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Final Call to Join us

There is now less than one week until Predictive Maintenance 2020!

If you are planning to attend but have not yet booked your place, please visit the registration page and secure your place today, to ensure that you and your organisation benefit from the most crucial electric-utility-focused, technically in-depth, and vendor-independent discussion of the latest strategic insights and practical applications to help you take your predictive maintenance strategies to the next level.

In the meantime, I am delighted to highlight some key features and a few new additions to an already rich and exciting agenda.

Register today

Topics Covered on Day One:

Predictive Maintenance System Architecture

Establishing a system design that effectively integrates new with legacy technologies and remains flexible to the demands of predictive maintenance and the evolving grid

Creating the Roadmap to Predictive Maintenance 
Identifying the key milestones and establishing the migration path to full predictive maintenance

Sensor Deployment
Developing a cost-effective sensorisation roll-out strategy that delivers high levels of data accuracy and ensures grid asset health

Risk Management 
Mitigating infrastructure and workforce risks using a predictive approach as a tool

Maximising Asset Life Cycles
Leveraging sensorisation and novel applications to enable previously inaccessible insights into asset condition and creating more efficient maintenance routines

Drivers for Change in Maintenance 
Assessing the internal and external factors driving the need for change in maintenance departments to better support the needs of the smart utility organisation

Alongside the case study programme:

Strategic Panel
Creating the business case for predictive maintenance – highlighting the benefits, establishing the roadmap and determining the ROI in the migration toward predictive maintenance

Roundtable Discussions 
Join a table and discuss key issues surrounding one of the themes from the day’s intensive presentations

Networking Reception
Take advantage of the opportunity to unwind after the day whilst forging new connections with colleagues from across the European maintenance community

View day one agenda

Topics Covered on Day Two:

Data Lakes
Leveraging the potential of data lakes to generate quick insights from raw data and enhance your predictive maintenance strategy

Data Quality
Overcoming the quality challenges associated with legacy data to enable reliable predictive maintenance services

Cloud Leveraging
Applications Leveraging cloud technology with a central dashboard and live field data to gain predictive insights from existing data resources on field assets

Predictive Maintenance Methodologies
Determining the optimal balance between supply security and cost efficacy in relation to investment decisions arrived at by leveraging existing data and modelling variables in real time

Workforce Development
Reconfiguring your maintenance workforce and implementing a workforce development programme to upskill and empower your field force around predictive maintenance

Outsourcing Field Forces
Managing outsourced field forces to ensure maintenance quality, data integrity and cost-efficiency in the migration to predictive maintenance

Alongside the case study programme:

Technology Innovation Panel
Technology innovators will present their experiences of applying predictive maintenance tools and technologies in the smart grid domain

View day two agenda

Topics Covered on Day Three:

Machine Learning as a Predictive Tool
Combining central data platforms, legacy data and machine learning algorithms to inform intelligent field operation strategies and minimise excavation damage to existing infrastructure

Cybersecurity
Evaluating the cybersecurity risks inherent in predictive maintenance and devising a strategy to ensure effective prevention and monitoring of assets as the number of sensors in the grid increases

Digital Twin

Evaluating the potential of digital twins in enabling advanced predictive maintenance both for individual assets and the grid overall

AI & ML

Assessing the potential of AI & ML to process high volumes of grid data and provide advanced insights to support predictive maintenance procedures

LIDAR & UAV

Examining the full potential of LIDAR & UAV technologies to facilitate airborne analysis of hazards to power grid infrastructure and enable advanced maintenance strategies

Blockchain

Exploring the potential of next generation data collation methods to enable real-time, multi-party data insights to support predictive maintenance

Alongside the case study programme:

Tutorial: Augmented Reality
Exploring the potential of next generation technologies to provide field forces with real time maintenance guidance on a wide range of assets from a central facility

View day three agenda


Case Study: Axpo Power on ERIS

Asset managers are under increasing pressure to balance new investments alongside refurbishing the existing asset base to maximise lifecycle whilst reducing costs. In a rapidly digitising grid environment, there are many more variables affecting the lifecycle of assets. If not managed effectively these factors can lead to ineffective or improperly timed investment decisions, with implications for future revenue and operational reliability.

