Show and Tell - Data and Digitalisation, Digital Twins.pdf
- 1. Strategic Innovation Fund Project ‘Show and Tell’ webinar Data & Digitalisation: Digital Twin Projects 20 May 2022
- 2. Welcome David Richardson, Head of Innovation, Innovate UK
- 4. Introduction: Data & Digitalisation challenge David Richardson, Head of Innovation, Innovate UK
- 5. Data and Digitalisation Challenge Aim: deliver the next generation of user driven digital products, services and processes spanning all energy networks, industry and Government. Themes include: Data monitoring, quality, collection Develop enabling digital products supporting other challenges Unlock data access, interoperability, and insights for third parties Improve efficiency, security, and resilience of networks Image courtesy: The European Files, Big data, IA, augmented intelligence: Building grids for the energy transition
- 6. Agenda – Data and Digitalisation, Part 1 1. Virtual Energy System NGESO 2. EN-twin-e SPEN 3. Digi-GIFT SPEN Q&A on projects 1, 2 & 3 10:20am – 10 minute break 4. Digital Twin - Exploring the societal, operational, and cross industry whole system benefits on the Gas Distribution Network SGN 5. Digital Twins: Exploring the commercial, societal and operational benefits on green hydrogen Projects SGN 6. Gas Networks Interoperable Digital Twin NGGT Q&A on projects 4, 5 & 6 11:40am – end of session
- 7. Virtual Energy System Jonathan Barcroft, National Grid ESO Beatrice Nassi & Andy Kervell, Arup
- 8. VIRTUAL ENERGY SYSTEM COMMON FRAMEWORK Project Supporters: Andy Kervell Associate, Arup Jonathan Barcroft Workstream Lead – National Grid ESO Beatrice Nassi Business Analyst, Arup
- 9. THE CHALLENGE 18- 30GW Interconnection by 2041 NOA - 2022 50GW Offshore Wind by 2030 UK Gov Energy Strategy 120- 230GW Flexibility by 2050 FES - 2021 “Increased data availability and digitalisation of systems is fundamental to enable markets and technology to manage peaks and troughs.” Bridging the Gap 2021 Transport Heat Industry & Utilities Hydrogen Active Network Management
- 10. LAYERED DATA GENERATES INSIGHT 4. HOW IT ALL WORKS IT BEGINS WITH A COMMON FRAMEWORK 1. POPULATED BY EXISTING AND NEW DIGITAL TWINS 2. EACH DIGITAL TWIN CONTRIBUTES 3.
- 11. REVIEW OF DISCOVERY Andy Kervell Associate, Arup Beatrice Nassi Business Analyst, Arup
- 12. DEMONSTRATING THE COMMON FRAMEWORK “Collaboratively prove and demonstrate, with industry, how the socio-technical principles work”
- 13. THE NEED FOR A DEMONSTRATOR WHY DO WE NEED A DEMONSTRATOR • Start by starting… • Show me, don’t tell me • Avoid duplication of effort • Align with the National Digital Twin programme • Demonstrate value CHARACTERISTICS OF THE USE CASE • Allows key socio-technical factors to be tested • Engages stakeholders from across the energy sector • Appeals to a wide audience • Leverages existing work (platforms, technology, data streams) • Theoretically feasible within SIF timeframes Testing of key factors Cross segment Wide appeal Leverages existing work Theoretically feasible
- 14. DISCOVERY TIMELINE Week 0 Week 1 Week 2 Week 8 Week 4 Week 5 Week 6 Week 7 Week 3 W/C 11-Apr W/C 01-Mar W/C 07-Mar W/C 14-Mar W/C 25-Apr W/C 28-Mar W/C 04-Apr W/C 18-Apr W/C 21-Mar • Kick-off meeting • Desk research of previous works • Agreed plan for collaboration • User interviews • User needs • Draft map for case study • Co-creation workshops • Determine concepts for potential demonstrator 1. Framing • Map stakeholder ecosystem • Stakeholder interviews • Identify key information types • Prioritise key information types 3. Synthesis • Synthesize needs, challenges & opportunities • Prioritise user needs • Review problem statement • Technology review 5. Document • Discovery Report • Deliver key research questions for Alpha • Close-out meeting: final retrospective
- 15. OUR HYPOTHESIS IS THAT…. ….is a problem/obstacle to accurately model, assess and control the whole system flexibility The lack of end-to-end visibility of: • generators assets • connectors • network capacity and constraints across both the transmission and distribution networks
- 16. WHAT IS WHOLE SYSTEM FLEXIBILITY? “Flexibility is the ability to adjust energy supply and demand to keep them balanced.” -Bridging the Gap to Net Zero 2022
- 18. WHAT DOES FLEXIBILTY MEAN TO OUR USERS
- 19. THE COMMON FRAMEWORK DEMONSTRATOR
- 20. VIRTUAL ENERGY SYSTEM - ALPHA Objective: ▪ Evaluate the risks, costs and benefits of the Virtual Energy System through the ‘Visibility of Flexibility’ demonstrator. 3 workstreams: ▪ Stakeholder engagement ▪ Common framework & principles ▪ Use cases
- 21. VIRTUAL ENERGY SYSTEM COMMON FRAMEWORK Project Supporters: Andy Kervell Associate, Arup Jonathan Barcroft Workstream Lead – National Grid ESO Beatrice Nassi Business Analyst, Arup
- 22. EN-twin-e Panos Papadopoulos, University of Strathclyde Niko Louvranos, Digital Catapult
- 23. Internal Use Internal Use Internal Use EN-Twin-e A Distribution Network Digital Twin Show & Tell A project funded by Ofgem’s Strategic Innovation Fund (SIF) Project Lead Consortium partners
