Microgrids Digital Transformation



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Transcription:

Microgrids Digital Transformation Maher Chebbo, PhD Energy General Manager Energy for EMEA SAP Maher.chebbo@sap.com President of ESMIG 2015 SAP SE or an SAP affiliate company. All reserved. ETP SmartGrids Demand &rights Digital Chair Customer 1

1 The Microgrids Equation 2 Digital Energy 3 Microgrids Digital Intelligence 4 Conclusion 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 2

SmartGrids and Microgrids : Real Time, Internet of Things, Big Data and Digital Transformation needed Weather Prediction: Sunny, Windy, 23ºC Service Ecosystem 2020+ Wind leads to more electricity generation M. SANCHEZ, 2006, Quelle: European Technology Platform SmartGrids Energy production covers (estimated) needs 2015 SAP SE or an SAP affiliate company. All rights reserved. Green Electricity available Lower electricity production Sun leads to increased electricity generation Electricity Car can get cheaper recharge Heat generators are not needed Customer 3

The Microgrids Equation MICROGRID MODES OF OPERATION INTO ACTIVE NETWORKS STORAGE VARIABLE LOAD DEMAND SIDE DISTRIBUTED ENERGY THE MICROGRIDS EQUATION ECONOMICS SMARTGRIDS BUSINESS MODELS INTERNET OF THINGS BIG DATA, IT/OT REAL TIME PREDICTIONS 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 4

1 The Microgrids Equation 2 Digital Energy 3 Microgrids Digital Intelligence 4 Conclusion 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 5

Big data brings new business opportunities, innovation, transformation and growth Millions 35,000 25,000 15,000 5,000 30+ Billion Things by 2020 Internetof-Things 2007 2015 2020 Strategy Analytics, October 2014 Home Devices Personal Devices 44 trillion gigabytes (44ZB) of data will be generated in 2020 data creation is more than doubling every two years http://www.emc.com/leadership/digital-universe/ 2014iview/executive-summary.htm 60% increase in operating margin in retail companies using Big Data as a new resource http://www.mckinsey.com/insights/ business_technology/ big_data_the_next_frontier_for_innovation More than 60% of CEOs expect 15% 50% of their earnings growth in the next 5 years to come from technology-enabled business innovations. McKinsey study, 2013 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 6

The Digital Strategy empowering the Business Strategy 2011 SAP AG. All rights reserved. 7

Technology innovations Maturity Model for Utilities & Grids 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 8

IT/OT Integration : Situation awareness, integrating financial and operational data with predictive analytics to drive decision making 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 9

Underground Residential Distribution (URD) : Role of IT/OT integration & Big Data in improving Outage Management Analyze the test/ inspection and historical outage data around Underground Residential Distribution assets (Primary cables, Pad Mount Transformers and Fuses) View and Analyze a condition score for URD cables and transformers, Optimize inspection, Visualize the URD network on a geo-spatial user interface, Layer descriptive and predictive analytics 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 10

Digital Grid Applications & Analytics combining Business Processes + Information + Technology Information Intelligence : e.g. Real Time Predictive Analytics (e.g. Predicting Customer s Demand) In-Memory Technology Big Data (HANA) Complex Event Processing IT/OT Integration Cloud Metering-ISO Smart Homes Smart Cities Visual Enterprise Active Networks Aggregation Customer Self Services Mobility User Experience Electrical Vehicles Cloud Demand Management Virtual Power Plants Cloud / On Premise SmartGrids & Microgrids Platforms (OnPrem or PaaS) 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 11

Critical Transformer Load & Loss of Life using inmemory Big Data Predictive Analytics In-Memory Predictive IEC 60076-7 VDE 0532-76-7 (Loading guide for oil-immersed transformers) 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 12

Example of Technology Innovations : Asset & Customers Big Data and Analytics Asset Lifecycle & Predicitions In-Memory (HANA) & Analytics Geo Analytics Smart Metering & Energy Efficiency 3D Visual Enterprise SmartGrids 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 13

The Unique Value Proposition Combining Business Processes, Information and Technology Forecasting BUSINESS PROCESS PLATFORM INFORMATION PLATFORM Predictions Powered by in-memory Technology (SAP HANA) 2011 SAP AG. All rights reserved. 14

Smarter Decisions + Smarter Processes = Smarter Services 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 15

1 The Microgrids Equation 2 Digital Energy 3 Microgrids Digital Intelligence 4 Conclusion 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 16

Microgrids different Modes of Operation and required integration in Active Network Management (e.g. Southern Company project) In any of the three Operating modes of Microgrids, Active Network Management requires: Ø Ø Ø Ø Ø Ø Management of power flow constraints Management of voltage constraints Management of distributed generation contributing to transmission system constraints Smart electric vehicle charging Demand Response (domestic / commercial) Day ahead scheduling of controllable demand to coincide with renewable energy production to support frequency stability 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 17

Incorporate Microgrids Controller enabled by Digital Intelligence for an improved Active Network Management Data Historian New layer of control: Microgrid Controller (Southern Company) ANM Application DMS DERMS Digital Intelligence Digital Intelligence Microgrid Controller Digital Intelligence Microgrid Controller Microgrid Controller Generator Facility Microgrid Circuit Microgrid Energy Storage System Generator Substation Microgrid Energy Storage System 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 18

Layers of Microgrid Control (Southern Company Project) which could be empowered by Digital Intelligence (IT/OT, IoT, HANA, RT) Layers of Microgrid Control Digital Intelligence 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 19 19

«Apple Store» like as a Public HANA Cloud Platform for Energy Services : H2020 project «FLEXICIENCY» could include Microgrid cases ENR HCP FLEXICIENCY Electricity pan-european Marketplace for Distribution & Retail : Kind of Apple Store for Energy Demand Services target 10 000 Utilities on the same Public Marketplace 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 20

1 The Microgrids Equation 2 Digital Energy 3 Microgrids Digital Intelligence 4 Conclusion 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 21

Microgrids : what will change? WILL CHANGE TO BECOME WITH 1 ENERGY CONNECT ALL ASSETS AND CUSTOMERS DATA IN REAL TIME PREDICTIBLE SMARTGRIDS MICROGRIDS 2 NETWORKS INTEGRATE MICROGRIDS WIH A SPECIFIC CONTROLLER LAYER MORE ACTIVE DIGITAL INTELLIGENCE 3 DATA BIG DATA COLLECTED IN REAL TIME INTELLIGENCE IN-MEMORY HANA PREDICTIVE ANALYTICS 4 CUSTOMERS FLEXIBLE DEMAND EMPOWERED DIGITAL ENERGY 5 MICROGRIDS INTEGRATE WITH ACTIVE NETWORKS, DER AND ACTIVE DEMAND DIGITAL IT/OT, IoT, BIG DATA, HANA PREDICTIVE ANALYTICS 2015 SAP SE or an SAP affiliate company. All rights reserved. Customer 22

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