Now in a position to utilise an extensive pool of grid data, utilities must work hard to extract more value from their data and deliver more accurate investment decisions. At Predictive Maintenance2020Jörg Kottmann, Director of Asset Management at AXPO, will share details of ERIS; a platform that harnesses a variety of data resources to create an investment strategy that considers age, load, weather and other factors to determine which assets need action most urgently. We caught up with Jörg to learn more about the applications of ERIS and how it can enhance predictive maintenance capabilities.

“A grid operator’s job is to operate a reliable and at the same time efficient grid. These two goals have to be weighed up against each other. AXPO has developed ERIS (Evaluation of Reliability Index for Electric Systems) for this purpose. The efficient planning of expansions and upgrades can be derived from a single source on the basis of the security of supply. The impacts of electricity generation on renewable energies in combination with electromobility on grid reliability can be assessed and the necessary investments derived from this. 

ERIS gives hard parameters and values such as a grid reliability value for individual or whole regions. This data driven approach is desirable for the board and investors, who can now turn to data decisions to drive investment planning. AXPO has developed the quality score ERIS to assess grid reliability. ERIS allows users to define the desired level of grid reliability to which the expansion and upgrade investments can be systematically and efficiently geared towards user requirements. The ERIS method is being put to very successful use at AXPO. 

The ERIS method gives the security of supply of grids and partial grids a value. It allows grid operators to define their desired level of security of supply. This allows it to determine the need for action, not just for today but also for tomorrow, influenced by e-mobility and an increasingly decentralised feed-in. ERIS thus lets you take efficient decisions on whether investments are needed in expansions or upgrades based on the expected regional load development and ageing of the operating resources from a single source. 

A major challenge we have overcome is in working out which variables come together synergistically enough to create a value add for companies. Creating an algorithm that could reconcile all variables and incorporate forecasting data, weather data, and other resources to create an algorithm with an actionable output and subsequently demonstrating the value and gaining trust for the efficacy of the model proved to be more difficult aspects of ERIS’s roll out.

Our roadmap requires us to develop the model further by adding more data and getting more people on the platform. I look forward to sharing more details of our experience with ERIS with colleagues at Predictive Maintenance 2020.”

Jörg’s will be one of 14+ utility case studies being presented at Predictive Maintenance 2020. Alongside the case study agenda, there will be a technology innovation panel, a series of end-user focused roundtable discussions, a tutorial on the opportunities of Augmented Reality, a solution zone displaying state-of-the-art predictive maintenance tools and technologies and a networking evening reception open to all participants.

14+ utility case studies including:

  • Jörg Kottman, Director of Asset Management – AXPO
  • Mika Loukkalahti, Leading Expert, Asset Management – Helen Electricity Network
  • Camiel Oremus, Business Director Asset Management – DNV GL
  • Michael Weixelbraun, Head of Asset Management – Austrian Power Grid
  • Petr Lang, Head of Strategic Asset Management – E.ON Distribuce a.s
  • Rasmus Armas, Head of Asset Management – Elektrilevi
  • Thomas Castelijns, Data Scientist – Enexis
  • Sebastien Michelin, Asset Performance Management Solution Architect for Electric Utilities – Schneider Electric
  • Joris Soens, Head of Assets & Grid Architecture – Fluvius

Register today:

To find out how you can participate as a Delegate, Exhibitor or Sponsor:

Call:     +44 (0)20 8057 1700

Email:  registration@smartgrid-forums.com

Visit:    Predictive Maintenance 2020

We look forward to welcoming you to the event in January!

PS: Group booking discount!