- 24. Problem Statement The need for near real-time simulation of the Electricity System using Digital Twin technology With the anticipated electrification of heat and transport, and the proliferation of distributed energy resources connected at distribution level we will see an increase in demand-side flexibility as we aim to achieve the UK’s net zero targets. To maximise the benefits of this increased demand-side flexibility to the consumers we require better visibility of the potential impact and efficacy these assets might have when balancing the National Electricity Transmission System. And therein lies the opportunity to use digital twin technology and artificial intelligence to model and simulate more of the electricity network much closer to real-time allowing us to make better decisions in operational timescales to effectively manage the increasingly complex interactions between distribution, transmission, and ESO.
- 25. Project Overview Exploring the technical feasibility of a Digital Twin of the Distribution System The project aims to develop systems and processes to manage the more intertwined and complex electricity system in its future state. Focus on exploring how Digital Twins can support visualising, understanding, and evolving a system as complex as the UK’s electricity networks to respond and adapt in real time, and also forecast future scenarios that will allow us to unlock the benefits of increased demand-side flexibility. Project aims: ● Establish the minimum viable product and the highest value use cases, ● Determine the art of the possible based on available technology and data availability, ● Outline an architecture for an interoperable digital twin considering best practice, ● Develop a strategy to develop and verify our digital twin functionality. NETS Balancing SYstem Balancing service provider Aggregated BMU DT Transmission and Distribution Transmission Monitoring System Distribution Monitoring System
- 26. User Needs Digital Twin Users and Use Cases ESO, TNO, DNO - main users of the DT: The DT would provide greater visibility (near real time) of DERs connected to the distribution network and identify constraints in order to ensure the network operates within limits and unlock available flexibility. This will allow ESO make more effective balancing decisions, from a security, reliability and cost standpoint. ESO would like to know the aggregated DER output now and predictions for points in the near-future, along with what flexibility is available on those resources. The information should be provided within operational timescales. Potential additional users of the DT: - Aggregators: visibility of the anticipated operating envelopes to inform their bidding decisions into ESO The overall use cases can be broken down into three main areas, from 33kV down to LV: 1. DER Output Visibility (Now and next) 1. Active power – reported as “reduced demand” 2. Reactive power – reported as “reduced demand” 3. Mix of energy source type (wind, PV, EV, biomass gen, battery storage) 1. Identify constraints in DER flexibility (Now and next) 1. Active power operating envelopes 2. Reactive power operating envelopes 1. Enable optimisation of balancing decisions ("What-if" Simulations)
- 27. Addressing the problem Digital Twin Functional Architecture ● Distribution Network visibility ○ Near real time ○ Thermal and static voltage constraints (power flow) ● Active (P) and reactive (Q) power operational flexibility envelopes ○ P and Q capability at network interface ○ Communicated to the ESO for secure and effective balancing ● What-if scenarios ○ Use of forecasts ○ Operational timescales ● Generation mix (and load) disaggregation ○ Exploratory ○ Use for advanced modelling at transmission interface (ESO, TNO) Operational envelope example
- 28. Addressing the problem Digital Twin Functional Architecture - Twin Top and Twin End ● Twin Top ○ (up to) 33 kV (under given GSP) ○ Near real-time visibility ○ Operational envelopes ○ What-if scenarios ● Twin End ○ Down to LV (415 V) ○ Assess impact of implementation of technologies (e.g. EVs, heat pumps) to network constraints ● General considerations ○ Assimilate existing SCADA streams ○ Use of forecasts ○ Network topology from GIS ○ Missing/unavailable data ○ Execution and interface with users
- 29. Digital Twin Data & Architecture (1/2) Data Discovery: ascertain the extent to which data is available now through existing data feeds and future planned ones and identify gaps and methods to fill those gaps for future phases. Key Findings: - ESO: - Grid balancing only using a limited number of DERs at this point in time. - Outage planning done using conservative assumptions to secure DERs ESO is aware of. - ESO has no visibility of what energy resource are dispatched and from which GSP, whether it’s a DNO or an aggregator one. - ESO cannot request dispatch at a certain GSP. - DNO: - Visibility & data availability progressively diminishes moving from 33kV, 11kV down to LV whilst number of assets exponentially increases - Laborious and heavy processing needed for that data to become usable in real time Addressing the problem Method: - Deep-dive sessions with SPEN’s (SP, SPT, SPD) Smart Systems, IT, Real Time Systems, Data Historians, and Smart Grid teams, and with NGESO’s Operational Planning, National Planning, Whole Systems and National Balancing teams - Literature review
