2023

THE BUZZ ABOUT ENERGYD ATA & W H E R E T O F I N D I T
Facilitating cross-sectoral
exchange of energy data

CONTENTE XECUTIVE SUMMARY
1.

3

MA XED-OUT GRIDS & NEW OPPORTUNITIESD R I V E D E M A N D , N E W I N I T I AT I V E S
F O R E N E R G Y D ATA

2.

4

WHERE TO FIND PROMISINGE N E R G Y D ATA S O U R C E S

3.

8

D E S I G NIN G A FU T URE- RE A DY
SMART METERING L ANDSCAPE

4.

U N L O C K I N G E N E R G Y D ATA —­A GOVERNANCE VIE W

5.

12U N L O C K I N G E N E R G Y D ATA —­SMART METER ARCHITECTURE VIEWCONCLUSION

2

10

14
16

KURT BAESIRENE MACCHIARELLI

Partner, Energy & Utilities
Brusselsbaes.kurt@adlittle.com

Partner, Energy & Utilities
Romemacchiarelli.irene@adlittle.com

SAM CLAUWAERTNELE VANDE VELDEManager, Energy & Utilities
Brusselsclauwaert.sam@adlittle.com

Business Analyst, Energy & Utilities
Brussels
vandevelde.nele@adlittle.com

ARTHUR D. LITTLEEXECUTIVE SUMMARYEXPLO R I N G OPPORTUNITIESI N EN ERGY DATA
Increased electrification across society to meetclimate targets, paired with European and local
legislation, has put pressure on every level of the grid,
while creating opportunities for existing and new market
players. In addition, end consumers are looking foractive opportunities to valorize their energy-efficiency
investments, like solar photovoltaic (PV), heat pumps,
electric boilers, and home batteries. Service providers
are eagerly scouting for new opportunities to create
value by leveraging the skyrocketing amounts of datathat accompany these changes.
Although the opportunities for commercial energy
market players to offer energy services are vast, one key
barrier is preventing fast innovation: access to energy
data. The demand from existing and new market players
has increased steadily and continually and will continue
to do so.
In this Report, we identify systems and parties who
are trying to retrieve the data and explore relevantenergy data use cases. We examine these cases throughthree different lenses: how to facilitate energy data
access through smart meters, how to meet governancerequirements, and finally how to incorporate the IT
system perspective. The opportunities are indeed huge
— catching and exploring them is the challenge.

3

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

1. MAXED-OUT GRIDS & NEW
OPPORTUNITIES DRIVE DEMAND,N E W I N I T I AT I V E S F O R E N E R G Y D ATA
The energy transition is driving the uptake ofmaintenance and toward new asset investments

renewable energy sources and the electrificationand digital innovations. Indeed, the energyof overall energy demand. The resulting steep

transition is attracting many new players to theincrease of intermittent energy production

game who are putting increased pressure on theand new electric loads are putting pressure on

grid players to access and draw insights fromevery voltage level in our energy networks (seedata that measures energy consumption.

sidebar “Addressing the problems of increased
consumption and renewable energy”).

These constraints not only limit the economic

Legacy gold-plated distribution networks

hamper the energy transition as clean energy

have reached their limits of capacity, pushingstruggles to find its way to the grid. Meanwhile,

many distribution system operators (DSOs)

new loads for e-mobility, like charge poles, andand transmission system operators (TSOs) into

data center infrastructure are being impeded in

unknown territory, as the focus shifts away fromalready highly regulated areas.

growth potential of certain regions; they also

Addressing the problems of increased consumption and renewable energy
Germany and Luxembourg predict congestion

Upscaling the physical grid infrastructure torisks in the near future, while Denmark and Italy

increase capacity is labor- and cost-intensive

have already experienced grid congestion fromand requires multiple years of development.

renewable energy overgeneration. Denmark now

Therefore, more and more TSOs and DSOs arelimits its renewable energy generation, and Italy

investigating a complementary strategy ofplans to double investments in renovation andactivating congestion management where

grid digitization. The Netherlands has experienced

consumers agree to shift consumption andregional events where new connections were

injection at peak moments in exchange

prohibited due to capacity shortages on thefor compensation. To facilitate correct

high- and medium-voltage levels.

