异常电能表查找系统研究

发布时间：2018-09-01 16:36

【摘要】：电能计量装置是电力系统重要组成部分,电能计量装置准确与否将影响到电力贸易结算的公平、准确,直接关系到电力企业和用户的实际利益。电能计量装置异常,将损害电力企业和用户的经济利益,更严重的将导致电力系统无法正常工作。电能计量装置正误差超差将导致用户经济利益受损；电能计量装置负误差超差将导致台区线损量变大,直接影响电力企业的经济利益。因此及时有效地定位异常电能表,受到了社会广泛关注。全文主要从用户用电异常导致台区线损量异常的角度建立数学模型,从而达到定位异常电能表的目的。本文结合目前国内外对异常电能表的研究,提出了基于用户信息采集系统的异常电能表查找系统。本文首先对电能计量装置异常的原因及异常表现进行讨论分析,并对国内外目前异常电能表查找研究现状进行了总结。电能计量装置异常将导致台区线损量异常,通过观察台区线损量是否异常从而发现台区是否存在用户用电异常。线损量异常是由台区某些计量装置异常造成的,计量装置误差越大则其对线损量造成的影响越大。通过数学推导发现,在合理排除某些因素的情况下,用户电量采样值与台区线损量之间呈线性关系,而皮尔逊相关系数法是用来描述两个随机变量之间线性关系紧密程度的,因此本文提出利用皮尔逊相关系数法分别计算台区各用户电量采样值与台区线损量之间的相关系数,相关系数越高的用户则其对台区线损量造成异常的可能性越大。在实际利用皮尔逊相关系数法定位异常电能表用户时,取得了显著成效。但在实践过程中发现了皮尔逊相关系数法的部分不足,在应用过程中发现当用户私接户外电线用电时皮尔逊相关系数法的定位精度不高,经过理论分析此种情况异常用电量与台区线损量并不成线性关系,本文提出了基于灰色GM(1,1)模型的阈值模型来定位此种情况下异常电能表用户。本文分析了灰色GM(1,1)模型的建模机理,利用灰色GM(1,1)模型建立用户负荷预测模型,同时对灰色GM(1,1)模型存在的问题进行了论述,提出了利用马尔科夫链算法对灰色GM(1,1)模型进行修正,克服了原有模型的不足,提高了灰色GM(1,1)模型的预测精度。最后在负荷预测值的基础上,综合利用历史数据和专家意见选取合适阈值,建立用户负荷阈值模型,当用户采样值不在负荷阈值范围内,则对该用户进行排查。最后在用户用电信息采集系统的基础上,建立了异常电能表查找系统,本文详细介绍了异常电能表查找系统的架构及设计思路。
[Abstract]:The electric energy metering device is an important part of the power system. Whether the electric energy metering device is accurate or not will affect the fairness and accuracy of the electric power trade settlement and directly affect the actual interests of the electric power enterprises and users. Abnormal energy metering devices will harm the economic interests of power enterprises and users, and will lead to the failure of the power system to work properly. The positive error of the electric energy metering device will lead to the damage of the user's economic benefit, and the negative error of the power metering device will lead to the increase of the line loss in the station area, which will directly affect the economic benefit of the electric power enterprise. Therefore, the timely and effective positioning of abnormal watt-hour meters has received widespread attention. In this paper, a mathematical model is established from the point of view of abnormal line loss caused by abnormal power consumption, so as to achieve the purpose of locating abnormal watt-hour meter. Based on the research of abnormal watt-hour meter at home and abroad, this paper puts forward an abnormal watt-hour meter lookup system based on user information acquisition system. In this paper, the reason and performance of abnormal electric energy metering device are discussed and analyzed, and the research status of abnormal watt-hour meter at home and abroad is summarized. The anomaly of electric energy metering device will lead to abnormal line loss in the station area. By observing whether the line loss amount in the station area is abnormal or not, we can find out whether there is an abnormal power consumption in the station area. The anomaly of line loss is caused by the anomaly of some metering devices in the station area, and the greater the error of the measuring device, the greater the influence on the line loss. Through mathematical derivation, it is found that the linear relationship between the sampling value of the user's electricity quantity and the line loss of the station area is linear when some factors are reasonably excluded, and Pearson correlation coefficient method is used to describe the degree of the linear relationship between the two random variables. Therefore, the Pearson correlation coefficient method is used to calculate the correlation coefficient between the sampling value of electricity quantity and the line loss of the station area, and the higher the correlation coefficient is, the more likely it is that the higher the correlation coefficient is, the more abnormal it is to the line loss amount of the station area. When using Pearson correlation coefficient method to locate users of abnormal watt-hour meters, remarkable results have been achieved. However, some deficiencies of Pearson correlation coefficient method are found in the process of practice. In the process of application, it is found that the positioning accuracy of Pearson correlation coefficient method is not high when the user uses electricity for outdoor wire. Based on the theoretical analysis that the abnormal power consumption is not linearly related to the line loss of the station area, a threshold model based on the grey GM (1 / 1) model is proposed to locate the users of the abnormal watt-hour meter in this case. In this paper, the modeling mechanism of grey GM (1K1) model is analyzed, and the user load forecasting model is established by using the grey GM (1K1) model. At the same time, the problems existing in the grey GM (1K1) model are discussed, and the grey GM (1K1) model is modified by Markov chain algorithm. It overcomes the shortcomings of the original model and improves the prediction accuracy of the grey GM (1 ~ 1) model. Finally, on the basis of load forecasting value, using historical data and expert opinion to select appropriate threshold value, the user load threshold model is established. When the sampling value of user is not within the range of load threshold, the user is searched. Finally, on the basis of the information collection system, the paper establishes the abnormal watt-hour meter lookup system. This paper introduces the structure and design idea of the abnormal watt-hour meter lookup system in detail.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TM933.4

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