- 30. Digital Twin Data & Architecture (2/2) Architecture Discovery & Definition: Assess current and outline future architecture for DT considering best practice (open standards, maintaining cyber security, and data privacy) Key Findings: - There are component parts (existing/in development) that can be leveraged as architectural components of the DT. - SPEN has developed a tool (NAVI) to parse through, model and analyse the network at scale, and is accessible via WEB APIs. It covers LV to HV, metering data, Historian data, and Geospatial info. - But NAVI cannot operate in real-time and data cleansing is a laborious process. - Given the right use cases, the NAVI tool could become the DT applications platform. - Consideration to remove barriers such as IT infrastructure vs. energy network topology separation from technical, cultural, and security point of view. - SPEN is already working towards an Enterprise Bus Architecture (ESB) to move away from the current disparate approach to data collection and data manipulation. - Considerations for target topology to support DT need to be made (on-prem/cloud/hybrid), taking CAPEX/OPEX aspects into consideration given the exponential growth of data expected from the increased visibility from 11kV and LV levels. Addressing the problem
- 31. Looking forward (1) Develop PoC & and apply it to representative part of the network ● Choose network locations from candidates ● Proof of Concept (PoC) for Twin Top and Twin End ○ Methods implementation using synthetic (or offline) data ○ Explore practical and computational implementation aspects ● Case studies ○ Scenarios defined in collaboration with project partners and with input from CBA ○ Twin Top - near real-time operational envelopes and for near future ○ Twin End - what-if scenarios for Low Carbon Technologies penetration and identification of potential constraints ○ Exploration for Twin End use for real time
- 32. Looking forward (2) Feasibility of ML based modelling & Development of architecture requirements at scale Data Driven (ML) Model Exploration: ● Assessment of suitability of the data for supporting ML modelling given performance data requirements at scale ● Recommendation on data augmentation necessary to support ML modelling and DT use cases. Architecture and Implementation: ● Develop the Target Application/Technology architecture description (requirements) ● Application & Technology build ● Identify Deployment type (on-prem/hybrid/cloud) ● Identify App/Tech Key Issues ● Understand and address any data management issues (storage, migration, privacy sovereignty, governance, regulatory)
- 33. Digi-GIFT Dr Haiyu Li & Dr Eduardo Martínez-Ceseña, University of Manchester
- 34. 34 Digitalisation of holistic data connection interfaces for Gird Integration and Future Transformation (Digi-GIFT) Accomplishments, Challenges & Solutions Friday, 20 May 2022 Dr Haiyu Li, Dr Eduardo Martínez-Ceseña and Prof Zhirun Hu Department of Electrical and Electronic Engineering The University of Manchester
- 35. 35 03 Challenges and Solutions 01 Accomplishments • FITNESS – Future Intelligent Transmission NEtwork SubSation • VSATT - Virtual Substation Acceptance Testing and Training • CREST - Cyber Resiliency Electrical Substation Technologies 02 Statement of Problems • Interoperability • Big data • Network security • Shared data process and infrastructure • Cyber security • Enabling to support future real time data driven applications, such as: - Digital Twins: for example, Wide area monitoring and system integrity protection and control. - Markets and service coordination cross parties Contents
- 36. 36 The aim of Digi-GIFT is to build an integrated and robust cyber intrusion and defence system into a shared data infrastructure in order to manage data integrity, quality and security and data privacy for the business as usual as well as future real time data-driven applications to support digital twins. In the discovery phase, issues, challenges and proposed solutions are identified. To support the proposed solutions, Cost Benefits Analysis (CBA) on three key challenges areas were conducted. They are: • CBA for shared data infrastructure for better data collection, integrity and quality analysis. • CBA for an integrated cyber intrusion defence system (ICIDS). • Quantifying the value of flexibility service coordination in the Scottish Power distribution area. Conclusion. Executive Summary
- 37. 37 Statement of problems The complexity and scale of achieving net zero will require more agile, flexible and secured interconnected networks. The energy system transition and its digitalisation will pay a vital part to facilitate a net zero economy and to safeguard the UK’s global leadership. Based on literature reviews, the identified key challenges are • Lack of both data sets and interfacing among different assets to common business, • Lack of shared data infrastructure and confidence of data integrity and quality due to unreliable data communication links, especially IoT, • Remote data collection from SCADA and IoT sensors will also require appropriate security solutions that can guarantee the integrity of each of the separate security zone. • Lack of reliable cyber intrusion defence mechanism against more advanced cyber-attacks, such as malicious false tripping attacks, to power system SCADA and P&C systems in order to disrupt the power systems.
