A project to analyze power usage data offered by Taiwan Power Cooperation in 2017 Smart Grid Big Data Analytics Competition
The goal of this project is to find some useful information through out the history data of power usage and some open data (e.g. weather data). We use clustering method to form groups and later we will build deep learning (SVR, RNN, LSTM) model to predict power usage. This repository focus on how to do clustering.
低壓智慧電表大數據分析與設計競賽。針對歷史用電資料，利用數值分析等方法，提出具學術或應用價值的研究
- 本篇著重於如何做分群，不包含預測用電量的檔案。
利用本次競賽所提供的一年期間，每15分鐘低壓智慧電表資料，自行搭配氣象資料等，進而利用數值分析或演算分析個體或全體住戶的用電行為，例如用電量預測、用電特徵、不同區域比較或節電建議…等 (不限於此)。
開放資料內容 1.用戶類型：低壓住宅1,000戶以上 環境資訊：該資料所屬地區(縣市)、用電類型(表燈…等)。 即時用電資料：當下前15分鐘的用電能量（kWh） 歷史用電資料：去年度所有15分鐘用電能量（kWh） 電價資訊：台電現行季節電價、住商簡易時間電價方案 2.介面與格式 研析組：提供用戶一整年度歷史用電資料，格式擬為CSV。
國立交通大學 林于翔、許睿之、楊凱期、黃揚、彭笙榕、蘇恆毅、黃婉婷、陳泓勳
This project is licensed under the MIT License
Copyright (C) <2017> <Wan-Ting Huang>
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