This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under

Grant Agreement No 731148.

Smart system of renewable energy storage based on INtegrated EVs and bAtteries to

empower mobile, Distributed and centralised Energy storage in the distribution grid

The INVADE software platform

eSmart – Stig Ø. Ottesen, Knut H. H. Johansen

INVADE Exploitation Workshop

Copenhagen 06/03/2019

Agenda / Content

1. Role in INVADE

2. Achievements so far

3. What is eSmart Systems?

4. Ambitions in the project

5. Business case and target stakeholders

1

Role in project

2

Role in project

3

1. Have information about

flexibility sources, contracts

and flexibility services

2. Collect meter values every

15 minutes

3. Use machine learning to

predict production,

consumption and available

flexibility for near future

4. Use optimization

techniques to find optimal

ways to utilize flexibility to

obtain pre-defined

objectives

5. Send flexibility plans to

local systems

Achievements so far

4

1. Developed first version of

Integrated INVADE Platform

2. Ready to receive data and run

flexibility services for the pilots

3. First customer outside INVADE

consortium already up and

running

4. Lot of interesting business cases

from INVADE exploitation

What is eSmart Systems?

© www.esmartsystems.com

At eSmart our mission is to build digital intelligence to provide exceptional solutions to our customers and accelerate the transition to sustainable societies.

Proven Products with an Increasing Market Traction

Connected Drone: Analytics software for infrastructure inspections

Connected Prosumer: Analytics software for distributed energy resources

+ Improves infrastructure inspections through image recognition analysis

+ Automatic detection of grid anomalies (e.g. missing components, objects on power lines), ability to analyse 180,000+ images in less than one hour

+ Benefits the utility by more efficient inspections and analysis of data and in turn improved maintenance of the grid

+ Increases the utilization of distributed energy resources though AI-powered predictions of consumption and generation and sophisticated optimization models

+ Benefits the prosumer with higher utilization of energy resources and reduced power bills

+ Benefits the utility by enabling energy flexibility to relieve grid constraints and postpone investments

eSmart and AI - Background

8. February 2019

Institute for Energy Technology (IFE)NOK 10 billion invested in R&D focused on Applied

AI, Real-time Data and Advanced IoT

International co-operative effort affiliated to OECD (Organization for Economic Co-operation and

Developmentin in Paris) – hosted and run by IFE

Gunnar Randers together with Albert Einstein in 1939 Einstein’s home - Long Island, 1939.

Background – Applied AI in Critical Processes Started 1985 in Halden

eSmart - Focus on AI

Global attention #1 in Grid Analytics Competition in US Among top 4 Microsoft AI partners

out of 2600 AI companies

Knut H. H. Johansen © eSmart Systems

eSmart Systems & AI

AI & Machine LearningTop 100 Influencers and Brands

#30 @josephsirosh

eSmart Board of Directors

Source: Onalytica

An irreversible and dramatic change in human history

Three technologies converge into

extreme power

Exponential growth in volume of available data

Digital Technology Convergence

Exponential growth in computational power and storage

Exponential growth in development of sophisticated AI algorithms

a revolution

Alpha Zero

2017Learned by self-play alone …

…. in 9 hours !!

Tabula-rasa – No prior hard-coded knowledge

played 44 million games against itself

Artificial Intelligence – example – Alfa Zeroa chess-playing computer

If AI can create the worlds best chess player in 9 hours

what can AI then do for your business?

Knut H. H. Johansen © eSmart Systems

Artificial Neural Networks – Early Stage

Source: Cybercontrols

Knut H. H. Johansen © eSmart Systems

Deep Learning (Neural Networks) - Today

Source: NVIDIA

Knut H. H. Johansen © eSmart Systems

Deep Learning (Neural Networks) - Today

Input Output

Deep insight in utility operations and planning

Domain Insight

IoT, Storage, Graph,

Security, Microservices,

Data

EngineeringDeep learning, detection, prediction, segmentation, recommendation

Machine

Learning

Domain Insight

Data Engineering Machine Learning

© www.esmartsystems.com

Leveraging smart meter (AMI) data to improve operations and recover lost revenues

• Jacksonville, Florida – smart metering (AMI) of

water and electricity – 300 000 customers

• 7500 truck rolls a year to check zero

consumption meters - 80% are wasted

• Advanced analytics to estimate likelihood of

broken water meters

• 86.5 % prediction accuracy

• Annual net value for JEA $1.1 million

Ambitions in the project?

