Summary Industry Desired Outputs

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Description of research
required by industry


Industry desired outputs

Interested companies

% Funding


Status 14/2/2011


Study the

and coexistence of
energy information


Research stra
nd A1
:Investigate business
models that would enable service suppliers
worldwide while achieving an adequate
level of DSM and meeting regulatory

Bill, UTRC; Ian K., BGE ;
Wouter NXP; Frank ESB


Key focus

1/Reissue A1 call to
RPO’s f
or business skills

2/Target experts

3/ call to all RPO’s

Research strand A2:

Investigate network
topologies to enable service providers,
consumers, automated HAN, and
distributed generation to communicate
and inte
ract in the content of a high % RE
on grid and a paradigm shift in range and
scope of energy supply services

Bill, UTRC; Ian K., BGE;
Wouter NXP; Frank ESB

contract awarded A2 to

co leads

plus UCC, UCD, TNI as


Local Smart Gr

Factory Optimisation

1 & 2

Optimisation of factory or continuous flow
manufacturing site

Alex, IBM; Stephan GM,



1/Revise brief with IERC
members 2/Reissue call
asap as per Ai above.


Local Smart Energy

1 & 2

Optimisation of Co
mmercial Buildings

Alex, IBM; Ewout NXP; Jim


al a key

contract awarded to UCC
as lead plus 4c,NUIG,


HAN Energy
Management System


Research and recommend HAN
architectures that will deliver desired cost
ons and functionality for consumers
and energy reduction for suppliers

Ian, BGE; Wouter NXP; Neil
ESBN; Chris Vodafone; Fran
& Jim ESB Energy Solutions


a huge

contract awarded to UCD
as lead plus CIT, DCU,
UCC ,TNI as collabor


Energy Storage at a
commercial level


Identify and scope the business and
technology case for energy storage systems
for a defined set of commercial enterprises

Jim, ESB; Rhiannon BGE;
Chris Vodafone



1/ feedback from

on market

2/ revisit calls 1&2


Utilization of waste heat
energy within the
commercial sector


Identify and map industrial zones where
low grade energy might be inter
from one facility to any other facility

Jim, ESB; Rhiannon BGE;
is Vodafone



Await proposal from I2E2
to avoid cost duplication.

Summary Industry Desired Outputs


IERC Scoping /Status

Research Area A: Convergence & Co
existence of energy information networks

To study the converg
ence and coexistence of energy information networks and types.

Current situation

There is general consensus among industrial companies and energy service suppliers that
there is a need for Demand Side Management to facilitate the planned increase in varia
renewable energy resources on the electricity grids worldwide. However, there is a great
deal of uncertainty about the business models and communication networks that will be
used and this is stifling development with companies preferring to stay in a
wait and see
mode. The business models are complicated by uncertainty about the tariff levels that will
be set for time of use tariffs, the carbon taxes that will be introduced, customer behaviour,
customer acceptance and government policies. The communica
tion network development
is complicated by the absence of agreed standards, distributed generation, micro
generation, the tendency to treat networks in isolation and confusion about the
interpretation of results from reported demonstrations.

Desired situa

There is a need for a viable business model and a communications network topology that
will underpin electricity supplier consumer demand management interaction.

The Gap

A business model that would be viable in the majority of scenarios has not yet e

An agreed communications network topology/architecture for the delivery of the new
energy services has not yet emerged.

Proposed project

Investigate the value chain in energy supply demand optimisation in order to propose a
business model and com
munications network topology that could be confidently pursued
by industry developers and energy service suppliers to deliver demand side flexibility in
communities of energy consumers. The project will have a business model and a network
topology strand.