compensation for low-voltage congestion
management, smart meters are essential toproviding insight of household consumption

on a granular time-of-use basis.
Figure A. Highlights of Europe’s energy congestion-related
problems
Figure A. Highlights of Europe’s energy congestion-related problems

Predicted
congestion risks

Renewable energy
production halted

Generating renewableenergy overloads the gridGermany & Luxembourg

The Netherlands

Denmark

Italy

Energy grid stress tests show
substantial risks for futurecongestion

Capacity shortages led large energy
consumers & producers to go on
waiting list before they could
connect to grid

Capacity of grid is sometimes too
limited to transport all produced
renewable energy, so energy
producers need to pause it

Increased generation of renewableenergy causes overload of grid &congestion, visible by electricity
interruptions & overheating of
infrastructure

Source: Arthur D. Little

4

New
connections blockedARTHUR D. LITTLE

New players entering the market can help
enable the ecosystem to resolve the emerging
grid challenges. They can offer services tomanage energy consumption, which provides
greater insight for the end clients and market
parties, ultimately creating more energy

COUNTRIES TAKINGINITIATIVE S TO UNLOCK
E NERGY DATA TO TH E
MARKET

flexibility in the market (see Figure 1).

Across the globe, countries are centralizing

The changing landscape calls for existing

facilitation of distributing energy data.

players to expand or adapt their offerings. Both
new and existing players typically need accessto metering data and other diversified energy
data products. Going forward, data access andsupport for developing data-sharing use cases

their energy data as one step toward easier

There is no one-size-fits-all approach thatapplies to every market when considering all
the possible data-sharing architectures. Legacy
processes and legislation are the main drivers

are necessary to provide value-adding services.

of data-sharing market designs in each country.

While access and participation to build energy- In most countries, the smart meter data value

data use cases often exist for establishedsystem market parties and processes, newparties keen to build on energy data insights
find their access is often very cumbersome
or is not facilitated at all.

Some noteworthy trends include:

chain is mostly owned and operated by DSOs

and/or TSOs, where in some cases centralized
entities standardize communication (e.g.,
Atrias in Belgium, Australian Energy Market
Operator in Australia, SII in Italy).

- In Italy, a central system (SII) managed by aOpen energy data sharing

public company was created in 2010 (but still

To optimize the overall energy system cost,
open energy data sharing should be promoted
and embedded in regulatory mechanisms.
Effective data governance at market levelmust be in place to enable new and existing
players to establish energy data use casesthat generate value.

not finalized) to store data from end consumers(both gas and electricity); a second wave ofsmart meter rollout is ongoing and will allow for
an increase in granularity of data, opening newopportunities for data valorization.

- In Nordic countries, centralization is taking placeacross borders. Enacting central hub interaction
reduces market-entry barriers for commercial
players who do business in the region. In
addition, centralization offers possibilities for
distributed energy proliferation via renewables
and demand-side flexibility.

Figure 1. Energy market dynamics and energy data usage
Figure 1. Energy market dynamics and energy data usage

Rapidly changing
energy landscape

A shift inlandscape players

Increasing needfor energy data

End client in control
at optimal cost

A rapidly changing energy
landscape brings newchallenges & opportunities.
There should be fullcommitment to flexible &controllable data chain where
digitization supports fast
data transfer.

This results in a change of
behavior with existing players& new players that wish todevelop new services &optimize operations throughenergy data. Therefore,
central, uniform access toenergy data is needed.

Increase in players requires
increasing disclosure ofvarious energy data products
from meter data landscape.
Disclosure to market must be
performant and offer
diversified data.

It is important that the end
customer is always in controlof their data disclosure, which
is facilitated at optimizedsocial cost.

Source: Arthur D. Little

5

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T- Privacy risks accompany the increased dataexchange, necessitating a transparent

overview of the data shared with market
parties. New entities are created to hostcentral consent registers to log data
authorizations, which allows commercial-

entities to use the energy data of end clients.
A review of the data collection reveals an
increasing variety of different data types,
which provides flexibility and congestion
services such as voltage and frequency data,
combined with price signals. The data opens
a door leading away from the core business ofmetering data toward diversified commercial
energy data offerings. However, this change
often conflicts with the regulatory roles andresponsibilities of grid operators. TSOs and/or DSOs are introducing nonregulated entities
to avoid regulatory conflicts and enter new
services like re.alto and EnergyDataDK, which
was developed by the Technical University ofDenmark (DTU) and its partners (see sidebar“Energy insights accelerate energy use
optimization”).