New application of energy flexibility

Large scale demand response for Norwegian TSO Statnett

Connected ProsumerDemand side management to solve transmission-level challenges in northern Norway

+ A solution for Statnett, the Norwegian TSO

+ Delivery: A system providing Statnett the possibility to manually disconnect load through a dashboard at Statnett’sown control center

+ Project headed by eSmart Systems

+ Project management

+ Software development

+ Cooperated with several sub-contractors:

+ Load provided by balance responsible parties

+ Statkraft and Ishavskraft

+ Load from industrial, public and residential sectors

+ Hardware provided by E2U Systems

SWEDEN

420 kV power line300/220 kV power line132 kV power linePower stationSub station

NORWAY

Polar Circle

Connected ProsumerDemand side management for commercial prosumers

Energy assets+ Solar PV generation+ Thermal storage+ Battery storage+ Flexible forklift charging

eSmart deliveries+ Intelligent energy management dashboard

+ Predictions+ Optimization+ Activity based energy control

Pain relief: energy management to reduce energy costs and increase energy resource efficiency

Energy assets+ Solar PV generation+ Thermal storage

eSmart deliveries+ Intelligent energy management dashboard

+ Solar monitoring+ Predictions+ 100 kW regulatory limit

Pain relief: avoid costly peak power tariffs, and optimize the utilization of local PV production

Energy assets+ Solar PV’s+ HVAC systems with heat recovery+ Large electric boilers+ Thermal storage

eSmart deliveries+ Visualization of energy flow (public)+ Predictions for loads and available

flexibility+ Dynamic “smart” EV charging

Pain relief: avoid costly peak power tariffs and to provide a common energy platform across a diversified portfolio of shopping malls and equipment

DER monitoringDER and activity data streams

monitored real-time

DER schedulingDemand side flex utilized for

optimization scenarios

Demand side flexibility market bidding

Aggregated flex portfolios optimized for market bididng

Monitor IoT – energy assets

+ Collect data

+ Aggregate

+ Monitor

+ Visualize

Intelligent decision-support for

scheduling flexibility portfolios to

optimize value according to

+ ToU

+ kWmax control

+ Self-balancing

+ EV charging capacity

optimization

The Connected Prosumer Product

Intelligent decision-support for

bidding flexibility portfolios

according to

+ Multi-market bidding strategy

(“Maybid”)

+ Offered by many

+ IoT and HW-integrations

+ Data management

+ Solved without AI

+ Offered by many

+ Can be solved with AI

and optimization, but in

many cases it is not

needed

+ Few if any players at the

moment

+ Complex flexibility

modelling

+ AI and optimization

needed

Main processes of Connected Prosumer

Business case and target stakeholders

Product Adaption Life Cycle – Connected Prosumer

The Chasm – ideal point to enter the market

Source: Geoffrey Moore - Crossing the Chasm

Early market Mainstream market

enthusiasts visionaries pragmatists conservatives skeptics

It is the ability to quickly segment and activate reference customers –putting the right customer in front of the right prospect – that is the key to crossing the chasm and solidifying a foothold in the mainstream market.

Push from eSmart

No Pull from Prosumers

First Pull from

Prosumers

Target segments with current customer examples

+ DSO’s

+ TSO’s

+ I&C prosumers

+ Energy retailers

+ Power infrastructure operators + Middle-sized utilities

+ I&C prosumers

Business model – Software as a Service

Specification SaaS

1-4 weeks 3+ years

Direct

SaaS

PoC to SaaS Specification Customization PoC SaaS

1-2 weeks 4-6 weeks 3 months 1-3 years

Development project SaaS

1-3 years 1-3 years

R&D to SaaS

+ The direct way to SaaS contract

+ Period of work prior to start of SaaS relatively short with specification and customization to customer needs necessary before starting SaaS contract

+ Typically takes 3-6 weeks combined

+ Recurring revenue from start of SaaS. SaaS contract length initially 1-3 years

+ Proof of concept (“PoC”) contract in which a customization and proof of concept phase is added

+ PoC period provides extra comfort to customer when purchasing new solutions

+ Option to start SaaS subscription with initial length of 1-3 years given successful PoCphase

+ Nature of R&D or project is less commercial than two examples above

+ Development project phase naturally takes up majority of project time

+ Billing in both phases of project (development is paid)

• Note: Black arrows/lines indicate timing of signature/commercial agreement

This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under

Grant Agreement No 731148.

Any question or comment?

Thank you!