multiFLEX: Flexible Multi-utility, Multi-service Smart Metering

Architecture for Energy Vectors with Active Prosumers

Edoardo Patti

, Enrico Pons

, Dario Martellacci

, Federico Boni Castagnetti

, Andrea Acquaviva

and Enrico Macii

Dept. of Control and Computer Engineering, Politecnico di Torino, Torino, Italy

Dept. of Energy, Politecnico di Torino, Torino, Italy

IREN Energia, Torino, Italy

Keywords:

Distributed Software Infrastructure, Smart Metering, Smart Grid, Demand Response, Distributed Systems,

Distribution Network.

Abstract:

In order to move forward the vision of Smart Grid, a ﬂexible multi-utility and multi-service metering archi-

tecture is needed to allow innovative services and utilities for the different actors playing in this scenario. To

achieve this, different meters (e.g. electric, water, heating and gas meters) must be integrated into a distributed

architecture in order to gather and analyse heterogeneous data. Hence, such architecture provides in real-time

a complete overview of the energy consumption and production in the grid from different prospectives. From

customer viewpoint, this information can be used to provide user awareness and suggest green behaviours,

thus reducing energy waste. From energy operator or utility provider viewpoint, for instance such analysis

can: i) improve the demand response for optimizing the energy management during peak periods; ii) proﬁle

consumer energy behaviours for predicting the short term energy demand; iii) improve energy and market

efﬁciency. In this paper, we discuss the characteristics of this infrastructure and its expected impacts on utility

providers, energy operators and customers.

1 INTRODUCTION

The electricity market was introduced in the Euro-

pean countries following the Directive 96/92/EC of

the European Parliament and of the Council concern-

ing ”common rules for the internal market in electric-

ity” (European Parliament, 1999). Up to now the mar-

ket is working properly for big producers, retailers

and users, while the small consumers and prosumers

cannot access directly the market and cannot be inﬂu-

enced by price signals.

Distributed generation from renewable and

non-programmable energy sources is becoming

widespread. This requires a more ﬂexible manage-

ment of distribution grids, also involving energy

storages, both at the prosumers and on the network.

For these reasons, a ”smarter” grid is needed by

Transmission and Distribution System Operators

(TSOs and DSOs) together with retailers and market

operators in order to face in their activities.

A ﬁrst step in this direction is the development

of a ﬂexible smart metering architecture for multi-

ple energy vectors (multiFLEX). In some countries,

smart meters are already deployed at user level. Such

smart meters are nearly devoted to billing improve-

ments. However, a new metering systems is needed

to go much further by providing their contribution to

various objectives such as: i) end-user affordability

of electricity; ii) energy and market efﬁciency im-

provement; iii) CO

emissions and pollutants reduc-

tion. Hence, such ﬂexible smart metering architecture

must be able to: i) integrate the already available com-

ponentsand devices that can be implementedin a plug

and play way; ii) combine and correlate information

from meters of different services such as electricity,

water, gas and district heating; iii) provide advanced

services to users, DSOs and other utilities; iv) en-

hance the retail market. Following this view, the mul-

tiFLEX infrastructure integrates different information

from heterogeneous data-sources to promote innova-

tive services related to electricity, water, gas and dis-

trict heating.

The rest of this paper is organized as follows. Sec-

tion 2 reviews the relevant state of the art on dis-

288

Patti E., Pons E., Martellacci D., Boni Castagnetti F., Acquaviva A. and Macii E..

multiFLEX: Flexible Multi-utility, Multi-service Smart Metering Architecture for Energy Vectors with Active Prosumers.

DOI: 10.5220/0005483202880293

In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS-2015), pages 288-293

ISBN: 978-989-758-105-2

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

tributed architectures for Smart Grid. Section 3 de-

scribes the characteristics and objectives addressed by

multiFLEX. Section 4 introduces the proposed soft-

ware architecture and its expected impacts are pre-

sented in Section 5. Finally, Section 6 provides the

concluding remarks.

2 STATE OF THE ART ON

DISTRIBUTED

ARCHITECTURE FOR SMART

GRIDS

In a Smart Grid scenario, different middleware so-

lutions and service oriented architectures have been

proposed to enable a pervasive monitoring and man-

agement of the the grid itself for providing ser-

vices. Moreover in (Karnouskos, 2009; Warmer et al.,

2009), the authors focus on the importance of ex-

ploiting a Web Services approach to establish the in-

teroperability between Smart Home and Smart Grid

contexts. Also at building level, service oriented ar-

chitectures (Candido et al., 2009a; Candido et al.,

2009b) and middelware solutions (Stavropoulos et al.,

2013) have been proposed. Moreover, such solutions

provide a set of API (Application Programming In-

terfaces) in order to promote the integration and the

communication between Smart Buildings and Smart

Grids. However, this is necessary but still not enough.