6

Energy insights accelerateenergy use optimization

Re.alto SRL, a nonregulated entity of Elia
Group, maximizes an energy data API
marketplace with the ambition to accelerate
digital transformation and decarbonization.
It provides energy suppliers with access tonear-real-time data from electrical homedevices, such as digital meters, electricvehicles, solar photovoltaics, batteries, heatpumps, and boilers, directly from the devices
themselves, without the need for additional
hardware. On the other hand, the marketplace
offers a broader set of energy services via
100+ energy APIs to optimize the end user’s
electricity supply, storage, and output.

ARTHUR D. LITTLE

7

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

2. WHERE TO FIND PROMISINGE N E R G Y D ATA S O U R C E S

Energy data can originate from two major
distinct sources:
1. Traditional system market players — grid
operators, balance responsible parties, energy
suppliers.
2. Nontraditional market players — thereal estate sector, original equipment
manufacturers (OEMs), e-mobility providers.
Both sources are introducing new products andservices, generating a richness of energy data
relevant to the operations of the evolving energy
landscape. They can use the raw data that is
directly disclosed at the smart meter or thevalidated data that is transferred via the data

Technical registers
The introduction of smart meters has given
system market parties insight into a goldmineof consumption data. Collecting technical datasuch as meter event information (e.g., outages),voltage information, and peak power can
provide a grid company with a 360-degree viewof the meter that supports asset management
and system operations. Real-time voltage
information helps grid operators visualize andmonitor the low-voltage network and perform
data-driven congestion management. On
the other hand, peak power data shows whenhousehold consumption is highest, leading toenergy allocation based on new mechanisms,

chain, depending on the product or service.

such as dynamic capacity tariffs. This method

In some countries, it is or will be required by law

sidebar “Introducing capacity tariff in Belgium”).

will be introduced in Flanders, Belgium (seefor traditional data registers to provide certain
data products to the market for free. This ishappening already in the Netherlands, where grid
operators, closed distribution system operators,
and parties responsible for meters must disclose
specific energy data products for free.

DATA F ROM T R AD I T I ONAL
SYST EM M AR KET PLAYE RS
Consumption & injection registers
By far, the most valuable energy data source
comes from the electricity consumed by andinjected into the grid. As we are transitioning
toward a supply-driven energy landscape (anincrease of variable, weather-dependent energy
sources) while also becoming more electricityintensive, there is a growing need for granularand near-real-time energy data to perform
effective and automated demand-side control.

8Introducing capacity tariff in Belgium
In January 2023, a dynamic capacity tariff
was added to energy bills in Flanders,which represents around 60% of Belgium’s
consumers. Going forward, the grid fee
on energy bills will include a dynamic

component based on the month’s highest
consumption peak (in kW), which is averaged
with the consumption peaks of the last
12 months. This encourages consumers withsmart meters to avoid using many different
electric devices at the same time or to
optimize auto-consumption from rooftop
solar panels.

ARTHUR D. LITTLE

Asset data
In addition to energy usage information, asset
data about the meter is useful for system
market parties, mainly for system operators. It
includes general meter information such as its
age, type, and capacity; it also shares schedulesof recent and upcoming software updates andmeter maintenance. This data allows system
market parties to anticipate potential problems
with reading meter data.

A tool to evaluate the impact
of energy transition

With support from Arthur D. Little, two
Italian DSOs developed an energy transition
tool to leverage a wide range of energy data
sources (electricity consumption curves fromsmart meters, buildings’ energy efficiency
ratings, heating plants registers, e-mobility
data, decarbonization targets, etc.). They
aimed to evaluate future gaps in grid

capacity. This tool will allow the DSO to

DATA F RO M
NON T R A DI TI ON AL
MA R KE T P LAYER S

develop an asset development strategy
based on scenario analysis, including
consumption, peak demand, and metering
points, to review and enhance its networks’

Diversifying data types allows new market
players to combine metering data with external
data to introduce new services. New sources

capital expenditure plans accordingly, andto evaluate the potential role of flexibility
services mechanisms.

of energy data are being unlocked; theseinclude real estate registers and government
demographic registers. OEMs provide anothersource of data, especially from heat pumps,
electric boilers, washing machines, and chargepoles (see Figure 2 and sidebar “A tool toevaluate the impact of energy transition”).

