Drive business innovation by harnessing energy data

Pieter den Hamer

Lead Big Data, Business Intelligence & Analytics, Alliander

Associate, Copernicus Institute, University of Utrecht

© Pieter den Hamer, Alliander, 2015

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Information

Energy

© Pieter den Hamer, Alliander, 2015 3

+ Green

but

Volatile

Energy

Demand

& Supply

- Grey

but

Predictable

Energy

Demand

& Supply

Source: CE Delft

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Smart Homes

Smart Meters

Smart Appliances

Dynamic Pricing

Electric

Vehicles

+

Charging

Stations

Smart Grid Offshore

Wind

Substation

Automation

Energy

Storage

Waste heat

distribution / city

warming

Local (solar)

energy production

Solar Farms

Smart Power Plants

EU Super Grid

Hydro

Power

Communciations Grid

(mobile + fiber)

MicroGrids

Virtual Power Plants

Onshore Wind

Biogas

Tidal

Energy

Smart Buildings & Cities

Dynamic

Demand/Supply

Balancing

Power Quality Mgt

CO2 emission reduction

+ CCS

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ENTERPRISE

DATA

(Finance,

Customers,

Workforce)

GEOSPATIAL

DATA

(Assets,

Network)

STREAMING

DATA

(Energy D/S,

Grid Status,

Social Media)

CONNECTED

(BIG) DATA

& Analytics

Connected partners

Connected

employees

Connected smart grid

Connected assets

(Internet of Things)

Building the Connected Utility

Connected Data - example A: scenario analysis & load forecasting for asset investment planning

Asset Management

Peak Determination

(1.5 billion sensor data rows)

Macro-economic, urban, socio-demographic,

technological (EV, PV, …) trend data

Load Forecasting

Bottlenecks

Investments

© Pieter den Hamer, Alliander, 2015

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Connected Data - example B: Realtime Asset Condition Monitoring (pilot)

© Pieter den Hamer, Alliander, 2015

Connected Data - Example C: (research phase): self managing & healing grids

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Main features:

• Dynamic reconfiguration of net

topology for resiliency, net loss

reduction, incident impact

minimization & graceful degradation

• Strong support for Microgrid / local

prosumer ‘energy sharing’ initiatives

• Optimize use of (local) renewable

production & storage, minimize

central energy production

• Dynamic energy pricing for

prosumer behaviour incentivizing &

(local) D/S balancing

• Power quality management

Design concepts:

• Orchestration of a ‘shared energy

economy’

• Beyond the Internet of Things:

towards a ‘societal nervous system’

• Smart autonomous systems

• AI - multi agent simulations of the

smart grid as a complex system

© Pieter den Hamer, Alliander, 2015 9

APPENDIX

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© Pieter den Hamer, Alliander, 2015 11

Big data & analytics platform – underlying architecture (high level)

In

tell

igen

ce &

vis

uali

sati

on

la

yer

SAP BW

Smart Grid – Big Data Lake

Data

layer

Basic Asset

Register (Geo-

spatial)

ERP - SAP (FICO, CRM, ISU, etc.)

GIS (NRG)

Other GRID

(OMS, DMS, Scada, …) Sou

rce

syste

ms

EXTERNAL (EDSN, Social, …)

Process Mining

Enterprise Data Warehouse (structured

+unstructured)

ODS

Data Provisioning Layer

Open/Linked Data provisioning

Workspace (+ high performance in-database analytics)

Predictive Analytics

Unstructured (CS, ECM, …)

Geospatial & grid Analytics

(Self Service) Reporting & dashboards

Prescriptive Analytics

Model / Rule development

(Self Service) Exploration

Extract Transform Load / Replication

Data quality insight

Data

str

eam

ing

Event detection

& orches-tration

Visualization & Interaction

(Work in Progres)

BO Information Steward

BO Lumira / BO Analysis

for Office / Esri ArcGIS

BO Webi / BO

Dashboard / Esri ArcGIS Esri

Perceptive ReflectOne R / Matlab / Vision /

Gaia / tbd

SPSS / R / tbd Clickscheduler / tbd

BO Lumira / Esri / tbd

HANA + IQ

HANA Oracle Oracle Oracle

BO Data Services Oracle

Streams / SRS

HANA + IQ

(Work in Progress)

(Work in Progress)

Conclusion: big data-driven innovations … we’re just getting started !

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Asset Management &

Operations

• Investment planning &

optimization

• Predictive, condition based

asset maintenance

• Outage risk analysis

• Maintenance scenario

simulations

• Augmented reality for

workforce support

Grid Management

• Outage detection, localization

& control

• Realtime load (demand &

supply) forecasting

• Power quality monitoring

• Grid configuration simulations

• Technical net loss reductions

• Self healing grids

Customer Care

• Communication localization &

personalization

• Fraud/theft detection

• Social media outage detection

• Energy prosumer behaviour

analysis

• Energy saving potential analysis

• Customer Energy Insight services

• Open & linked data sharing

• Dynamic energy pricing