- 38. 38 • This CBA compares between bespoke (or dedicated) data infrastructure and shared data infrastructure for 3 to 6 databases with consideration of the same cost for each database, but different % of data overlaps among databases and different costs of data infrastructures. Fig.1 Bespoke (or Dedicated) systems Fig.2 Shared data system CBA 1 for Shared Data Infrastructure
- 39. 39 Fig.3 CBA for data cleaning vs. x% overlap Fig.4 CBA of data maintenance • The saving for shared data infrastructure varies depends on the number of databases. For example, when considering 3 databases with 30% overlap scenario the saving is £270,000, and with 50% overlap scenario, the saving would reach £450,000. For 6 databases, the saving for 50% overlap scenario is £900,000. The maintenance cost saving for 3 or 6 databases is £80,000 or £200,000 per annual, respectively. CBA 1 for Shared Data Infrastructure
- 40. 40 • The CBA studies used Markov Decision Process (MDP) tool for carrying out Cyber-attack risk analysis for a typical transmission substation and assess monetised benefit of investment on cybersecurity (ICIDS) over time, Fig.5 Risk score over time Fig.6 Monetised benefit of investment on cybersecurity over time • The studies show that with the investment of cyber security, especially ICIDS, the cost saving for cyber risk costing for a transmission substation is £700,000 in 2022. This risk costing saving will go up to £1,200,000 in 2031 according to the cyber risk scoring analysis from 6 in 2022 to 8 in 2031. The potential costing saving for cyber attack risk on 400 transmission substation will be £280m. CBA 2 for Cyber Risk with/without Investments
- 41. 41 • The shared data infrastructure offered by digi-GIFT enables the coordination of flexible energy resources at different network levels • The volume of services available is reduced due to conflicts • Coordination can remove those conflicts, and increase the volume of available flexible resources Illustrative example Initial business case Voltage at customer level CLASS SS SS SS SS Voltage at customer level
- 42. 42 • The volume of flexibility at the point of connection of a representative network is modelled with PQ maps CBA 3 for Value of Flexibility Service Coordination Network and DER coordination Medium level of DERs coordination High level of DERs coordination P Q – The incremental active power that coordination brings is quantified – The associated economic values are scaled at the SP level considering (i) network mix, (ii) value of flexibility and (iii) future energy scenarios Value assumptions Future scenarios and coordination strategies (Adv) Leading the way Baseline Steady progression Optimistic £79m £55m £31m Reference £44m £31m £17m Pessimistic £9m £7m £4m
- 43. 43 Conclusion We need • Share data process infrastructure to avoid unnecessary needs of a bespoke digital infrastructure for one specific function; • Efficient and effective data process and analysis tools to ensure the integrity and quality of data exchange. • An integrated cyber security and defence strategies based on AI and machine learning to ensure the resiliency of our power systems against more advanced cyber-attacks, such as malicious false tripping attacks, to power system SCADA and P&C systems. • Real time data stream based on novel data pipeline processing technologies to support real time data driven applications (or digital twins) as subscribers, hence enable to support an unlimited digital twin applications without need duplicate data acquisition systems.
- 44. 44 Any question?
- 45. Q&A – Data and Digitalisation challenge 1. Virtual Energy System 2. EN-twin-e 3. Digi-GIFT
- 46. 10 minute break See you soon…..