Figure 2. overview of energy data sources
Figure 2. overview of energy data sources
NON-EXHAUSTIVE

SMART METERINGASSET MANAGEMENT/SYSTEM OPERATIONSREAL ESTATE REGISTERS

GOVERNMENT/MUNICIPALITIESOEMsOTHERS

Energy-consumption data

Access point information

Electricity system
conformity certification

Community/household
demographics

Behind-the-meter installed
devices & capacity

Pricing forecasts ofelectricity & gas

Energy-injection data

Congestion areas

Energy-efficiency rating

Life support customers

Consumption patterns

Solar & wind-specificweather forecasts

Peak capacity

Planned & forecasted
connected capacity

Energy-efficiency
characteristics

Granted energy-related
subsidies

Available flexibility& time windows

Forecast of sustainableenergy generation

Event information

Maintenance/
outage events

Roof size & orientation

Roof size & orientation

Real-time consumption
information

Predictions of EV
driving & charging

Frequency/voltage data

Charging infrastructure

Property age & last
renovation date

Property age & last
renovation date

Performance &maintenance info

Balancing volume &price information

Utility
Source: Arthur D. Little

9

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

3 . DESIGNING A FUTURE-RE ADY
SMART METERING LANDSCAPE

Understanding smart meter data sources is key
to retrieving the right data for its corresponding- Demand response. More granular data isneeded to enable residential demand response,

use case:as these events can be triggered, for example,- Energy-efficiency monitoring. Green loans

from 2 pm to 5 pm. Daily aggregated data willrenovation energy-efficiency improvements.

(equal to one every 15 minutes), which enables

are granted based on a building’s post-

The required data points don’t need to havehigh granularity; they do not need to bereal-time or instantly available, either. Instead,efficiency improvements can be identified andassessed by creating an energy consumption
profile. An energy consumption profile basedon aggregated data taken before and after therenovations should be sufficient to identify andassess the energy-efficiency improvements.

not be sufficient here. Typically, most European
countries already take 96 meter readings per day
effective demand-response market support.

- Congestion management. A grid operator
needs near-real-time or real-time voltage
information on the street or household
level to effectively enable local congestion
management and initiate the necessary
dispatch actions. Acquiring this data in atimely manner once a critical congestion event
occurs is a key step in addressing the problem.
The principles above capture key design criteria
for a future-ready smart meter data value chain(see Figure 3):

Figure 3. A smart meter value chain with design principles
Figure 3. A smart meter value chain with design principles
Systemstep

Behind-the-meter
devices

Responsible

OEMs

Functions• Potential to unlock& control flexibilityof smart high-load
devices• Home energy mgmt
system enables
energy mgmt

Smart meter

Data collectors &headend system

Meter data
management

Asset
management &system operations

Central market
system (CMS)

Suppliers/energy dataservice providers

Distribution system operator• Meter reading• Meter data(consumption,communication
injection, event, • Firmware updates
technical data)• Meter registration• Event registration & configuration• Remote control• Meter data
validation,
estimation& editing• Consumption
calculation

CRM/billingsystems• Meter installation • Meter data
& replacements
centralization• Outage & anomaly& market disclosure
detection• Meter mutation• Network• Consent mgmt formonitoring
third-party use• Commodity invoicing• Energy mgmt
• New product &service offerings

1 Modular metering value chain allows for integration of new utilities data points (e.g., hydrogen/heat) and can flexibly adapt to new requirements
2 Controllable consumption behavior in line with …

… available net capacity

3 Uniform data access to scale with increasing needs of market
4 Diversified metering landscape discloses a variety of meter data products in line with market needs

Designprinciples

5 Performant metering landscape scales with uptake of new players & high increases in data requests
6 Secured metering landscape aligns with risks & data-privacy requirements of exchanged data products from meter to market
Consumer control ensures data privacy & transparency in use

7 of data by external parties
8 Affordable societal cost aligns with value case & TCO of envisioned metering infrastructure
9 Customer-centricity in meter value chain with a focus on easy, transparent & timely handling of client requests

Source: Arthur D. Little

Source: Arthur D. Little

10

ARTHUR D. LITTLE

1. Modular metering value chain. The meter

5. Performant. The architecture must bedata value chain should be flexible enoughprepared and scalable to process increasing

to adapt to uncertain future scenarios andamounts of data.

