NILM的一些论文，尤其是Kelly的可以仔细了解学习一下她的实验流程和设计。为之后自己设计网络结构和解题思路打基础。

序列到点网络nilm，即基于序列到点的深度CNN神经网络，进行非侵入式负荷分解

学习NILM 会使用到的数据集，已经转换成了HDF5格式，可以直接使用。The Reference Energy Disaggregation Dataset (REDD) [5] was introduced as the rst publicly available data set collected specically to aid NILM research. The data set contains both aggregate and sub-metered power data from six households, and has since become the most popular data set for evaluating energy disaggregation algorithms.

提供完整可跑的NILMTK项目，数据集是REDD的低频数据，使用方法有两个CO和FHMM，来进行分解和预测。 除了导入项目代码，还需要配置环境，详见我笔记里面说明的流程https://blog.csdn.net/wwb1990/category_9655726.html

基于辅助线性整数规划的负荷分解，这是一篇论文，Load disaggregation based on aided linear integer programming (ALIP) is proposed. We start with a conventional linear integer programming (IP)-based disaggregation and enhance it in several ways. The enhancements include additional constraints, correction based on a state diagram, median filtering, and linear-programming-based refinement.

关于nilmtk工具包的论文说明，是，有助于了解nilmtk工具包的使用。

这个代码是NILMTK中的CO代码，主要利用组合优化算法来做电荷负载分解