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Sean Lyons 26 th January 2016

Smart Energy Cluster Optimisation

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Page 1: Smart Energy Cluster Optimisation

Sean Lyons 26th January 2016

Page 2: Smart Energy Cluster Optimisation

01/05/2023 www.tssg.org 2

TSSG

• Founded: In 1996, has 100+ researchers (112 people) in Waterford.

• Expertise: is a leading software R&D Centre with particular expertise in network, mobile and communications services.

• Science: is a leading SFI funded SRC Centre working with IBM, Cisco and Alcatel-Lucent.

• International: is one of Ireland’s leaders in the EU collaborative R&D programmes (FP7/Horizon 2020) and has worked with over 450 companies on these programmes.

• Industry: completed over 110 direct industry projects in Ireland over the past 5 years and has spun out a number of leading international start-ups such as FeedHenry Ltd

Telecommunications Software & Systems Group

Page 3: Smart Energy Cluster Optimisation

StorageBattery, Thermal,

Pumped Hydro, CAES

Load – Selectable, Predictable

EV’s, Thermal, Pumping, Data Centres

MarketSEM Pricing

Wind ForecastingTariffs

Demand PredictionDSU’s AGU’s

Distributed GenerationRenewables – Wind, Solar

CHP

SECOSmart Energy

Cluster Optimisation

SECO – Smart Energy Cluster Optimisation

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SECO ‘ties it all together’

Page 4: Smart Energy Cluster Optimisation

New paradigm• Supply/Demand balancing• Requirement to cater for

Intermittency & Variability of Renewables

• Energy Conservation, Energy Efficiency, De-carbonised energy

• Mandatory EU Targets

The Problem & Opportunity Identification

Old paradigm• 100% Demand driven• Large Centralised Power

and Old, Unidirectional Infrastructure

• Inefficiencies, e.g. Spinning Reserve

• 29% of ETS* CO2 emitted by the power industry

Transition will not occur with a ‘Top Down’ Approach

* ETS + EU Emissions Trading Scheme

Page 5: Smart Energy Cluster Optimisation

• Microgrids not alone reduce the cost of energy to the end consumer

• ++ the balancing/ramping/frequency/voltage services can be sold to the grid operator – Ancillary Services

• ++ microgrids are a tangible manifestation of Smart Grid that enable the further evolution of Smart Grid

Why Solve It?

• but allow the consumer to make profit on their energy by exploiting arbitrage opportunities in the electricity market

• Intelligence gives Control – turn Consumers into Prosumers

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• Smart Grid must put the ‘End User’ in the Centre• Incentivise behaviour – Dynamic Tariffs• Facilitate Distributed Generation• Control = Power = Playmaker• Consumer Participation• Intelligent Decision System

Solution

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Where’s the Money?

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Original MRSO DataOptimal MRSO DataSMP Data (EP2)SMP Data (EA2)

Load (kW) Price (€/MWh)

Market Price Fluctuations

Turn on/off load on market signals

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Benefits hierarchy - consumer• Energy cost savings• Energy arbitrage – profit opportunity• Security of supply

– Availability & Price• CSR (Green)

Benefits hierarchy – Grid Operator & Energy Regulator

• Capacity• Balancing/ramping etc• De-Carbonised energy• Energy independence• Energy price

Page 9: Smart Energy Cluster Optimisation

• Model the factory/cluster load to establish an accurate profile with a view to predicting upcoming demand and trends

• Integrate with market to optimise real time pricing• Enable demand side management mechanisms• Enable Distributed Generation technologies including

wind, CHP, battery storage, diesel generation, etc.• Potentially trade power within the cluster (future)• Model various scenarios to optimise and maximise

returns • Model these scenarios versus acceptable risk profiles

thereby retaining control on site

SECO in Industrial Settings

Page 10: Smart Energy Cluster Optimisation

• Stage 1 - Test bed sites in Industrial Load Centres• Stage 2 – Enabling Virtual Power Plants with

complimentary vertical partners- Storage Technologies- Distributed Generation- Voltage Optimisation- Ancillary Services- EMS Systems

• Stage 3 - Microgrid partners in UK, EU and US

Route to Market

Page 11: Smart Energy Cluster Optimisation

• New Paradigm• Green Wave of Innovation• Prosumers• Energy Independence• Low Carbon Economy = 6th Wave• Ancillary Services/Negawatts – DSM, VPP, VNM,…….

All need Intelligence and Control to be effective• Hierarchy of Smart Grid – Dynamic Tariffs, Consumer

Participation, Control, RE, Decision Systems

The Future

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Page 13: Smart Energy Cluster Optimisation

• SECO Algorithms and platform– developed by PhD level Optimisation experts– exclusive license from TSSG (WIT)

• Extensive industry knowledge input to platform– Principal Investigator, Concept Developer &

Promoter from the Energy sector• TSSG expertise in development of high level software

and Optimisation systems

Intellectual Property

Page 14: Smart Energy Cluster Optimisation

Thank you for your attention

Any questions?

Contact: Sean [email protected] 302761