https://github.com/nipunbatra/gemello

https://github.com/nipunbatra/gemello

algorithms analytics data-science disaggregation energy grid ipython-notebook jupyter-notebook machine-learning nilm python smart-meter sustainability

Last synced: about 1 month ago
JSON representation

• Host: GitHub
• URL: https://github.com/nipunbatra/gemello
• Owner: nipunbatra
• Created: 2015-10-09T05:09:39.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2017-11-28T23:21:51.000Z (almost 7 years ago)
• Last Synced: 2024-10-11T15:40:57.435Z (about 1 month ago)
• Topics: algorithms, analytics, data-science, disaggregation, energy, grid, ipython-notebook, jupyter-notebook, machine-learning, nilm, python, smart-meter, sustainability
• Language: Jupyter Notebook
• Size: 689 MB
• Stars: 18
• Watchers: 4
• Forks: 3
• Open Issues: 4
• Metadata Files:
  • Readme: Readme.md

Awesome Lists containing this project

README

        
Gemello: Creating a Detailed Energy Breakdown from just the Monthly Electricity Bill

-------------------

This repository contains code for Gemello: Creating a Detailed Energy Breakdown from just the Monthly Electricity Bill. This paper was accepted at [SIGKDD 2016](http://www.kdd.org/kdd2016/).

Please use the following bib entry to cite the paper.

```

@inproceedings{Batra:2016:GCD:2939672.2939735,

 author = {Batra, Nipun and Singh, Amarjeet and Whitehouse, Kamin},

 title = {Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill},

 booktitle = {Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},

 series = {KDD '16},

 year = {2016},

 location = {San Francisco, California, USA},

 pages = {431--440},

  url = {http://doi.acm.org/10.1145/2939672.2939735},

 doi = {10.1145/2939672.2939735}

}

```

More pertinent links to the paper

1. [Paper pdf](https://www.iiitd.edu.in/~nipunb/papers/gemello.pdf)

2. [Youtube video](https://www.youtube.com/watch?v=pzgqd9OhvDA)

3. [Poster](https://www.iiitd.edu.in/~nipunb/slides/kdd_poster_final.pdf)

This work was also presented at the [3rd NILM workshop](http://nilmworkshop.org/2016/). You can find the [slides](http://nilmworkshop.org/2016/slides/NipunBatra2.pdf) and the [talk recording](https://www.youtube.com/watch?v=LUauYdlbH74).

This Readme gives a description of the repository structure and how one can repeat the experiments. The final plots and analysis is all done in IPython notebooks.

Each folder in this repository has a Readme describing the contents of the folder.

First, links to the notebooks for the figures

| Figure/Table| Link |

| --- | --- |

| Figure 1 | [Approach](https://docs.google.com/drawings/d/1R68GnSezUbC-RiGcwy3E8cSYYHZAgf50YiYkTOqUWFg/edit?usp=sharing) |

| Figure 2 | [Dataset description](https://github.com/nipunbatra/Gemello/blob/master/code/dataset_description.ipynb) |

| Figure 3 |[Code for producing estimates](https://github.com/nipunbatra/Gemello/blob/master/code/main_result_parallel_new.py), [Notebook for ingesting the estimates and producing plots](https://github.com/nipunbatra/Gemello/blob/master/code/main-result.ipynb) |

| Figure 4 | [Comparison with state-of-art at higher frequency](https://github.com/nipunbatra/Gemello/blob/master/code/lbm-2min-15min-vs-gemello.ipynb)|

| Figure 5 and Table 3| [Sensitivity analysis on features](https://github.com/nipunbatra/Gemello/blob/master/code/sensitivity-features.ipynb)|

| Figure 6| [Sensitivity analysis on number of homes](https://github.com/nipunbatra/Gemello/blob/master/code/sensitivity-numhomes.ipynb) |