Using ANFIS to Predict Harmonic Distortion in Residential Building Loads: A case study in the Amazonian Region of Brazil

Albino Moisés Faro de Morais Junior, M. Tostes, U. Bezerra, T. M. Soares
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Abstract

With the increasing use of nonlinear loads in homes in Brazil comes the problem of harmonic injection in the power system and increasingly is a problem for the electric sector that needs to scale it. Knowing the loads that consume energy and inject harmonics into the system is important so that solutions are sought to make the use of the system more efficient and improve the quality of the energy that circulates in the electrical grid. This work presents simulations of DHTv and DHTi of a set of residences in order to predict the behaviour of the load over time, using previous measurements. The modelling is conducted using an ANFIS, which uses a neural network to adjust the parameters of the output that uses fuzzy rule to determine the output values of the system.
应用ANFIS预测住宅建筑荷载谐波畸变:以巴西亚马逊地区为例
随着巴西家庭使用非线性负载的增加,电力系统中的谐波注入问题也随之而来,这对需要扩大规模的电力部门来说日益成为一个问题。了解消耗能量和向系统注入谐波的负载是很重要的,这样才能寻求解决方案,使系统的使用更有效,并提高在电网中循环的能量的质量。这项工作提出了一组住宅的DHTv和DHTi的模拟,以便预测负载随时间的行为,使用以前的测量。采用ANFIS进行建模,利用神经网络调节输出参数,利用模糊规则确定系统输出值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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