requirements in the energy landscape. It
should allow for easy integration with system
operations and asset management andfacilitate the introduction of new utilities
such as water, hydrogen, and heat.
2. Controllable. Introducing more variable
and sustainable resources makes the energy
landscape driven by supply, instead of demand.
Monitoring and steering the behavior ofend consumers will be required to optimallymanage the grid and prevent power outages.
3. Uniform data access. Data must be equallyaccessible to all parties with permission touse it.
4. Diversified. Smart meters can disclose morethan consumption data. Insights that focus on
events, voltage, and generation can be shared
to inform emerging use cases.

6. Secure metering landscape. Cybersecurity
should be central to both the processes andarchitecture, given the increasing integrationof metering data into the system operations ofstrategic energy infrastructure. Ensuring data
privacy across the entire chain from source toend user also relies on solid cybersecurity.
7. Consumer control. Full control andtransparency to grant energy data accessto commercial parties should be given to
the consumer.
8. Affordable societal cost. Adapting the meterdata value chain will trigger costs to optimize
in line with the system’s needs and benefits.
9. Customer-centric. The customer’s touchpoints within the metering value chain should
allow for simple, timely, and transparent
handling, with a focus on self-service andfirst-line support enablement.

11

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

4 . U N L O C K I N G E N E R G Y D ATA —A GOVERNANCE VIEW

To meet the challenges of sustainability
and customer-centricity, it is critical forenergy network operators to collaborate
with nontraditional partners, regulators,
and competitors. This cooperation relies on
consumer data from smart meters, but data
sharing is currently difficult due to issues
with quality, governance, confidentiality,
and availability. The complexity and challenges
can be overcome through a combination ofcollaboration and customer-centricity, often
enabled by regulatory push. A regulatory
framework is required to set legislative groundrules for collaboration and data sharing, whichmust be backed by robust customer dataconsent mechanisms and a cross-industry
IT structure to support data exchange.
The Netherlands has initiated a regulatory
framework with these characteristics (seesidebar “Case study — A nationwide energy
data exchange framework in the Netherlands”).

12

A R E G U L AT O R Y
FR AMEWORK ISREQUIRED TOS E T L E G I S L AT I V E
GROUND RULESF O R C O L L A B O R AT I O N
A N D D ATA S H A R I N GARTHUR D. LITTLE

Case study — A nationwide energy data exchange framework in the Netherlands
In the Netherlands, the energy grid operators

decisions made by the MFF. BAS is responsible

initiated a nationwide energy data exchange

for the technical and operational sides of data

decision and implementation framework for all

sharing (see Figure B). In addition, BAS is alsointerested market parties to enable sector-wide

responsible, by law, for setting up a centralized

data sharing. All players were aligned throughenergy data authorization layer. This platform

the Market Facilitation Forum (MFF), a newcovers the identification, authentication, andconsultation and decision-making forum open

authorization of any requests for predefined

to all energy sector stakeholders. A second

energy data product categories.

FigureB.created
Framework
entity, BAS, wasto execute thefor data-exchange decisions andimplementations
Figure B. Framework for data-exchange decisions and implementations
Market Facilitation Forum (MFF)

Administrator Energy Data Exchange Framework (BAS)

Legal format: Association

Legal format: Limited liability company (Ltd.)This entity manages agreements for data exchange used in regulated
energy processes in accordance with decisions taken in MFF;
coordinates & facilitates implementation of decisions made by MFF

This is an open, independent, decisive & binding consultation &decision-making platform for all issues related to data exchange
used in regulated energy processes

Chairman

Disputecommittee

MFF instructs BAS
BAS supports MFF

Secretary

Repr. org.

Repr. org.

Repr. org.

