Smart Meter Data Analytic using Hadoop
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Smart Meter Data Analytic using Hadoop

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Smart Meter Data Analytic using Hadoop Smart Meter Data Analytic using Hadoop Presentation Transcript

  • Smart Meter Data Analytic Using Hadoop Omkar Nibandhe and Abhishek Korpe students
  • SMART METER DATA ANALYTICS (SMDA) USING HADOOP By : Omkar Nibandhe ( Student ) Abhishek Korpe ( Student ) 03-04-2014SMDAusingHADOOP 2
  • Why Smart Meter Data Analytics ? 03-04-2014SMDAusingHADOOP 3
  • What are SMART METERS ? MIF • Track and store the amount of energy used. • Send the collected data to the Energy Distribution company server at regular time intervals. House/ Industry Smart Meter Server 03-04-2014SMDAusingHADOOP 4
  • Advantages • Service Provider • Demand-Response • Time of use tariff • Load Profile Analysis • Theft Detection • Billing Accuracy • Customers • Usage Pattern • Billing Accuracy • Convenience in change of service provider 03-04-2014SMDAusingHADOOP 5
  • Confronting the data deluge • Rate Generation – 15 minutes. • For single meter – 3000 readings/month (approx ). • For 1 million meters – 36 Billion readings/year (approx). • Annual Growth – 13% ( 2010 – 2015 ). • Total Shipment – 460.9 Million Smart Meters. Source: Build smart metering solutions with IBM Informix TimeSeries 03-04-2014SMDAusingHADOOP 6
  • Capitalizing on the unique value of Hadoop Solution ? • Reducing data load times. • Improving query performance. • Massive Scalability. 03-04-2014SMDAusingHADOOP 7
  • Demand - Response 03-04-2014SMDAusingHADOOP 8
  • Time of use Tariff 03-04-2014SMDAusingHADOOP 9
  • Load Profile Analysis Using hadoopUsing hadoop load time 03-04-2014SMDAusingHADOOP 10
  • Data Flow Diagram Predictive Analysis ( FLUME ) Load Profile Analysis 03-04-2014SMDAusingHADOOP 11
  • Hadoop Cluster in LAB 412 Masters Slaves Slave1 Slave7 Slave8 Slave9 Slave11 Slave6Slave5Slave4Slave3Slave2 Slave10 Slave19Slave18 Slave17Slave16Slave15Slave14Slave13 Slave12 Slave20 Slave21 03-04-2014SMDAusingHADOOP 12
  • LAB 412 (MESCOE Pune, India) 03-04-2014SMDAusingHADOOP 13
  • SMDA - NameNode 03-04-2014SMDAusingHADOOP 14
  • SMDA - SecondaryNameNode 03-04-2014SMDAusingHADOOP 15
  • SMDA - JobTracker 03-04-2014SMDAusingHADOOP 16
  • SMDA – Input ( .MIF ) 03-04-2014SMDAusingHADOOP 17 1392 19501 0.157
  • SMDA - Output 03-04-2014SMDAusingHADOOP 18
  • Test Job 1 03-04-2014SMDAusingHADOOP 19
  • Test Job 2 ( Combiner ) 03-04-2014SMDAusingHADOOP 20
  • Future Scope • Analysis of - • Customer segmentation. • Customer behavior. • Meter ping commands. • Outage management. • Power quality. • Extending data point(s) : weather, geographical location, family consumption, etc. 03-04-2014SMDAusingHADOOP 21
  • Thanks to …. • Irish Social Science Data Archive ( ISSDA ). • Rahul Khinvasara – Director, zCon Solutions Pvt. Ltd. • Modern Education Society’s College of Engineering (MESCOE). • Prof. Balaji Bodkhe – Guide, MESCOE. • Prof. N. Shaikh – Head of Computer Department, MESCOE. • Prof. A. Hake – Vice Principal, MESCOE. • Prof. P. Raut – Administrative Head, MESCOE. 03-04-2014SMDAusingHADOOP 22
  • Any Suggestions ?? 03-04-2014SMDAusingHADOOP 23
  • Thank You. 03-04-2014SMDAusingHADOOP 24
  • Any Questions? 03-04-2014SMDAusingHADOOP 25