- 47. WELCOME BACK! David Richardson, Head of Innovation, Innovate UK
- 48. Digital Twin - Exploring the societal, operational, and cross industry whole system benefits on the Gas Distribution Network Peter Philip, SGN Graham Faiz, DNV Erwin Frank-Schultz, IBM Tharun Nandini, AWS
- 49. Digital Twins: Exploring the commercial, societal and operational benefits on green hydrogen Projects Peter Philip, SGN Graham Faiz, DNV Erwin Frank-Schultz, IBM Tharun Nandini, AWS
- 50. 10027059 - Digital Twin - Exploring the societal, operational, and cross industry whole system benefits on the Gas Distribution Network 10025731 - Digital Twins: Exploring the commercial, societal and operational benefits on green hydrogen projects SIF Discovery Show & Tell SGN - Pete Philip IBM - Erwin Frank-Schultz DNV - Graham Faiz AWS - Tharun Nandini May 2022
- 51. Fast forward 10 years 51 • Very different energy system • Producers • More wind, solar, tidal, heat pumps, hydrogen, bio-gas, nuclear • Less methane to produce electricity and heat homes, but still substantial (and the majority) • Consumers • More EVs, batteries on homes, district heating, peaking plants, electric / hydrogen transport, shipping & industrial etc • 100% Hydrogen to homes • Hydrogen and bio-gas mix into the methane network • Hydrogen for power stations
- 52. Current systems and processes will not be enough 52 Energy Digitalisation Taskforce publishes recommendations for a digitalised Net Zero energy system (17/01/2022) • Digital Twins will enable the energy sectors to get the plumbing right and support our journey to Net- Zero
- 53. • SIF Discovery Phase Show & Tell Gas Network Digital Twin 53
- 54. Digital Twins use data from the real world to model the structure and behaviour of systems to improve decisions. 54
- 55. • Key industry changes driving the project • New low carbon gas producers connecting to the distribution network • Managing cross-sectoral energy demand and supply • Objectives • Facilitating user access to open energy data. Enabling anyone with legitimate reasons to access the right data, creating a new energy ecosystem of internal and external users and solution providers. • Improving the visibility and capacity to make better informed decisions, by connecting different sets of systems and data, whilst providing context to that data and enable “what if” scenario simulation. • Connecting and interoperating multiple digital twins from different energy ecosystem partners using open industry standards. Key findings 55
- 56. We engaged a wide range of Stakeholders 56
- 57. The challenge for the gas network is securing supply for customers as the network decentralises, and managing the move to decarbonised energy Modelling the changes in the network due to decentralisation 57
- 58. Three Personas…… Persona 1: Barbara, a SGN low pressure network planner. • Barbara uses network for strategic network planning and operational decision making • Plans new renewable energy connections (biogas, hydrogen), manages pressure, new capacity, maintenance and also deals with incidents such as leaks. • These network valuable models are used in isolation. • She would like to feed them with data automatically and communicate the insights they provide to other internal and external users in the right context. Persona 2: Helen, a local authority planner. • Today, Helen has no visibility of the gas distribution network in her local authority to help with planning activities. • Needs better visibility of the current and forecast capacity of the network, and new network plans across her local authority. • This will improve city planning activities and assist the planning of new gas consumers or producers (e.g. biomethane or CHP plants). Persona 3: Fred, an energy portfolio entrepreneur. • Fred has invested in peaking plants, hydrogen production and wind farms. • He wants to optimise his energy portfolio to maximise his ROI and is frustrated by the long planning and commission processes. • He has poor interactions with the distribution companies and ESO. 58
- 59. We modelled the personas and developed DILO 59
- 60. We mapped the existing systems and user (needs) to our reference architecture 60
- 61. Benefits of the gas industry digital twin 1. Expedite decision-making on commissioning and connecting new entrants injecting low- carbon gas Benefits: Planning-to-commission lead times reduced, improved customer satisfaction scores through speed and quality of service provided, faster adoption of green energy and thereby reduced CO2 emissions, full transparency on the gas source as well as other measurements not currently provided such as quality and calorific value. 2. Managing intermittent demand and supply and cross-sectorial energy integration Benefits: Increased fixed asset utilisation, optimal network planning decisions, increased cross-sectorial coupling of energy network, reduced cost to end customer, increased network availability / reduced outages. 3. Improve public safety Benefits: Increased fixed asset utilisation, improved decision-making on critical and emergency incidents, improved public safety and reduced down-time, improved customer satisfaction scores through speed and quality of service provided. 61
- 62. 62
- 63. Introductions 63 DNV • Global independent assurance and risk management company. • In the energy market we assure that energy systems work safely and effectively through monitoring, verifying and advising on the energy infrastructure through the full concept, finance, design, build and operating cycles. • Published the energy industry’s first recommended practice (RP) on how to quality-assure digital twins in November 2020. SGN • UK gas distribution network that manages the network that distributes natural and green gas to 5.9 million homes and businesses across Scotland and the south of England. • Operates more than 44,000 miles (71,000 km) of pipes across the UK. • Leading the H100 Fife project, a ground-breaking demonstration project that will evidence the role hydrogen can play in decarbonising heat.
