08:30Implementing DAM Systems – comparing the potential of legacy and state-of-the-art digital asset management systems to support next generation processes
Understanding the benefits of building in-house knowledge and asset management platforms for the achievement of long-term strategic aims
Determining the value proposition for investing in upgrading legacy asset management systems against investing in advanced asset management software
Quantifying the value of smart asset management software for optimising asset management capabilities, track asset lifecycles and compare assets through data modelling
Identifying strategies for implementing next generation DAM systems to boost departmental productivity whilst mitigating any adverse effects on day to day operations
Mapping out a workforce development plan to enable efficient training and development of key staff and ensure timely adoption of DAM systems
Determining optimal timelines for effectively improving asset management processes to support analytics objectives and generate maximum ROI
09:00Implementing ISO 55000 – effectively interpreting best practice guidelines to drive resource efficiency and streamline the implementation of digital asset management
Conceptualising improvements in your asset management functions when best-in-class standards are followed, to identify key areas for value creation
Understanding the benefits of risk-based frameworks for decision-making in increasingly integrated and digitised asset management processes
Learning from specific examples in which ISO 55000 has been effectively followed, to understand how a balance of risk, cost and performance has been achieved
Interpreting ISO 55000 standards for your organisation to optimise its application and ensure best practice
Developing a roadmap for the implementation of ISO 55000 to drive smart investment decisions and achieve the wider strategic goals of your organisation
09:30Data Management – implementing a comprehensive data management framework to facilitate smart data ingestions, create efficient IT infrastructure and support advanced analytics
Consolidating historical data with new dataflows to provide a strong foundation for effectively analysing customer behaviour and grid assets
Creating an efficient and integrated model to facilitate data discovery across business units
Understanding how to merge data from different sources, such as SCADA, GIS systems and smart meters, into an enterprise-wide data management approach
Determining how smart services sourcing can inform advanced grid analytics and more accurately inform investment decisions
Capitalising on the power of a consistent data quality strategy to create a ‘virtual data factory’ and generate insights from increasing data reserves
Facilitating collaboration through data sharing and integrate external data into internal modelling to better support advanced analytics
Ignacio Canales
Head of Global IT for Generation and Distribution, Iberdrola
10:00Q&A Panel Session
10:15Morning Break, Exhibition, Networking
10:30Investment Planning – leveraging data driven insights to model multiple investment scenarios and ensure robust risk management in the investment planning process
Effective investment planning to ensure quality of supply and grid stability whilst keeping costs at acceptable limits
Developing metrics for quantifying the risk posed by asset failures based on condition, utilisation demand and reliability data
Creating quantifiable risk parameters to accurately guide investment portfolio management and facilitate the integration of advanced analytics into investment modelling
Understanding the ways in which AI&ML can be incorporated into investment scenario analyses to mitigate risk and secure robust investment strategies
Establishing effective communication techniques for conveying the importance of data driven investments to the board
Optimising data driven investment planning to gain a better return on existing budgets and attract higher levels of future investment
11:00Grid Planning – utilising multiple data sources to accurately inform grid planning processes and ensure well targeted infrastructure development strategies
Unlocking the power of data analytics to inform bottom-up innovation, demonstrate value creation for specific projects, and secure quality of supply whilst reducing expenditure
Weighing up the benefits of upgrading grid infrastructure against investment in greater grid flexibility and better network management
Testing the value of creating a national wireless connection through the use of LoRaWAN technology to enhance data extraction from older electrical assets
Identifying strategies for managing the integration of smart assets alongside the maintenance and upgrading of aging assets
Creating actionable insights for grid planning from increased dataflows by leveraging computational power and self-learning AI&ML to inform grid investment
Developing and delivering highly optimised investment plans that minimise upfront costs and maximise value across asset lifecycles
11:30Outage Detection – capitalising on the computational power of AI to create a platform that predicts outages in real-time to reduce expenditure
Deriving actionable insights from sensor and smart device data to more accurately and quickly depict network outages
Developing an AI Event Smart Alarming model which is able to forecast outages from millions of events to a central OT control application
Overcoming data collection, storage and cleaning challenges to centralise dataflows and consolidate disparate sources
Effectively managing the department, and out-sourcing tasks, to successfully handle the significant workforce demands of collecting, clearing and analysing historical data
Setting out the roadmap for using the platform to predict congestion and develop greater in-house capacity to effectively maintain and advance the software