Grid
companies

Systemmarket parties

Non-system
parties

Representative Representative
business
consumer
associations
associations

Activities of MFF• Establish & manage a consultation forum• Facilitate discussions & documentation of market needs & visions• Facilitate decision-making & provide escalation mechanisms• Mandate to BAS for detailed execution

Activities of BAS• Manage market agreements, as established by MFF• Support operation of MFF• Coordinate decision-making in MFF• Develop & manage centralized consent layer

THE CONSENT PLATFORM IS INVOKED THE MOMENT END CONSUMER SIGNS UP
FOR CONTRACT WITH MARKET PARTY THAT REQUIRES THEIR ENERGY DATA
Functional layer
At this layer, service providers
develop applications that use
energy data. Examples include:

Consent platform:

Remote energy-efficiency audits
based on actual usage data

Supplier

Activation of residential
demand responsePricecomparators Bank…

Making real-load profiles available

Unlocking energy data in secure & transparent way bycentrally managing permissions to various data sources.
Three steps: (1) identification: establishing someone's
identity; (2) authentication: confirmation of identity; and(3) authorization: verifying authority to grant permission
to use data in question. The following basic use cases are
distinguished:

Taking full advantage of variableenergy prices when charging an EV(Data) register administrator
Responsible party for read-out, registration& disclosure of energy data registers

Customer manages authorizations given
Customer consents to ad hoc data request
Customer authorizes multiple requests (subscription)
Third party requests customer data…

End consumer’s rights
The end consumer is the person who owns the data.
This person is authorized to grant permission toa service provider to use their data in providing
energy services.

Source: Arthur D. Little

13

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

5 . U N L O C K I N G E N E R G Y D ATA —SMART METER ARCHITECTURE VIEW

Four main metering landscape archetypes

Internet of Things, while the core meter’s

are presented below (see Figure 4), ranging

tasks are limited to measuring the electricity

from heterogeneous, slow, point-to-point data

flow. This offers the possibility for real-timesharing to a highly homogeneous meter data

data disclosure to support the introduction

value chain with local real-time data disclosure.

of new advanced applications. Additionally,

1. The first archetype displays a complex

centralized processes. Local processing

hetrogenous and often cost-ineffective
setup. Meter data is delivered after a long

delay to the market, where every market party
requires a point-to-point nonstandardized
integration with each individual DSO or otherdata-disclosing entity.
2. In the second archetype, the decentralized
heterogenous point-to-point integrations are
unified in a central market system (CMS),
facilitating ease and uniformity of exchange
across market parties. The process for incident
analysis and handling data-exchange issues
where data was not delivered is cumbersome
because of the individual DSO’s customized
Advanced metering infrastructure(AMI) landscapes, which enable two-way
communication with the digital meters.
3. The third archetype is characterized by uniform
data handling closer to the smart meters. All

heterogenous decentralized AMIs are reduced

to one uniform AMI functionality that collects
data of all smart meters. This is possible throughone central application operated by all datadisclosing entities, or multiple applications,operated by the individual entities, that run thesame software and business logic. The central
asset register from the central market system
must be maintained in order to deliver data to
the correct market parties. This register collects
all the contracts between market parties andconsumers as well as mutations such as moves
and switches.
4. The last archetype introduces a local

edge gateway on the meter. The gateway
calculates and communicates, supported byedge technology, artificial intelligence, and14

local processing allows for offloading heavy

lowers the risk for security breaches by

avoiding duplications and dispersions of

personalized data in centralized systems.
The UK market has gateways already in place
for pure communication purposes, but in the
Netherlands, the commercialization of an edge
gateway with extended functionality is being
explored.
The communication functionality of the CMS
and the centralized AMI focuses on data
export. A parallel data lake can be constructedto perform further calculations and create
aggregates with the collected data without
interrupting the core data-export processes.
This system needs to be highly available andhigh-performing, accessible via APIs by many
concurrent users. Similar API structures arebeing used in open banking, as explained in
the case study.
Regardless of structure, there is no doubt thatthe amount of collected data will significantly
increase in the near future. Introducing acentralized consent platform to manage larger
volumes of data is increasingly important. The
platform’s process has three steps, which werefer to as IAA: identification (establishingsomeone’s identity), authentication(confirming their identity), and authorization(verifying authority to grant permission). The
consumer receives a clear overview of all theauthorizations he or she has given. In the caseof the decentralized gateway structure, it
is possible to have local IAA functionality tocommunicate data directly from the smart
meter to the market party without passing
through a central metering system.

ARTHUR D. LITTLE

Figure 4. Metering landscape archetypes
Figure 4. Metering landscape archetypes

1

2

Heterogeneous point-to-point data sharing
SmartmetersAdvanced metering
infrastructure (AMI)

Market connector

Marketparties

Centralized energy data hub

SmartmetersAMI

Marketconnector

CMS

Marketparties

Each DSO has AMI & market connectors to disclose data. This obliges
market parties to design their IT systems to be compatible with market
connectors of each DSO.

