SUPERGrid: Security, Visualization, Fraud Detection and Big Data for Smart Grids

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1 SUPERGrid: Security, Visualization, Fraud Detection and Big Data for Smart Grids Juan Miguel Gómez Berbis, PhD Universidad Carlos III de Madrid

2 Project Outline l Based on the H2020 ITEA3 SECUREGRID project (5M ) l More than 20+ companies all over Europe (EDF, GDF Suez, VTT, SOTEC, Turkcell) l Adding Big Data and Visualization Platforms to Enhance a Smart Grid l Grid Management of the XXIth Century

3 Smart Grids Analysis, Management and Visualization Security Management Predictive Analytics

4 v Smart Grids Significant changes in energy systems From centralized, unidirectional grid I Generation, Transmission, Rail (established business) already automated to distributed energy and bidirectional energy balancing Hydrogen Storage End-to-end: Connect Generation & Consumption III and optimize via a Smart Grid Diesel Generator Biogas CHP Private Solar Offshore Wind Parks Pumped Storage Power Plant Storage Solutions Small Industrial Gas Turbine Storage Solutions Electrical Vehicles Smart Street Lighting Large Scale PV Plant I Generation, Transmission, Rail (established business) already automated II Little Automation in Distribution today - not sustainable Unidirectional Power Flow Bidirectional Power Flow Siemens AG 2013 All rights reserved. Page Larsh Johnson/ emeter, A Siemens Business

5 5 CoolReport by Nimbeo v

6 6 CoolReport v 1. Preparation 5. Dissemination 2. Data Extraction 4. Decisions and Results 3. Analysis

7 7 CoolReport v Preparation Data Extraction Agile Flexible Dynamic Adaptative Heterogenous Sources Internet of the Things M2M Sense&Report Open Data External Systems Analysis Visualization / Dissemination Smart Big Data Optimization Scalability Estimation/Prediction Aggregation Advanced GIS Dashboard KPIs HTML5 WebGL Netcartography

8 8 v Monitoring and Predic2ve Analy2cs

9 Fraud Detection Ingresos Edad

10 IDSS Big Data Structure Network Data Customer data Business data Big-Data Analytics Artificial Intelligence Data Mining Natural Language processing Predictive Analytics

11 IDSS Big-Data Analytics MapReduce map (k1,v1) à list(k2,v2) reduce (k2,list(v2)) à list(v2) Distortion for the centroid Segmentation Distance functions K-means

12 v Three Security Levels Outline - HVDC transmi l Encription at Smart Metering l Fraud Detection l IDSS The virtual power plant Power Hub Providing the link between distributed energy resources and system operators DSOmarket? Energy and reserve markets Create value from tradin flexibility IT system Infrastructure Organisation Biz. processes Enable new business ABB Group October 1, 2013 Slide 2

13 SUPERGrids Full potential of Smart Grids Dynamic Fraud Detection AI, IDSS Secure Smart Grids Static Smart Grids URI, HTML, HTTP Big Data Hadoop, MapReduce

14 References [1] Kalil, Tom (2012). "Big Data is a Big Deal". White House. [2] Office OF science AND technology policy executive office OF THE president. (2012). Obama administration unveils big data initiative: announces $200 million in new r&d investments. Retrieved February 14, 2013 From: ostp/big_data_press_release_final_2.pdf [3] Executive Office of the President (March 2012). "Big Data Across the Federal Government". White House. [4] Webster, Phil. "Supercomputing the Climate: NASA's Big Data Mission". CSC World. Computer Sciences Corporation. Retrieved February 14, [5] Data, data everywhere. The Economist. Retrieved February 14, 2013 From: [6] FICO Falcon Fraud Manager. Retrieved February 14, 2013 From: FIResourcesLibrary/FICO_Falcon_Fraud_Manager_1247PS.pdf [7] knowit Information Systems.(2012). ebay Study: How to Build Trust and Improve the Shopping Experience. Retrieved February 14, 2013 From: aid=1333

15 Q&A

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