Indeed, to provide services suitable for the whole

Smart Grid, such as demand response, a complete and

widespread overview of the grid itself is needed. Fol-

lowing this view in (Patti et al., 2014a), the authors

propose an architecture for integrating different data-

sources for increasing the energy efﬁciency in heating

distribution networks at district level.

In the power system scenario, Kim et al. present

a data-centric infrastructure that exploits the pub-

lish/subscribe communication paradigm to allow de-

centralized monitoring and management of the grid

itself (Kim et al., 2010). The GridStat middle-

ware (Tomsovic et al., 2005; Hauser et al., 2005;

Gjermundrod et al., 2009) is another solution for

enabling the communication across the devices in

power system. However, GridStat works with its own

closed and dedicated network infrastructure (Ger-

manus et al., 2010), which is incompatible with In-

ternet, so new routers must be deployed. Villa et

al. present the CoSGrid middleware for measuring

and controlling the electrical power of heterogeneous

Smart Grid infrastructures (Villa et al., 2011). It

exploits a remote method invocation and an event

notiﬁcation approach to enable the communication.

In (Patti et al., 2014b), the authors present a dis-

tributed software infrastructure for general purpose

services in power systems. They reached the interop-

erability across heterogeneous devices and built their

software architecture exploiting the LinkSmart mid-

dleware

, which creates a secure peer-to-per network.

With respect to the presented solutions, we pro-

pose multiFLEX, a multi-service and multi-utility ar-

chitecture that aims at facilitating the access of mul-

tiple actors to relevant data to foster the spreading

of various innovative services. As the previous so-

lutions, it enables the communication between het-

erogeneous devices in the grid. In addition, multi-

FLEX offers a cloud-based infrastructure to collects,

analyse and provide energy information from differ-

ent meters. It is worth noting that multiFLEX features

are not strictly related to power systems but they are

opened also to other utilities such as water, heating

and gas.

3 PROPOSED APPROACH

The existing applications acknowledge that metering

infrastructure is an enabling technology that needs to

be coupled with innovative services to reach energy

management by means of rewards, automation and

information. In order to reinforce customers’ engage-

ment in achieving energy efﬁciency, number of utili-

ties already operate demand response and direct load

control to limit and shift the peak loads. However,

new services can be integrated focusing on more com-

plex technical applications, transparent for the end-

user but nevertheless with higher social impact. mul-

tiFLEX pursues the ambition of innovating this sce-

nario exploiting:

• multi-service approach that uses information

coming from electric, water, gas, district heating

meters to provide general purpose services;

• substation meters to improve fault tolerance and

demand response capabilities of the network, tak-

ing into account local electric storage and genera-

tion;

• advanced Non-Intrusive Appliances Load Moni-

toring (NIALM) techniques to proﬁle user be-

haviours and introducing a user signature of en-

ergy consumption/production regarding electric-

ity, gas, water and heating;

• demand response algorithms that exploit informa-

tion about energy ﬂows from the meters and the

NIALM proﬁles.

https://linksmart.eu/redmine

multiFLEX:FlexibleMulti-utility,Multi-serviceSmartMeteringArchitectureforEnergyVectorswithActiveProsumers

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Figure 1: multiFLEX: ﬂexible, multi-utility, multi-service metering architecture.

To achieve this, a software infrastructure to gather

data from heterogeneous data-sources and to perform

real-time data processing is needed. This can be

achieved with a cloud system capable of aggregating

and correlating such information. Finally, the result-

ing software infrastructure have to provide end-users

with feedbacks suggestions for optimizing energy us-

age.

In order to allow innovative services and utilities

for the different actors playing in a Smart Grid context

(e.g. ESCOs, DSOs, prosumers and customers) a ﬂex-

ible multi-utility and multi-service metering architec-

ture is needed. As shown in Figure 1, multiFLEX

integrates off-the-shelf meters placed at the users

for electric, water, heating and gas metering. Such

heterogeneous meters directly communicate with a

building concentrator, which is in charge to enable

a bidirectional communication with the central cloud

system. For what concerns the electricity grid, mul-

tiFLEX also integrates off-the-shelf electric meters

deployed in MV/LV (Medium Voltage/Low Voltage)

substations. The central cloud system is in charge

of: i) collecting data from the building concentrators,

thus from the different meters at user home, and from

MV/LV substation meters; ii) post-processing incom-

ing information exploiting algorithms for data collec-

tion, fusion and mining; iii) providing a set of API

and tools for general purpose services and utilities.

