Towards Cost-Effective Utility Business Models

Selecting a Communication Architecture for the Rollout of New Smart Energy

Services

Toni Goeller

, Marc Wenninger

and Jochen Schmidt

MINcom Smart Solutions GmbH, Rosenheim, Germany

Department of Computer Science, Rosenheim University of Applied Sciences, Rosenheim, Germany

Keywords:

Smart Meter, Advanced Metering Infrastructure, AMI.

Abstract:

The IT architecture for meter reading and utility services is at the core of new business models and has a decisive

role as an enabler for resource efﬁciency measures. The communication architecture used by those services has

signiﬁcant impact on cost, ﬂexibility and speed of new service rollout. This article describes how the dominant

system model for meter reading came about, what alternative models exist, and what trade-offs those models

have for rollout of new services by different stakeholders. Control of a self learning home automation system

by dynamic tariff information (Real-Time-Pricing) is given as an application example.

1 HISTORY OF THE UTILITY

CENTRIC ICT

ARCHITECTURE FOR SMART

METERING

Technology advances in the last 50 years as well as

decreasing prices for integrated circuits and communi-

cation have driven the move from mechanical towards

electronic meters, from manual to automated reading,

and from annual or monthly readings towards more

frequent readings, e. g. in a 15 minute period. The

interesting aspect here is the approach taken to imple-

ment these straightforward developments – either as

a dedicated system solution for a speciﬁc problem or

as a generic infrastructure serving multiple purposes

with similar demands. Such demands are:

•

Ubiquity – meters can be almost anywhere in an

area served by electric energy and other metered

services.

•

Medium reliability – a system with extreme geo-

graphic distribution may not be dependent on the

availability of a single element or communication

branch.

•

Cost efﬁciency – low communication cost per ap-

plication using the ICT infrastructure. It is desir-

able when nodes and communication do not in-

cur a ﬁxed monthly cost or cost per transferred

byte, because a ﬁxed monthly cost per element

may break many business cases and a ﬁxed cost

of data may render cost estimates unpredictable.

As an example, assume you calculated the commu-

nication cost based on the small amount of meter

data to be transferred and are confronted with sev-

eral ﬁrmware upgrades of meters which involve a

signiﬁcantly higher data transfer volume.

In the beginning, generic use of the smart metering in-

frastructure was in focus. Theodore Paraskevakos, one

of the frontrunners of automatic meter reading, applied

his invention of Caller ID transmission in telecommu-

nications to ﬁelds as diverse as meter reading (Paraske-

vakos and Bushman, 1980), sensor communication

– at the heart of today’s Internet of Things (IoT) –,

the transmission of video rentals and other applica-

tions. With technology progress, the dedicated op-

timization of systems for the readout of billions of

meters got more attention. Potential customers for

such systems – sales or distribution units of utilities,

or dedicated meter reading service providers – usually

have no business in providing communication services

for elements outside their meter and distribution con-

trol infrastructure. Instead, they are interested in a

complete fulﬁllment of their customer-side tasks by a

single infrastructure:

•

Automated meter reading at deﬁned times and

transmission of the reading data to a data center,

•

Software update for all elements of the meter in-

frastructure, such as the meters themselves, con-

Goeller, T., Wenninger, M. and Schmidt, J.

Towards Cost-Effective Utility Business Models.

DOI: 10.5220/0006759202310237

In Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2018), pages 231-237

ISBN: 978-989-758-292-9

231

Sensor / Actuator

Information System

Meter Data

Management

Headend System

Customer

Utility

Gateway

Information

System

Smart Meter

Energy Service

Application

Sensor /

Actuator

Home

Automation

Data Center

Customer Premises

WAN

Figure 1: Traditional model for the Advanced Metering

Infrastrucure. The utility’s area of responsibility is depicted

on the left, the customer’s on the right. In some components

(e. g. home automation, sensors and actuators), the sphere of

inﬂuence overlaps or depends on the service model.

centrators and data hubs,

• Conﬁguration of meter infrastructure elements,

•

Securing bidirectional communication to inhibit

tampering with reading data as well as modiﬁca-

tion of ﬁrmware running on meters or other ele-

ments of the metering infrastructure.