In CMS, data of all AMIs is centrally collected & distributed in a uniform
way to all market parties. Issues can, however, still occur inheterogeneous AMI landscapes.

3

4

Smart
AMI
meters
Source:Arthur D. Little

Centralized AMI
Marketconnector

CMS

MarketpartiesEdge-enhanced & near-real-time data sharing

SmartmetersAMI

Marketconnector

CMS

Marketparties

Central asset
register

Central asset
register

Edge gateways

Edge gateways

Edge gateways

Further uniformization is possible when all AMIs are combined to one
single system that collects data from smart meters & directly
communicates it to market parties. This eliminates role of CMS for data
distribution. Only a central asset register is retained separately
for meter mutations.

Local (real-time) data delivery

When edge gateways are connected to smart meters, they offer asecond pathway to share data with market parties. Data is directly
delivered to the market parties in near real time without passing thecentral AMI. Both pathways will coexist because the calculation of theenergy balance for allocation & reconciliation will require centralized
consumption data.

Source: Arthur D. Little

15

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

CONCLUSIONC A PT UR I N G EN ERGYDATA O PPO RT UN I T I ES
There is consensus that energy data will be
the cornerstone in establishing a stable,
secure future power supply. Rethinking how
this data is unlocked and distributed to market

M U LT I P L E E N A B L E R S
ARE THE KEY TO
MA XIMIZING THE
VA S T O P P O R T U N I T I E S
I N E N E R G Y D ATA

participants in a uniform, transparent way
should be a top priority. Failure to understandand quality of the energy supply and missing- End consumers will be pursued by third parties

new (commercial) business models. In thisoccurs beyond the energy sector, in financial

this landscape means jeopardizing the security

Report, we highlighted the need for better
open data, explored traditional and new sources,
showed the benefits of smart metering, andrecommended setups for governance andarchitecture. Ultimately, multiple enablers are
the key to maximizing the vast opportunities
in energy data. Although specific regions, suchas the EU, are forerunners in using energy
data, the opportunities and challenges will be
relevant across the globe. Key takeaways formarket players include:- Open energy data sharing should be promoted
and embedded in regulatory mechanisms tooptimize the overall system cost of the energy
landscape.

- An effective data governance forum on market
level accelerates collaboration and use casedevelopment and encourages joint decisionmaking among new and existing players.

- Stricter privacy legislation will protect theend consumer and give them full controlof their data. Investing in quality user
experiences across the energy data value
chain will promote participation and use
case valorization.

16

wanting to exploit inherent data value. This

services, automotive, telecoms, and others.

- Countries are developing centralized consent
management to enable transparency andcontrol of energy data utilization; IT platforms
facilitate end consumer IAA of energy data
usage for products and services.

- There is no “one size fits all” for data sources.

Specific sources need to be tapped into basedon use case. Understanding the energy data
value chain and its possibilities and limitations
is critical in assessing a new energy product orservice’s viability.

- Data register operators should focus on
standardizing the end-to-end meteringarchitecture with modularization andsecurity at its core to keep pace with fastevolving trends and higher numbers of datatransactions.

- Metering architecture must be redesigned to
unlock real-time energy data use cases andsupport direct data distribution from the meterto the authorized market party. Maintaining
central infrastructure will ensure calculationof the energy balance to perform allocation
and reconciliation activities.

ARTHUR D. LITTLE

NOTES

17

R E P O R T: T H E B U Z Z A B O U T E N E R G Y D ATA & W H E R E T O F I N D I T

18

ARTHUR D. LITTLE

19

Arthur D. Little has been at the forefront of innovation since1886. We are an acknowledged thought leader in linking
strategy, innovation and transformation in technologyintensive and converging industries. We navigate our clients
through changing business ecosystems to uncover new growth
opportunities. We enable our clients to build innovation
capabilities and transform their organizations.
Our consultants have strong practical industry experience
combined with excellent knowledge of key trends and dynamics.
ADL is present in the most important business centers around theworld. We are proud to serve most of the Fortune 1000 companies, inaddition to other leading firms and public sector organizations.
For further information, please visit www.adlittle.com.
Copyright © Arthur D. Little – 2023. All rights reserved.