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| Effect analysis of quantization errors based on stochastic process considering average power |
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WANG Xuewei1, WANG Yanjun1, WANG Lei2, PENG Xiaojuan1
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1.College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;2.National Institute of Metrology, Beijing 100013, China
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| Abstract: |
| Aiming at the influence of quantization errors on power measurement error in digital substation energy metering system, the structural models of digital energy metering system and power measurement element are established from the perspective of system analysis, which reveals the error propagation relationship among the internal components of the digital energy metering system in detail. A stochastic process representation of the quantization errors is given and the analysis method based on the stochastic process considering average power is proposed. The mathematical model of power measurement error under the influence of quantization errors is deduced. Furthermore, the mathematical analytic formula of power measurement relative error is derived. By comparing the theoretical extreme value with the Monte Carlo simulation extreme value of power measurement relative error, in which both of them are in the same orders of magnitude and theoretical extreme values are greater than simulation extreme values, it is concluded that the proposed method is valid. Compared with the traditional quantitative error analysis method, the proposed method is universally applicable and can serve as theoretical basis for power measurement error estimation. |
| Key words: digital energy meter structural model quantization error stochastic process power measurement error |