Such customers are almost always conﬁned to a re-

gion or a country, and are subject to a long history

of national or regional regulation. Thus their interest

for globally standardized solutions is low, since po-

tential cost beneﬁts by global purchasing are offset by

the effort to convince the regulator to drop national

requirements in conﬂict with global solutions. This

is reﬂected in the large number of physical

and logi-

cal communication protocols employed in meter read-

ing systems. For each solution, this means a smaller

market and less competition within its region. For a

system, this means less compatibility among potential

solution components. Besides the fact that national

speciﬁcs in regulation hinder the deﬁnition and adop-

tion of global standards in the metering ﬁeld, the use

of this infrastructure for services beyond its scope and

provided by other organizations would create addi-

tional legal and administrative complications. As long

as the cost of an exclusive meter reading infrastructure

can be ofﬂoaded to customers and/or citizens, tradi-

tional utilities will have little incentive to engage in

services reusing the metering infrastructure.

Narrowband powerline communication like Echelon,

Prime, G3, broadband powerline communication, Wireless

MBus, LoRa, Sigfox, GPRS, LTE, Zigbee, WiFi and Low

Power WiFi dialects, just to name a few.

However, the generic infrastructure tasks listed

above led utilities to plan value-added services of their

own on top of the meter reading communication infras-

tructure. A typical service area is the optimized use of

electrical energy – e. g. by identifying energy-intensive

devices or by optimizing the time-of-use according to

the utility’s incentives. Naturally, the utilities plan to

offer these services over the infrastructure they control

(see Figure 1). At consumers’ homes, small ofﬁces or

workshops, this can be achieved by adding a commu-

nication link between the meter infrastructure and a

home automation system – either an existing one or a

system delivered to the customer as part of a service

contract. As shown in Figure 1, sensors, actuators

and information systems can be connected directly to

the utility driven infrastructure. This model is used in

classic ripple control or with the in-home display of

an external meter. Or, sensors, actuators and informa-

tion systems can be connected to a home automation

system which in turn is inﬂuenced by information is-

sued by the utility via its infrastructure. For the sole

purpose of meter reading dedicated large scale system

rollouts have started about 15 years ago and will be

extending well into the 2030s. This has happened in

parallel to the buildup of other communication infras-

tructure and in parallel to the almost ubiquitous avail-

ability of smartphones supporting WiFi and mobile

data. The pace of alternative communication system

rollouts will further accelerate with IoT sensor deploy-

ment and with applications that rely more and more

on online connectivity. It is not necessarily a bad thing

to have several dedicated systems performing similar

tasks. Some criteria to decide whether an additional

communication system is useful are total cost, total

system complexity (especially complexity of applica-

tions relying on several communication systems) and

the speed of innovation rollout (which may be higher

in a dedicated system). Our question is: Which sys-

tem architecture supports innovation in the energy and

utility markets, which are subject to rapid changes –

some of them with the potential to be disruptive? To

this end, we will look at two examples of cost and

complexity drivers. Then we discuss the evolution of

the economic and regulatory landscape in its inﬂuence

on the usefulness of architecture choices. We have

a look at communication systems available in homes

and small enterprises and discuss which architecture

enables fast and cost-effective rollout of new business

models. For this architecture, we describe a sample

application which is currently being realized.

SMARTGREENS 2018 - 7th International Conference on Smart Cities and Green ICT Systems

232

2 EXAMPLES FOR COST AND

COMPLEXITY DRIVERS

Using a dedicated communication infrastructure

means all costs have to be covered by the applica-

tions having access to and using this infrastructure. In

the extreme case of smart metering, only an annual

reading is necessary to bill a classic residential tariff.

In this case, the meter reading infrastructure has to

transmit no more than a few bytes of useful payload

every year. When we assume that the operational cost

for a smart metering infrastructure is up to 50 Euro

a year compared to a classic Ferraris meter with an-

nual reading, and that the meter reading can be coded

in a 50 byte data unit, we get communication costs

of 1 Euro per byte. When 15 minute readings are re-

quired and transmitted we transmit 35 kByte per Euro

communication cost, or 29.26 Euro per MByte of pay-

load. This is a considerable price, even compared with

the most expensive volume-based mobile data tariffs.

When other applications want to use this communi-

cation infrastructure, its owner will tend to charge a

prohibitively high cost, so that many applications will

become economically unfeasible over this infrastruc-

ture. Thus, third parties very probably will use another

available communication infrastructure.

