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A Hybrid Method for Non-Technical Loss Detection in Smart Distribution Grids

机译:智能配电网中非技术损失检测的混合方法

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摘要

Non technical losses (NTLs) are a major problem faced by DSOs all over the world. Traditional meter inspection techniques are not effective in detecting NTL, while the wide adoption of smart meters and smart grid technologies provide new opportunities for solving the problem. The proposed NTL detection system utilizes voltage sensitivity analysis, power system optimization, and support vector machines (SVMs) for correctly detecting NTLs in the distribution grid under various conditions. Breakout detection is used for extracting features from consumption time series and training an SVM classifier. Generalized least squares is used for estimating the network voltage self-sensitivities. Finally, the NTL detection problem is formed as a non-linear non-convex optimization problem solved with semi-definite programming relaxation. The three modules can be operated either autonomously or combined. The proposed NTL detection system is demonstrated under different scenarios to test its effectiveness.
机译:非技术损失(NTL)是全世界DSO面临的主要问题。传统的电表检查技术不能有效地检测NTL,而智能电表和智能电网技术的广泛采用为解决该问题提供了新的机会。提出的NTL检测系统利用电压灵敏度分析,电力系统优化和支持向量机(SVM)在各种情况下正确检测配电网中的NTL。突破检测用于从消耗时间序列中提取特征并训练SVM分类器。广义最小二乘用于估计网络电压的自敏感度。最后,NTL检测问题形成为一个非线性半凸优化问题,可以通过半定规划松弛来解决。这三个模块可以自主运行,也可以组合运行。建议的NTL检测系统将在不同的场景下进行演示,以测试其有效性。

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