- 64. Background – H100 Fife • H100-Fife will be a world-first network that will demonstrate 100% hydrogen and bring carbon- free heating and cooking to around 300 homes for the first time by the end of 2022. • Green (or clean, low carbon) hydrogen is one of the key technologies on the road to decarbonization. • The clean gas will be produced locally, by a dedicated electrolysis plant powered by a nearby offshore wind turbine. • This £28m project is investing in Fife’s green energy industry – SGN have chosen Energy Park Fife as the hydrogen hub for H100 Fife. • The project is investing £28m over its lifetime, bringing jobs and opportunities to residents and local businesses. 1. ORE Catapult 7MW offshore wind turbine will generate electricity. 2. Electricity generated by the turbine will be used to produce green hydrogen at a dedicated electrolysis plant – separating water into its elements; hydrogen and oxygen gas. 3. Hydrogen will be stored on-site in six purpose built tanks – enough hydrogen will be stored to heat 300 homes. 4. The hydrogen will be transported through a newly built gas network to 300 opted-in homes. 5. State of the art hydrogen appliances, will provide zero-carbon heating and cooking for the project’s four and a half year duration. 64
- 65. • Project to build a digital twin of a low- carbon hydrogen production facility. • Project green-lit in February 2022 as part of the Ofgem Strategic Innovation Fund (“SIF”) portfolio of projects. • Green Hydrogen Digital Twin will be based on the real-world H100-Fife use case. • Initial discovery phase to validate the problem to be solved and articulate the broader benefits of a hydrogen digital twin to stakeholders. • 4x project partners. 65 Green Hydrogen Digital Twin Exploring the commercial, societal and operational benefits of Digital Twins on green hydrogen projects Building a digital twin
- 66. Digital twin concept - scope 66 H2O + e- Electrolyser O2 H2 Compression High pressure storage Pressure let down Custody transfer metering & hydrogen quality Relief/vent Hydrogen Producer Back-up grid power e- e- H2 H2 H2 H2 H2 Wind e- Demonstration homes Power supply conditioning Energy generated (actual, expected, predicted) Energy stored, capacity, demand H2 stored, capacity, demand H2 generated, demand, flows, quality, volumes Digital Twin outputs (to other twins)
- 67. Key Questions • How can a digital twin of a green hydrogen project support an emerging hydrogen economy in a safe, resilient, innovative and effective way? • What are the commercial, societal and operational benefits that can be derived from the deployment of a digital twin concept on a green hydrogen use case connected to the H100-Fife project? • What skills are needed in industry to support the design, build and operation of such as twin? • How can the data generated from such as twin enable a digitally-rich ecosystem that puts the energy industry at the forefront of cutting-edge digital technology and processes and support the strategic ambitions of the UK Government as outlined in the UK Hydrogen Strategy? • How does the hydrogen economy – through a digital twin - interact with the other infrastructure such as the impact on electricity supply resilience, water supply and other potential end users such as transport and industry? • How can digital twins in form and empower the consumer and help to enhance trust between an end-user and clean energy providers; increase societal uptake; support future billing methodologies; and provide clarity about the provenance of the energy source. 67 Operator (commercial) Consumer & Fuel Poor Network Operator Local Authority Green H2 Developer Industry
- 68. Stakeholders 68
- 69. User Stories 69 I want to understand whether supplier contractual obligations are being met User story Functional element How do I effectively scale up or scale back production and sustain supply ? I want to deliver gas of suitable quality to consumers How do I better manage complex demand / supply challenge relating to storage, production and consumption? I want to manage the complex demands into my network from distributed production sources alongside the existing offtakes? Need I want to operate production facilities due to loss of utility supply (ie water and power) How do I gain a better understanding the complex demands placed upon my production system by future networks or industry? I want to understand how a digital twin of a green hydrogen facility can…. help me sustain safety on my network and ensure security of supply How do I manage the complex mix of utility needed to ensure my facility operates and can produce hydrogen? help me manage the complex interfaces between different utilities incl water, power etc Link to network digital twin 3D Visualisation help me manage an evolving network of customers who have many gas producers and inputs Scene I want to understand the consequence of facility H2 production failure Want How Link to utility digital twin Sensor/IoT Predictive AI Wind turbine* Electrolysis Storage Green Hydrogen Digital Twin *wind turbine could also be a “utility twin” if wind infrastructure is e.g an offshore wind farm Dashboard Gas Output
- 70. Green Hydrogen Production Digital Twin 70 Inputs Outputs (and return values from connected twins) Wind Power* Power Grid Water Supply H2 Quality H2 Quantity H2 Volume H2 Storage Oxygen Billing Data Commercial Framework Operations Maintenance System State Data ecosystem – inputs and outputs
- 71. Power output from the wind turbine at that wind speed under conditions of temperature and pressure. Data properties captured by the systems installed on the wind turbine: daily reports of 10 minute values/Data - 30 days 2 3 1 Date Gas Flow