As mentioned before, the variety of communica-

tion protocols in dedicated metering infrastructures

increase cost and complexity. This is illustrated by the

requirement of a separate display (In-Home Display)

for smart meters in some countries. A separate dis-

play makes sense when the customer has no access to

the meter itself, e. g. when the meters for several apart-

ments are located in the basement of an apartment com-

plex or when the meters are mounted on a nearby pole

to inhibit tampering. Smart meters often have built-in

wireless MBus or PLC modems, but a greater choice

of In-Home Displays exists with Zigbee modems. If

the utility does not want to buy all components from

a single source, it is often penalized by the need for

gateways with protocol conversion. In addition, data

content, presentation and data security from time to

time necessitate software and conﬁguration updates.

Therefore, a secure software distribution and activa-

tion platform has to be developed or extended for each

new integration component like an In-Home Display.

To develop and maintain such a platform is costly and

incurs permanent operating expenses. Furthermore,

professional displays generally offer limited function-

ality at a higher price than consumer goods. When we

look at the In-Home Display problem a second time,

the question is whether we need an In-Home Display

at all. Any old smartphone has more functionality and –

most importantly – comes with a well-established soft-

ware distribution platform. Better still, a smartphone is

available at almost all customers, who have no interest

in yet another display hardware (Gosden, 2015). The

requirement to use this superior and customer-friendly

solution is support of WiFi, the most widespread com-

munication solution. By doing that, solutions from

other industries are immediately available to the utility

industry, yielding immediate cost and customer satis-

faction beneﬁts. The consideration for regulation is

not to specify technical detail, which is often based

on a speciﬁc solution approach and risks to mandate

inferior solutions after new approaches have become

available (see (UK Department of Energy & Climate

Change, 2016) for an example of the lengthy and cum-

bersome process to scale back on technical detail in

regulation).

3 REGULATION AND

ECONOMIC DEVELOPMENTS

Utility services belong to basic needs and competition

on the physical access is rarely feasible for the supply

of energy, water, gas or long-distance heating. There-

fore utility services including metering, transmission

and remuneration of meter readings are highly regu-

lated. Also regulated is the unbundling of generation,

transmission, distribution and sale of electric energy.

In Germany, the operation of metering points is de-

ﬁned as an additional role; due to the security solution

speciﬁc to Germany (BSI-Gateway, smart metering

system) the meter point operator has additional regu-

lated tasks (Smart Metering Gateway Administration).

The combination of role unbundling and regulation of

network charges results in side-effects, which render

offering new services via traditional market roles un-

proﬁtable. For example, sales is burdened with higher

network charges when energy consumption of private

households deviates from standard load proﬁles.

Offering further energy services is usually unreg-

ulated business, at least if they are organizationally

separated from the regulated market roles, based on

a separate contract (opt-in), and obtain the required

meter readings (where necessary) with consent of the

customer using other ways than the ofﬁcial smart me-

ter gateway. Economically, the energy provider market

is developing towards more complex contractual re-

lationships: Distributed energy generation provides

manifold possibilities for optimizing the local or re-

gional utilization of renewable energy sources by per-

sonal and regional use. This helps to reduce necessary

investment in transmission, and to share the resulting

savings. Presently, only one sales contract per end-

customer is foreseen. With self-consumption and the

Towards Cost-Effective Utility Business Models

233

future possibility of local peer-to-peer selling, the tra-

ditional energy sales contract will carry less value in

terms of energy delivered and more in terms of an

insurance to provide a supply guarantee that steps in

when locally produced energy is not available in suf-

ﬁcient quantity. This will – at a pace the regulator

allows – lead to a considerable increase of connection

fees. Possibly, this increase will be compensated by

a decrease in the kilowatt-hour rate. In any case, the

share of sales, and presumably also the total revenue,

that depends on metered and priced readings in com-

pliance with regulation will decrease. Therefore, the

economic beneﬁt of the metering infrastructure will de-

crease further, the “cost of smart metering” to “energy

consumption revenue” ratio will become less and less

favorable, as long as there are no other applications

that use the metering infrastructure.