The business model strand will investigate business models that would enable energy
service suppliers worldwide to provide their customers with their energy needs while
achieving an adequate level of demand side management and meeting regulatory
ns. The strand will take into account consumer behaviour, time of use tariff levels,
energy trading, carbon tax level, carbon credit trading, variable oil prices and government
policy. It will map the supply and demand profiles of commercial, domestic and
users throughout the year in different weather conditions and explore complementariness.
It will identify possible services and service providers on a local, borough, regional and
national level. It will explore policy structures via scenarios.
It will attempt to identify a
business model that will be applicable in the majority of cases.

The network strand will investigate communications network topologies to enable service
providers, commercial/domestic/industrial consumers, automated home area

distributed generation suppliers to communicate and interact in the context of a high
penetration of variable renewable generation on the grid and a paradigm shift in the range
and scope of energy supply services. The network will probably opera
te in parallel with and
in isolation from a simpler smart
meter network. The network will carry metering data from
each consumer, meta
data on real
time pricing, control data for controlling discretionary
loads. Data flow will be bi
directional. Data neede
d for real
time control of generation and
demand will have to be fast in one direction and secure. Communication media such as
GSM, WiMax and power line carrier will have to be investigated. Ideally a network topology
will be identified that will be suitab
le for the majority of the service models that the service
providers would want to implement.

In the course of the workshop on 4

and 5

Nov, a parallel team identified specific areas
they prioritised. These were:


Optimization of Local Grid. Investigat
e and quantify the scope for optimizing the local
electricity grid and by locally optimizing with alternate forms of energy.


Interaction across network. This consideration was to establish the scope for interaction
between participants in the local energy
community, and between those participants
and the larger grid. There was mention of scope to trade either supply of energy (or
variation on demand) again on real time. Cloud computing will be an important enabler
for this work package (and probable some of

the others also). The use of the cloud will
enable interactions in a secure manner.

The project will have three stages with a go/no
go decision point before the start of each

Stage 1 will be a scoping stage where state
art will be investi
gated and potential
business models and network topologies will be evaluated in a study (paper and practical)
to see if there are options worth pursuing in any greater detail.

Stage 2 would develop the components of a network topology and evaluate in a la
demonstrator of 20
30 simulated consumers. It would also revisit and update Stage 1 work
in the light of new developments.

Stage 3 would build and evaluate a community scale demonstrator with a mixed profile of
commercial, domestic and industrial
consumers. It would also revisit and update Stage
1and 2 work in the light of new developments.

The project team will require expertise in: business models, communications networks,
government policy, intelligent component development, consumer behaviour.

Research Area B

Local Smart Grid

Factory Optimisation


The scope of this research area extended from the lowest level, which was talked about
from the periphery of pieces of equipment in a factory, right up to a community of
factories, c
ommercial buildings and possible homes. Parallels were drawn with the SEAI
Dundalk Sustainable Energy Zone with a community of about 200 homes, several factories,
a college campus and a hotel.

So at the lowest level, the scope went to the built
in proc
essors or intelligence with
appliances (such HVAC systems in a building to air compressors in a factory). It was
confirmed by the companies that they did NOT place useful value on collaborative of design
of appliances

that was each company’s core compete

but saw synergy in working
together to agree communication protocols and standards to allow effective
interoperability and optim
sation of factories or continuous flow manufacturing sites.

In the model we have used in IERC discussions, this scope ext
ends into:

Level 1 (home, factory and commercial buildings) to communicate with appliances
right up to

Level 2 (community).

Current Situation

The current situation in a factory environment was best articulated by one IERC member, in
automotive manufactu
ring and assembly, who explained that his factory manager cannot
holistically optimize his energy use in terms of factory throughput and costs. It seems that
while there are energy management systems, and there are ERP and factory management
systems, syste
ms to optimize across factory and energy considerations in a systemic way
are not available.

Desired Situation

Systems enabling factory managers access to systems that would optimize across
traditional factory considerations like throughput with emerging
considerations of energy
use, and have decision support systems to help such managers make optimal decisions.

We would like to see a manufacturing demonstration site with an integrated energy
demand management system and smart factory grid.