Save a further 10% on 3+ delegates booked from the same organisation at the same time


Case Study: Enexis on Machine Learning to Reduce Dig Damage

The ability to identify the exact location of underground assets is leading to significant reduction in dig damage, power supply disruption, and unplanned costs. Utilities who are leveraging machine learning algorithms to pinpoint asset location despite incomplete data are going further, faster. Not only able to significantly reduce dig damage, these utilities are also able to remove significant workforce hazards and transform their SAIDI ratings.

This week we caught up with Thomas Castelijns, Data Scientist at Enexis, who has joined the speaker line-up at Predictive Maintenance 2020Thomas shared his experience of using machine learning as a predictive tool with a focus on combining central data platforms, legacy
data and machine learning algorithms to inform intelligent field operations and minimise excavation damage to
existing infrastructure.

Thomas explained:

The business case for this is pretty compelling. Damages to assets resulting from excavation work are one of the highest risks of activities in Enexis’ operations. In 2018, Enexis registered 250k notifications of excavation work. 6500 of them led to a damage to one of Enexis’ assets. This is one of the highest costs for Enexis. These errors created a clear need for additional capabilities to mitigate repeats of damage and to avoid further disruption to consumers.

The need for enhanced analytical capabilities drove Enexis towards the creation of an advanced digitalization transition programme. This will see Enexis make more data driven decisions. The impetus for this developmental direction was clear, and so it was not difficult to obtain approval and investment. We were able to deliver the model within a few months and provide actionable data for the business.

The algorithm produces weekly predictions about the probability of excavation damage in relation to the location of field operations. The current model is then evaluated by field personnel. The model accurately guides them to high-risk areas where they could then pass on the data to excavation companies, enabling them to avoid outages. Difficulties in implementation involved challenges around the correct labelling of data and unbalanced data.

The journey to completion and proper assessment of the project still involves some steps ahead. We will need to evaluate the results, continue to add/adjust features within our prediction model and we plan to integrate results from other utilities. This will include other asset classes such as water utilities. 

To boost the potency and accessibility of the model even further, we plan to connect to KAFKA streams to generate real time predictions and deploy the model to Amazon Web Services to enable greater connectivity and enhancement of field operation capabilities. I look forward to sharing more details of Enexis’ experiences, challenges and future roadmap with colleagues at Predictive Maintenance 2020.

Thomas will be joined by an expert line-up of leading utility maintenance professionals who will share their real-world applications of predictive maintenance and intelligent ways to leverage data to enhance operational functionality.

Alongside the case-study conference programme, there will be plenty of networking opportunities through round-table discussions, a lively exhibition area featuring innovative solutions from leading suppliers, and a networking evening reception open to all participants.

Register your place today

View the full programme

14+ utility case studies including:

  • Jörg Kottman, Director of Asset Management – AXPO
  • Mika Loukkalahti, Leading Expert, Asset Management – Helen Electricity Network
  • Camiel Oremus, Business Director Asset Management – DNV GL
  • Michael Weixelbraun, Head of Asset Management – Austrian Power Grid
  • Petr Lang, Head of Strategic Asset Management – E.ON Distribuce a.s
  • Rasmus Armas, Head of Asset Management – Elektrilevi
  • Thomas Castelijns, Data Scientist – Enexis
  • Sebastien Michelin, Asset Performance Management Solution Architect for Electric Utilities – Schneider Electric
  • Joris Soens, Head of Assets & Grid Architecture – Fluvius

View the full line-up

Register today:

To find out how you can participate as a Delegate, Exhibitor or Sponsor:

Call:     +44 (0)20 8057 1700

Email:  registration@smartgrid-forums.com

Visit:    Predictive Maintenance 2020

We look forward to welcoming you to the event in January!

PS: Group booking discount!

Save a further 10% on 3+ delegates booked from the same organisation at the same time


Early Bird Expires Friday 29th November 2019

A quick reminder that the Early Bird rate for Predictive Maintenance 2020 expires next Friday 29th November. To save €200 on delegate places and €1,000 on exhibition spaces, please visit the registration page of the event website and secure your place today.