Applications going beyond pure energy supply usu-

ally require hardware on the customer side. The de-

velopment in the area of home and ofﬁce automation

solutions is currently very dynamic, regarding both

the functionality provided as well as interfaces offered

for device and solution integration. For a utility com-

pany, selecting a home automation solution or a home

automation portfolio and integrating it with its commu-

nication infrastructure therefore poses a high risk. Any

choice would have to be accompanied by continuous

market observation, and must be updated if required,

entailing new integration efforts. The customers’ qual-

ity demands on a solution recommended by the utility

company are higher than those on one purchased di-

rectly from some retailer, putting additional pressure

on the utility’s ability to compete. Also, home au-

tomation provides many functions (comfort, security,

entertainment, amongst others) which are neither in

the utility’s focus nor is it the customer’s expectation

that the utility excels in all application areas of home

automation. And even if the utility or its energy ser-

vice provider offers an attractive package, the customer

may be uncomfortable with external control of his pri-

vate sphere. If the hardware on the customer side is

linked via the same communication infrastructure that

is used for meter readings, the provider is not free re-

garding the integration. In addition to that, speciﬁc

German regulation requires that data ﬂows which are

not deﬁned yet in the smart meter gateway speciﬁca-

tion must be cleared by the Federal Network Agency

(Bundesnetzagentur) and the Federal agency for In-

formation System Security (Bundesamt für Sicherheit

in der Informationstechnik, BSI). Using the regulated

infrastructure for unregulated services therefore poses

a high project risk. This is an inherent problem, as it

cannot be the duty of regulation to identify possible in-

novative business models before the market does, and

adjust the rules proactively to these business models.

Thus, the regulated and the new unregulated ser-

vices in the energy sector should be separated, both

organizationally and regarding the communication in-

frastructures, if delays and uncertainty factors are to

be avoided when launching new services.

4 EXISTING SYSTEMS AND

FURTHER APPLICATIONS

For system optimization the following communication

systems common to residential or ofﬁce areas can be

considered:

Communication infrastructure for smart meter

readings: regulated; completion of nationwide roll-

out in Germany by 2032.

Internet via landline, cable or mobile modem, usu-

ally with WiFi access point: 2016 available in

89.3% of all households (Statistisches Bundesamt,

2017a). Under control of the owner/tenant, re-

garding contracts as well as availability, which

depends, e. g., on whether the modem is turned on

or whether the current WiFi password is known to

the clients.

Internet via smartphone, maybe with WiFi access

point: used in 2017 by 70.5% of all persons aged

10 and above living Germany (Statistisches Bunde-

samt, 2017b). Controlled by the smartphone user;

physical presence of the user, active device as well

as availability of data connection via mobile net-

work required.

Public WiFi: Currently low availability in house-

holds, with increasing tendency in densely popu-

lated areas.

For the regulated application of meter readings the

communication systems 2-4 were rejected early on, as

they are outside the control of the provider, and their

use by the provider might entail considerable coor-

dination effort between provider and communication

contract holder.

By bundling energy and internet supply it would

be quite possible to integrate the communication mo-

dem in the meter, thus guaranteeing the uninterrupted

function of the modem under control of the utility com-

pany or the internet provider. As an opt-in offer this

kind of bundling would be unobjectionable – the net-

work separation between smart meter system and the

customer’s home network could be realized without

difﬁculty using logical network separation functional-

ity provided by modern modems. This model promises

considerable savings, as only a single communication

SMARTGREENS 2018 - 7th International Conference on Smart Cities and Green ICT Systems

234

infrastructure and its operation is required, reﬁnanced

by two utilizations. Unfortunately big utility compa-

nies had substantial concerns, fearing that telecommu-

nication providers would become competitors in the

energy sector, and that they would facilitate market

entry by this bundling model. Still, this approach is

an excellent business model for municipal utilities that

hold shares in local telecommunication providers.

Generally, concerns regarding the reliability of

customer-provided infrastructure cease to apply when

the service is in the customer’s self-interest. In the

application example presented in this paper (Section 6)

this is obtained by providing tariff information via

the customer’s internet link, resulting in lower energy

costs and optimization of the utilization of the cus-

tomer’s own energy sources and storages.

Public WiFi (item no. 4) is the only technology

available independently of contracts with mobile net-

work operators in virtually any smartphone

. The

fact that public WiFi access points become more

widespread is powered by several strongly growing

applications, as it uses the most pervasive wireless

communication technology with the most affordable

chip-sets. It is therefore suitable for communicating

with all sensors and actuators that are connected to a

power supply or have sufﬁcient ambient energy at their

disposal for energy harvesting. For local control and

inspection applications, a common smartphone can be

used over WiFi with authentiﬁcation; dedicated main-

tenance hardware is not required. Further applications

for public WiFi are in-house location-based services

and connectivity offers for citizens and customers. All

these reasons will lead to public WiFi coverage in-

crease in city regions, albeit not a coverage that will

ever come close to 100% of all supplier end-points.