Example of services for the prosumers are the access

to historical records of the energy consumption and

their analysis with saving suggestions. While, exam-

ple of services for the DSOs are: i) fault detection; ii)

detection of thefts; iii) demand response; iv) energy

storage integration.

In order to achieve a ﬂexible multi-service and

multi-utility infrastructure, multiFLEX has to ensure

real-time bidirectional communication with each me-

ter in the Smart Grid. As shown in Figure 1, multi-

FLEX integrates heterogeneous meters (e.g. electric,

gas, water and heating meters) deployed at users and

also electric meters at MV/LV substations to monitor

the whole Smart Grid and to manage the loads in real-

time. Following this approach, the meters are seen as

a network device connected to internet. Hence, mul-

tiFLEX enables:

• real-time readings management;

• real-time accounting activities management;

• real-time information to customers through a suit-

able interface structure;

• detection of energy thefts;

• near-real-time grid level and user level fault de-

tection allowing optimal alarming and ﬁrst inter-

vention systems to be adopted;

• demand response together with optimal integra-

tion of distributed generation and storage systems.

In order to enable a non intrusive automated en-

ergy monitoring systems to proﬁle the energy con-

sumptions of the appliances, multiFLEX integrates in

its cloud a load proﬁling system that leverages the

NIALM technology (Zoha et al., 2012). NIALM is

a signal processing technique, which discerns the en-

ergy consumption of the appliances from the aggre-

gated data acquired from a single point of measure-

ment. It exploits transient electricity consumption

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Figure 2: multiFLEX software architecture layers.

events that are used to uniquely characterize each ap-

pliance. The resulting load proﬁles are used for i)

suggesting changing in user behaviours that will al-

low savings; ii) input for the demand response man-

agement system; iii) energy consumptions analysis.

4 multiFLEX SOFTWARE

ARCHITECTURE

In order to address the objectives described in Sec-

tion 3, we propose an innovative multi-service dis-

tributed infrastructure to allow remote management

and provide new services to DSOs, prosumers and ﬁ-

nal customers. To achieve this, multiFLEX has to en-

able the interoperability across heterogeneous devices

exploiting middleware technologies that seem to be

promising along this direction (Patti et al., 2013; Patti

et al., 2014b). As shown in Figure 2, the resulting

architecture is organized in the following layers:

Integration Layer: it is in charge to enable the inter-

operability across the heterogeneous devices by

abstracting a certain technology to a Web Ser-

vices. Hence, it translates whatever kind of lan-

guage the low-level technology speaks into Web

Services.

M2M Layer: the Machine-to-Machine (M2M)

Layer is responsible for data communication

based on publish/subscribe approach (Eugster

et al., 2003). This approach increases the scalabil-

ity because it removes the interdependencies be-

tween producer and consumer of the information

allowing the development of services completely

independent from the systems and deployed de-

vices. Furthermore, it allows the development of

distributed applications and services that react in

real-time to certain events.

Storage Layer: it collects the data coming from the

meters and devices deployed across the city. mul-

tiFLEX is a modular and ﬂexible infrastructure

where heterogeneous technology can be plugged

in. Hence, databases in the storage layer exploit a

non-relational schema-less approach.

Application Layer: it provides a set of API, tools

and distributed applications to manage and post-

process the information coming from the lower

layers.

Security Layer: it provides features to enable a

secure and trusted communication. It controls

whether a device or service can be trusted or not.

Therefore, it enables mutual authentication by

providing the means to create a public key infras-

tructure. Furthermore, it allows cryptographic op-

erations for message protection in order to guar-

antee the conﬁdentiality between the parties.

In addition to the presented multiFLEX software

architecture layers, we identiﬁed two main platforms

for providing feedback and post-processed analysis to

end-users:

User Interface Platform: it is built on top of the Ap-

plication Layer. It is a user-friendly multi-service

platform that provides end users’ energy con-

sumption, tips and suggestions to promote green

behaviours, to reduce energy waste and related

costs as well. This platform is also used by stake-

holders, such as the multi-utility companies, in or-

der to manage and control deployed meters, for

instance to check system status, operating condi-

tions and faults.

NIALM Platform: It is a cloud-based data process-

ing unit dedicated to proﬁle the user electrical en-

ergy consumptions. It exploits energy disaggre-

gation algorithm to discern the consumption of

the appliances from the aggregated data acquired

by the single meter at home. From this informa-

tion, the algorithm extracts the signature patterns

in order to associate each transient to a speciﬁc

appliance. Then the resulting disaggregated in-

formation are made available to provide energy

awareness (via the User Interface Platform) and

to forecast more accurately the energy demand in

the short term.