13:30Flexibility – dynamically managing distributed energy resource through active network management to support the development of a decentralised system
Creating methodologies to highlight when it makes more business sense to invest in flexibility services or in upgrading grid infrastructure
Understanding the ways in which data can optimise network management strategies to mitigate congestion in the grid and reduce the need for continual investment
Generating advanced topological models that create clear insights into consumption patterns, and allow targeted grid planning and localised balancing mechanisms
Capitalising on state-of-the-art technologies such as AI&ML to increase automation and flexibility the grid
Optimising investment planning through accurately modelling demand and implementing effective network management techniques
14:00Disruptive Technologies – exploring the outliers of asset management and the ways in which critical infrastructure can be universally beneficial to maximise long-term grid resilience
Conceptualising exploration strategies for critical infrastructure, to understand the brittleness of future energy ecosystems cause by short-term innovation mindsets and long-term investment
Exploring paradigm shifts and leverage points to challenge innovation blind spots and create a research lens that investigates the questions that are too big for one DSO but relevant for all
Using a complex system approach to future-proof critical infrastructures in rapidly changing environments and combat an uncertain technological future
Investigating our blind spots in the digital realm to look at how AI and blockchain could create working ecosystems in radically different and unexpected ways
Exploring anomalies and the ways in which disruption could occur as well as co-creating with unlikely partners to connect to the fringe
14:30AI&ML – leveraging the computational power and self-learning capability of artificial intelligence to support complex scenario planning and inform risk mitigation
Understanding the ways in which AI&ML can be incorporated into the analysis of assets to inform a more robust investment strategy in a more complex grid
Capitalising on the self-learning capability of AI&ML to foster innovation through modelling multiple scenarios and more intelligently managing risk
Making sense of increasing dataflows through the computational power of AI&ML and more accurately forecast system changes
Balancing the development of in-house workforce capability with leverage external expertise and attracting new talent to drive up your internal AI&ML capability
Overcoming bias in AI&ML algorithms to guarantee the accuracy and reliability of investment decisions
Fully comprehending the business-case for integrating AI&ML into investment analysis of investments and gaining trust for its adoption
Ahmed Mousa
Manager, Utility of the Future, Electric & Gas Asset Strategy, PSEG
15:00Digital Twin – evaluating the viability of digital twin technology for establishing asset performance parameters and mitigating operational risk
Determining the value of simulation technology in stress testing the operational limits and optimising lifecycles
Identifying the specific use-cases for which digital twin technologies can create most value
Assessing the technical and organisational requirements of different digital twin architectures to create the best strategy for individual assets
Weighing up the benefits of adopting digital simulations against the resource and time requirements for cleaning and managing the data and creating advanced models
Implementing a plan for scaling up the application of digital twin across the grid to significantly improve asset performance and reduce overall costs
16:00Technology Innovation Panel – digital asset management tools and technologies
During this session leading technology suppliers will each give a 15-min presentation on how they are developing new solutions to meet the rapidly changing demands of a more data driven asset management function. This is your opportunity to quiz the tech innovators and influence the direction of future product development to better meet end-user requirements.
During this session, the audience breaks out into three different roundtable groups, each focused on a specific theme arising from the day’s presentations. Each roundtable group will address the challenges, discuss potential solutions, and create a summary of recommendations for feedback to the wider group.
Roundtable Room 1: Creating the Roadmap
Roundtable Room 2: Digitising the Asset Management Function
Roundtable Room 3: Digitising the Future Grid
19:15Roundtable Feedback
During this session participants return to the main stage, where each roundtable leader delivers a 10-minute summary of the outcome of the roundtable discussions.
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Mandana WhiteCEO, Smart Grid Forums
Carl JohnstoneDirector, i4 Asset Management
Jorge SimoesHead of the Digital Factory, EDP
Rasmus ArmasHead of Asset Management, Elektrilevi
Ignacio CanalesHead of Global IT for Generation and Distribution, Iberdrola
Stephan StåleredSenior Project Manager, Ellevio
Peter Lyck IngerslevInnovation Engineer, Energinet
Alexander Riishede JensbyInnovation Manager, Energinet
Bart BikkerEnergy Management System Specialist, Stedin
Patrick van EijkData Scientist, Infiniot
Mika LoukkalahtiLeading Expert Asset Management, Helen Oy
Mário Teixeira CoutoElectrical Engineer, EDP
Jan-Peter DoomernikSenior Business Developer & Asset Manager, Enexis
Ahmed MousaManager, Utility of the Future, Electric & Gas Asset Strategy, PSEG
Dominic MoserHead of Strategic Grid Planning, Swissgrid
Graham BaldwinSolution Consultant, Hitachi ABB Power Grids
Alexander KrivobokovCo-Founder & Chief Marketing Officer, APLINES
Gero BieserChief Solution Expert Utilities, SAP
Nadine HerrwerthHead of Commercial Development, TWTG
Dr Steven BlairHead of Power Systems Technologies, SynaptecLecturer, University of Strathclyde
Bram AlkemaBusiness Development Asset Management, Nexans