If – as in the case of smart metering – no real-

time communication is required

, in many cases a

secure connection over any smart phone can be used

This requires that smartphone users get incentives for

the data transport. As data transmission using a dedi-

cated infrastructure is very expensive (cf. Section 2),

the budget for such a reward is sufﬁciently large. A

study performed by the TU Munich is available that

Bluetooth is not much worse regarding modem perva-

siveness, but less attractive due to its short range and lower

bandwidth.

For billing a monthly transmission of 15-minute read-

ings is sufﬁcient even for real-time pricing. For measur-

ing feedback in demand-response applications a higher rate

makes sense; as feedback-measuring is a statistical evalua-

tion, obviously not all meter points have to be transmitted for

each feedback-round, as long as the readings can be stored

in the meter or concentrator sufﬁciently long.

In Germany the requirements for a smart meter system

specify that a permanent tunneled connection is mandatory.

Sensor / Actuator

Information System

Meter Data

Management

Headend System

Customer

Utility

Gateway

Smart Meter

Energy Service

Application

Home

Automation

Data Center

Customer Premises

WAN

Internet

Communication

Modem

Figure 2: Providing energy services through dedicated and

public communication systems.

compares costs between traditional meter reading and

readings using existing smartphones (Schwab et al.,

2016).

To conclude: Several communication devices are

available that can be accessed in households, as well as

several applications reﬁnancing a joint communication

infrastructure, thus lowering the application-speciﬁc

costs of communication considerably.

5 OPTIMIZING PROVIDER

ORGANIZATION AND

ICT-ENVIRONMENT

Respecting costs, complexity and regulation, the fol-

low conclusions can be derived:

•

Additional services beyond the regulated ones

should make use of generic communication infras-

tructures and interfaces (LAN, WiFi) in order to

avoid high costs for development and operation

and an increase in project risk.

•

The communication infrastructure does not need

to be the property of the provider, as delivering un-

regulated services is always an opt-in model. This

implies the customer’s interest in service delivery

and provides the service provider with a motivation

for a customer-centric approach.

•

The service should make use of control standards,

or, if not possible, combine quasi-standards to con-

trol or inﬂuence smart home products to avoid the

need for custom hardware.

Thus, it seems advisable that new energy and provider

services are delivered using an existing communication

infrastructure as shown in Figure 2. The protection

of data privacy is governed by generic consumer pro-

tection and privacy rules. Those rules are much more

Towards Cost-Effective Utility Business Models

235

Sensor / Actuator

Information System

Meter Data

Management

Headend System

Customer

Utility

Gateway

Smart Meter

Energy Service

Application

Home

Automation

Data Center

Customer Premises

WAN

Internet

Communication

Modem

Shared access,

e.g. Public WiFi

Smart City

Sensor

Smart City

Application

Figure 3: Communication in shared infrastructures.

generic than speciﬁc requirements on the handling of

meter data and thus apply even to new business models

that did not exist when the regulation was written.

The regulation and role concept of intelligent me-

tering systems are of no relevance in terms of addi-

tional energy services, as they are not regulated energy

delivery services. In this system model, subsidiary

companies of energy providers and other third party

energy service companies may provide their service

by conclusion of a contract with the customer.

In Germany regulations demand intelligent meter-

ing systems to only use tunneled connections, other

countries may not regulate the communication, thus

not enforcing a dedicated communication infrastruc-

ture

. This is shown in Figure 3.

The communication architectures in Figure 2 and

Figure 3 are heavily affecting the system costs and

variety of providers. As a side effect it is also lowering

the entry threshold for IoT applications. Thus, if smart

metering is utilizing and investing in a shared infras-

tructure, it will support the development of additional

local applications. The previous chapter has shown

that it is possible for alternative providers to provide

services without accessing the smart meter infrastruc-

ture. Even the lack of access to energy consumption

readings of the meter operator can be substituted by

measuring consumption using one or several additional

calibrated meters within the customer’s electric circuit.