- 74. 74 Current Future “How do we keep our customers safe and warm, ensure security of supply whilst increasing the number of gas producers, off take points on the network, types of gas entering the network and balancing energy demand and production with other energy providers, such as wind and hydro renewables?” Where next? Build it – and connect! Distribution Network
- 75. Data Data Data Green H2 Twin Natural Gas Twin (NGGT) Bio Gas Twin Sources of Gas Gas Distribution Network Twin Scotland and Southern Networks UK / Regional Energy Twins All Energy Providers UK PLC Twins Energy, Telecoms, Transport etc Green H2 Data Data Interoperability Bio Gas Data Natural Gas Data Off Take Data PRS Pipe Lines AGI GOV Storage Data Future Work Current Work Transmission Network Distribution Network Roadmap Weather Data Demand Data Nuclear H2Twin Blue H2 Twin EN-twin-e SP Energy Virtual Energy System NG ESO Gas Networks Interoperability Digital Twin NGGT Network Data
- 76. Our future ecosystem of connected “gas/hydrogen network” digital twins • Ensure assets and infrastructure are compatible with the new gas blends • Ensure that at all times it remains safe for consumers to use • Ensure that that sufficient energy can be supplied to meet the country’s needs; that the supply is resilient • Balance complex supply side and demand side challenges • Will drive sustained focus on safety and sustainability of future network • Will become a ticket to trade when connected to commercial sandbox • Will managed varied “inputs” of network, which becomes increasingly distributed • Will support connectivity to renewables and other utilities for a whole systems perspective • Drive transformation of network planning size of pipes, replacement in the future • Ensure focus on treating data “as the asset” know what you have and where • Support (and be the trigger for) right skilling of the future workforce • Support the operation of the future business 76 TRUST Business needs Organisational maturity Data quality Assured operation
- 77. Alpha Phase 77 Merge Projects into one: Gas System of the Future Digital Twin Why • Value for money • Introducing digital twin interoperability • Accelerate transition to net zero • A critical enabler for the future gas system • Drive increase in digital maturity across energy networks • Ignite whole systems thinking • Balance supply and demand – a critical energy transition challenge
- 78. Alpha Phase 78 Proving the case • WP01 – Project Start Up • WP02 – Alpha Phase Technical Architecture • WP03 – Refine the User Cases • WP04 – User Teasing / Stakeholder Engagement • WP05 – Data / Data Quality Assessment • WP06 – Hydrogen Twin Prototyping • WP07 – Gas Network Prototyping • WP08 – Connected Twins • WP09 – Quality Assurance • WP10 – Beta Phase Solution Architecture • WP11 – Project Governance • WP12 – Project Closeout Quality Assurance Test the Business Case Prototype Beta Phase Build a Real World Digital Twin
- 79. 79 Thank you.
- 80. Gas Networks Interoperable Digital Twin Mark McNally, RAVMAC
- 81. Gas Network Interoperable Digital Twin Project Show & Tell - 20th May 2022 Ofgem Strategic Innovation Fund (SIF)
- 82. Gas Network Interoperable Digital Twin 1 Background and problem context Challenge area Understanding the impact that the lack of digital interoperability is having on Gas Network and its stakeholders and consumers. Project summary Develop the requirements to support future needs of a Gas Network Digital Twin. Objectives Identify the ‘data’ strategy and ‘interoperability’ needs and enablers to transform gas network stakeholder connectivity, information flow and value generation. Key benefits Detailed understanding of technical enablers, interdependencies, information gaps to construct digitals twin for the gas network to be able to exchange data accurately between all stakeholders. Consortia members National Grid Gas Transmission, RAVMAC, National Grid ESO, SGN & NGN. Core technologies Digital twin, Cloud storage, IOT, Data analytics, Simulation and Modelling, and Human factors
- 83. Gas Network Interoperable Digital Twin 2 Project Overview • The Energy Network are seeking to accelerate the use of digital twins across their networks to improve the efficiencies within existing operations and prepare for new green energy adoption. • Network providers are developing their own internal response to delivering the required digital twin functionality. • This presents data exchange problems on how networks will efficiently share information between themselves. • Little consideration of the overall energy network compounded by the lack of digital interoperability already apparent in existing internal operations and between network operators.
- 84. Gas Network Interoperable Digital Twin 2 Activities and approach to the problem Captured User requirements….through iterative Interview process. • Established project boundaries and definitions • Documented and analysed detailed operational use cases Understood Interoperability best practice cross sector • Challenges identified through research and discussion • Target use cases identified • Examined Human interoperability Assessed alternative approaches …..through Optioneering • Literature review of adjacent industry sectors • Interoperability benchmarking assessment. • Established standards landscape. • Cyber-Security considerations • Data strategy solutions and platforms • Reviewed adjacent SIF projects. Identified ways to Demonstrate in Alpha Phase • Constructed test cases off detailed Use Cases • Identified method of assessment for Alpha Phase • Produced outline design for model-based testing Transition pathway considered …..through • Assessed impact of hydrogen H2 • Reviewed H2 transition infrastructure and H2 project compatibility.