Progression t
owards that would be Lab demo (year 1), Factory line demo (year 2) Entire
Factory demo (year 3), Integration with renewable energy supply and energy demand
management (year 4). In terms of levels focus on level in years 1
3 and get to level 2
through integ
ration in year 4.

Decisions to be made with the developed systems tools would include:

(1) real
time cost
optimal load shedding decisions

(2) real
time cost
optimal production management considering real
time load shedding,
time energy pricing, and i
ntermittent supply from renewables.

(2) is priority for us. Should also include management of energy in the factory if
intermittent distributed energy supply is on
site (e.g., renewables or micro turbines).

Decisions should not reduce throughput but reduc
e energy costs only

Proposed project

Optimization of Factory or Continuous flow manufacturing site as follows:

Decision Support System (DSS). This would allow a factory manager have an
integrated system that allowed holistic optimization of energy measure
s alongside
“normal” factory measures around cost and throughput.

Modeling and Simulation

to allow users get answers to “what
if” questions.

Predicative analytics (demand/supply)

this was especially important in a future
where factories have their own
renewable energy systems or they are using
electricity from the grid that is highly weather dependent. This system would allow
them predict how they might adjust their demand to cope with likely energy

Real time. This consideration is importa

since today much energy management
is historical

and a user does not have the ability to make choices when they should
be making them.

Trading Capability. This arose in instances where a factory might have its own
energy sources and it could trade t
hem on the wider market. In addition, with a
market for demand response

optimization systems could effectively act as
automated energy traders.

Success Measures

The project, if successful would deliver:

Energy management systems available for factory or

process managers that are
integrated into the normal factory ERP systems. The system would allow holistic
decisions be taken to optimize energy, throughput and cost. The system would also
have modeling capability to assist with what
if scenario planning.

Community groups participating on the energy market as traders. The concept of
Virtual Power Plants

where blocks of demand would be traded on the market
would give consumers the potential to further reduce the energy costs.

Version as documented by Joe O
’Callaghan Thu 18

Nov 2010

Revised Rev 2 by Michael Grufferty for IERC 8.02.2011

Research Area E

Commercial Energy Storage


Much of the renewable energies coming available are variable. We cannot dispatch them as
we would a coal powered sta
tion. This research area has its origin in the opportunity to
store energy when it is plentiful and possible exceed the system needs. For example on a
windy night for a system with lots of wind turbines, At that time, in the middle of the
summer the syst
em demand will be low and will be challenged to use all of the available
energy produced. The opportunity is to use that stored energy at other times when it is
more useful and is needed.

The Irish energy policy is to achieve 40% of our electricity requi
rements from renewable
energy sources by 2020. Because of our weak connectivity to the UK and European grid, this
gives us a unique opportunity to research this area.

Current Situation

A wide range of existing energy storage solutions exist. For example,
flywheels, pumped
hydro (like Turlough hill), flow batteries, thermal mass, phase change materials and heat
pumps, among others. It is not clear to the companies that these technologies will sufficient
and appropriate for our future needs.

Additionally, mu
ch of the existing energy storage is at the national grid level, storage within
individual buildings, industrial parks or housing clusters.

Desired Situation

Cost effective energy storage solutions are more widespread. They enable consumers (or
groups of

consumers) reduced their energy costs since they have the ability to purchase
energy when it is plentiful and cheap and use it at other times when it is either scarce or
expensive (or both).

Proposed project

Identify and scope the business and technology

case for energy storage system for a
defined set of commercial enterprises.

Success Measures

For the commercial client: reduced overall cost of energy inputs. While the amount of
energy provided to the commercial enterprise will stay the same , the s
torage and
controlled release of this power would enable reduce energy costs and could enable
new ways for the enterprise be more efficient.

Less dumping of electricity generated from renewable wind sources

Version 2 as documented by Joe O’Callaghan, Fr
i 19

Nov 2010