Possible deviations within the range of the calibration

tolerance are in most cases insigniﬁcant and manipula-

tions can be detected by comparison with the readings

of the energy provider. In a regulated energy market,

traditional energy providers do not have the possibility

to prevent alternative services, they only get to choose

their communication architecture and the resulting in-

vestment costs of their services. The cooperation with

In case the provider makes use of mobile communica-

tion standards such as GPRS or LTE, the metering system

does already utilize a non-dedicated communication system.

Tariff Server

Billing Component

Actuator / Switch

Information System

Home Automation

Billing System

Headend System

Smart-Meter

Smart-Meter Infrastructure

Customer

Provider

Gateway

Real-Time-Pricing

Tariffs

Figure 4: Adaptive home automation guided by dynamic

tariffs.

alternative service providers also results in substan-

tial cost reduction and increase of customer beneﬁts

for traditional providers of energy services and energy

delivery.

6 APPLICATION EXAMPLE

Highly dynamic energy tariffs, known as Real-Time-

Pricing (RTP), are an example for additional energy

services. In (Wenninger et al., 2017) we describe a

generic, incentive-based load shifting method that op-

erates independently from the energy provider’s in-

frastructure by using RTP and a Home-Automation-

Gateway (HAG, see Figure 4). Based on the same

infrastructure, instead of providing highly dynamic

prices as an incentive for load shifting, it is possible to

implement a bonus system where the customer will be

provided with an inducement in form of a bonus while

having a static energy tariff.

The HAG fulﬁlls the task of automatically shifting

loads under the premise of respecting the customers’

habits when using appliances. This minimizes the risk

that load shifts would have negative effects on the cus-

tomers’ habits, which would lead to issues regarding

user acceptance of the automation system. We achieve

this by creating user proﬁles based on high resolution

energy data, which provides insight into the residents’

appliance usage habits. Based on this proﬁling, it

is possible to predict the probability of appliance us-

age, thus only scheduling load shifting tasks within

the user’s comfort zone. Through an information sys-

tem the customer can be provided with incentives for

manual load shifting of appliances that cannot be con-

trolled automatically by the HAG. The operation of

such systems requires requesting current energy tariffs

from a tariff server as well as high resolution energy

data provided by a smart meter. Additionally, the HAG

requires access to local appliances such as washing

SMARTGREENS 2018 - 7th International Conference on Smart Cities and Green ICT Systems

236

machine, dish washer or climate control. From a de-

mand side management (DSM) point of view, only the

combination can generate a surplus from the opera-

tion of smart meters. For example, in Germany the

planned smart meter infrastructure will not allow en-

ergy providers to have access to high resolution energy

data, but only to aggregated data that is of relevance for

billing purposes. Hence, the required high resolution

data must be extracted locally through an interface.

This interface acts as a bridge between the regulated

smart meter infrastructure and, e. g., the local WiFi.

Likewise, it is possible to install an additional unregu-

lated smart meter which will gather the required data,

especially in a bonus based system.

The beneﬁts of such an architecture goes beyond

overcoming regulations, as the high resolution and

therefore sensitive data must not leave the household

as they may solely be used within the HAG. Hav-

ing a smart meter independent infrastructure also pro-

vides the possibility for, but is not limited to, a local,

smartphone-based information system where the user

proﬁles stay within the user’s local network and there-

fore are not transmitted to any third-party. On the

contrary, it is possible to develop cloud-based DSM

business models, where the high resolution data is

centralized on a server, accessible over an internet

connection.

This provided example shows, that by adapting the

communication infrastructure, even with the regulated

smart meter infrastructure it is possible to develop new

and innovative business models which make use of

high resolution energy data.

7 CONCLUSION AND OUTLOOK

The considerations and examples in the article show

that the communication part of the ICT system design

heavily inﬂuences the range of offers to customers,

market success and costs for delivering public ser-

vices and optional unregulated services. The ability

to reuse an existing infrastructure and to easily extend

the offered service is a key success factor of big in-

ternet companies. However, innovative services are

not limited to big internet companies: small and local

companies have the ability to develop such services,

and they are even more capable of reaching customers

whom they already have a business-relationship with.

Overcoming the entry threshold is much easier if no

custom hardware and protocols are required to deliver

new services. In the area of smart energy, smart utility,

smart city, and IoT, a positive competition and coopera-

tion between internet providers, energy providers, and

municipalities will arise in the coming years. For eco-

nomic efﬁciency reasons, they will almost exclusively

make use of generic communications infrastructures

to stay competitive in a fast moving market.

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