- 85. Gas Network Interoperable Digital Twin 2 User needs developed and understood in relation to the problem Data capture form to understand key “Use Case” and problems & future requirements NGN SGN Cadent W&W Regulator Ofgem NGGT Operations NGGT Systems Operations GD Operations GD Systems Operations ET Operations • National Grid ET • Scottish and Southern Energy Networks • SP Energy Networks NG Electricity Systems Operator (ESO) ED Operators • Electricity North West Limited • Northern Powergrid • Scottish and Southern Energy • ScottishPower Energy Networks • UK Power Networks • Western Power Distribution NGGT Boundary for NGGTs Gas Networks Interoperable Digital Twin Boundary for SGNs Common Information Model development Energy Producers Industrial Users Suppliers Domestic Users Other & New Users BEIS Boundary diagram developed to scope project & needs of stakeholders
- 86. Gas Network Interoperable Digital Twin 2 Potential opportunities identified for addressing the problem An Energy Ontology – System description understood • Driving common data governance, • Classification and relationship • Delivering Semantic (meaning) understanding between stakeholders and new collaborators. • Promote Sematic understanding A Model-Based Test Environment (MBTE) • Model-based system engineering approach • Demonstration mechanism to create, prove out and verify both data and human system interoperability (HSI) interoperable digital twin solutions • Executable model and Reduce risks to system design Energy Sector Standards – to maintain system • Standardised and harmonised process for digital Twin functionality, • Includes assurance, compliance, cyber-security, IoT and reporting.
- 87. Gas Network Interoperable Digital Twin 2 Potential approaches identified for integrating solutions. Transitional Approach • Evolution of existing data tool migration, • Existing operational processes would undertake a Transitional pathway to the new functional and intended state Transformational Approach • Approach with prescribed boundaries, control mechanisms and functionality for future intended hydrogen operations. • Analysis concluded a Transformational approach would be the preferred option for new energy environments.
- 88. Gas Network Interoperable Digital Twin 2 Potential Benefits identified Ontology Model Based Test Environment Standards a shared understanding of structured information • Agreed terminology • Increased use and reuse • Increased maintainability • Facilitation knowledge sharing • Common vocabulary a Human System Interoperability testing • Improved data cognition • Better User navigation and experience • Continued validation and verification method • Supports manual to automation decisions. • Informs Skills and Competency gaps an Energy Sector Interoperability framework • Aids defining quality • Sets minimum requirements • “How to “ recognized solutions • Improves efficiency • Reduces risk • Auditable baseline Provides Provides Provides
- 89. Gas Network Interoperable Digital Twin 3 Looking Ahead – Considering the options Ontology Model Based Test Environment Standards Proposed Next steps: Data & Digitalisation Steering Group Align / share output with DDSG Data Interoperability Workstream Proposed Next steps: National Innovation Allowance (NIA) Broaden research into global standards best practice. Develop energy standards catalogue for digital and data interoperability. Proposed Next steps: Future SIF Alpha Phase Develop a model based Laboratory environment to Prove-out Human in the Loop using key Use cases
- 90. Gas Network Interoperable Digital Twin 3 Looking Ahead – Dissemination 75 Page Technical Report Covering All Aspects of Project Supplement Report Review of 60 Standards Supplement Report Document all Captured 25 Use cases
- 91. Thank you – questions Ofgem Strategic Innovation Fund (SIF)
- 92. Q&A – Data and Digitalisation challenge 4. Digital Twin - Exploring the societal, operational, and cross industry whole system benefits on the Gas Distribution Network 5. Digital Twins: Exploring the commercial, societal and operational benefits on green hydrogen Projects 6. Gas Networks Interoperable Digital Twin
- 93. Other Show and Tells Data and Digitalisation Whole System Gas network asset monitoring and analysis Projects (Friday 20 May 13.00-15.30) Weather and predictive analytics Projects (Monday 23 May 09.00- 11:30) Increasing flexibility sources in energy system and Hydrogen deployment and integration (Monday 23 May 13:00 – 15:30 Whole System Integration(Monday 23 May 09:00 – 11:30 Registration page will be shared in the chat https://www.eventbrite.com/cc/ofge m-sif-round-1-discovery-show-and- tells-259469?utm- campaign=social&utm- content=attendeeshare&utm- medium=discovery&utm- term=odclsxcollection&utm- source=cp&aff=odclsxcollection
- 94. Now Open for Ideas - Ofgem’s Strategic Innovation Fund A £450m fund for large scale electricity and gas energy network innovation Each challenge area has key themes which must be addressed. The projects against these can be technical, social, commercial and/or market innovations. Supporting a just energy transition Preparing for a net zero power system Improving energy system resilience and robustness Accelerating decarbonisation of major demands Inclusivity, accessibility, and cost of living crisis A fully decarbonised power system by 2035 Energy security and energy system durability Decarbonisation of heat, transport, and buildings Round 2 Challenges Supporting Launch Events – Wednesday 25 May 11:00 – 12:30 and 13:30 – 15:00 Check out the link in the chat
- 95. Thank you David Richardson, Head of Innovation, Innovate UK