5 EXPECTED IMPACTS

In this section we analyse the expected impacts for the

multiFLEX architecture. From a preliminary analy-

sis, it might seem that the utility companies already

multiFLEX:FlexibleMulti-utility,Multi-serviceSmartMeteringArchitectureforEnergyVectorswithActiveProsumers

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offers some of the proposed features such as: i) on-

line available user proﬁles; ii) on-line consumption

information; iii) suggestions for consumption opti-

mization; iv) basic predictions for future consump-

tion. However, the back-end block for data acquisi-

tion and processing is missing. Indeed, multiFLEX

aims on enabling a multi-service and multi-utility

platform in which different services like electricity,

water, gas and district heating, converge. Following

this view, multiFLEX provides end-users a complete

overview of their energy consumptions in real-time.

In addition, concerning the electrical consumption,

multiFLEX can analyse more accurately the users

load proﬁle thanks to the NIALM platform avoiding a

massive deployment of sensor devices, such as smart

plugs. Therefore the impact will be important both on

the provider and consumer side, for instance: i) re-

ducing costs for the utility companies on reading the

data; ii) providing real-time services to end-users; iii)

detecting faults; iv) providing demand response.

The availability of real time and open data at ev-

ery level of energy distribution (e.g electricity, water,

gas and heating) chain will be the turning point for

promoting the active involvement of end-users and

fostering other working actors, such as energy man-

agers, ESCOs and aggregators, in providing innova-

tive services. No one of the players listed before

can really make the difference without analysing and

exploiting data with such a granularity as to show

consumers habits, electric devices status and faults.

Hence, enabling the interoperability and interconnec-

tion between different meters and multiFLEX archi-

tecture, that canbe considered also as a common data-

exchange platform, will foster the spreading of inno-

vative services.

Social impacts will be strictly related to real-time

data availability even at consumer level. Indeed the

knowledge of each own consumptions is the starting

point for other more integrated and innovative ser-

vices (e.g. remote house control systems) that will

change people behaviours.

Sharing information related to the development

and the status of the Smart Grid has to be the ob-

jectives for its continuous expansion, stimulating a

virtuous circle. DSO will beneﬁt from a more effec-

tive operation and maintenance management systems

while consumers will beneﬁt from information of en-

ergy bad habits and more tailored energy offers.

5.1 Impacts on End Users

Knowing the itemized consumption of the household

devices means having the necessary actionable feed-

back information to propose for reducing the energy

waste. multiFLEX provides dual beneﬁts both to the

end-users and to the energy providers as well. In the

former case multiFLEX can provide detailed knowl-

edge of the household consumption for each appli-

ance and suggest personalized tips to reduce energy

waste. Generally, the beneﬁts for end-users are sum-

marized in the following:

• knowing the disaggregated energy of the house-

hold appliances;

• discovering which appliance is the most inefﬁ-

cient by comparing its consumption with more ef-

ﬁcient models present in other apartments;

• being aware of consumption for each appliance in

terms of energy, money and CO

footprints. This

can help the end-user in taking positive decisions

to reduce the energy waste by 15-20% (Darby,

2006; Darby, 2008);

• comparing the disaggregated appliance consump-

tion among different weeks, months or years;

• observing the energy consumption in real-time by

mean of a smartphone applications to monitor the

apartment and receive alarms whenever the en-

ergy situation in the apartment is not as expected.

5.2 Impacts on Utility Providers and

Energy Operators

In view of the utility provider, multiFLEX can in-

crease the efﬁciency of demand response strategies by

keeping track of energy use patterns and behaviour of

their customers. Hence from the energy operator and

utility provider viewpoints, the main advantages are:

• proﬁling consumer energy behaviours in order to

predict the short term energy demand;

• offering personalized pricing policies to con-

sumers after proﬁling;

• providing more efﬁcient demand response strate-

gies to optimize the energy management during

peak periods balancing the consumers’ energy

loads (Bergman et al., 2011).

6 CONCLUSIONS

In this paper, we presented the characteristics and the

objectives of multiFLEX, a ﬂexible multi-utility and

multi-service metering architecture for energy vectors

with active prosumers. Furthermore, we discussed

the beneﬁts and the expected impacts that such ar-

chitecture can have in a Smart Grid context. In-

deed, multiFLEX integrates different meters into a

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distributed infrastructure with the aim of gathering,

post-processing and analysing heterogeneous infor-

mation from different meters and data-sources. Thus,

multiFLEX provides an overview of both energy con-

sumption and production in the grid from different

viewpoints, fostering working actors in promoting

new and innovative services.

ACKNOWLEDGEMENTS

This work was supported by Flexmeter, which is a

H2020 European Research Project.

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