Register your place today

This week we caught up with Joris Soens, Head of Assets and Grid Architecture at Belgian DSO Fluvius. Joris has kindly agreed to speak on the morning of conference day one, and will be sharing Fluvius’ experience of gaining investment for predictive maintenance and utilising condition data to inform their asset replacement programme.

Joris explains:

“We face increasing challenges from multiple angles; aging assets, regulatory pressures, the need to maintain our assets at a high level whilst reducing costs. We were convinced that a lot of efficiency and improvement could be made if we make better use of our data for more objective decision making and to set stronger priorities. We used advanced analytics to present a simulated business case to our investment board making the case for large cost reductions without increasing operational risks.

Several projects subsequently delivered better investment and maintenance planning, as well as providing brand new insights from all kinds of condition data and external factors that impact health that we weren’t aware of before. We are now collecting insights and using the information to adapt our replacement programme. We can see that the results will continue to improve as we continue to advance our capabilities and innovate in the ways we gain data from our equipment, most commonly through additional sensors and IoT. 

Looking forward, we are developing an innovation board that will be watching and investing in new digital skills. We need to develop new IT capabilities whilst ensuring our old systems are still as robust to support field operations. We are developing an innovation roadmap to work alongside legacy systems and infrastructure. I look forward to sharing how we are improving our maintenance practices in the short term and leveraging innovation to transform them in the longer term.”

Joris will be joined by an expert line-up of leading utilities who will showcase their real-world applications of predictive maintenance using intelligent ways to leverage data and enhance operational efficiency. The event will provide networking opportunities through round-table discussions, evening networking receptions and a lively exhibition area featuring innovative solution providers from within the European power grid sector.

Don’t miss out on this opportunity to take part in this comprehensive, in-depth review of next-generation maintenance practices by booking your place now!

View the agenda

  • Jörg Kottman, Director of Asset Management – AXPO
  • Mika Loukkalahti, Leading Expert, Asset Management – Helen Electricity Network
  • Camiel Oremus, Business Director Asset Management – DNV GL
  • Michael Weixelbraun, Head of Asset Management – Austrian Power Grid
  • Petr Lang, Head of Strategic Asset Management – E.ON Distribuce a.s
  • Rasmus Armas, Head of Asset Management – Elektrilevi
  • Thomas Castelijns, Data Scientist – Enexis
  • Sebastien Michelin, Asset Performance Management Solution Architect for Electric Utilities – Schneider Electric
  • Joris Soens, Head of Assets & Grid Architecture – Fluvius

View the full line-up


Last Call for Early Bird Registrations!

Keep up to date with the latest news regarding the Predictive Maintenance 2020 conference.

This is the last call for registrations at the early bird rate for Predictive Maintenance 2020. To save €200 on delegate places and €1000 on exhibition spaces, please visit the registration page of the event website before midnight this Friday, 29th of November.

Book now to make sure you reap the benefits of hearing 12+ utility case studies focussed on advancing maintenance strategies and creating an intelligent grid architecture.

What’s different about this event? 

Practical, immediate focus – Our market research indicates there aren’t any events on the market like Predictive Maintenance 2020. Our use case focus and implementation driven forums bring together the latest developments going on in the European grid – today. Our utility driven programme brings together experts from the field to detail practical insights into their latest developments, deliver the choices they’ve made, preliminary results as well as the lessons learned from real world projects.

TSO/DSO Oriented Case-Study Agenda – This event focusses on the emergent field of predictive maintenance and the latest developments in the field as well as feasibility of roll-out in the current state of the energy industry. With a comprehensive agenda informed by in-depth research, all the key challenges facing smart grid operators will be systematically addressed, ensuring you leave the conference with all the sector-specific information you need to fast-track your projects and deliver a more efficient energy system within the necessary timelines.

Future Technologies – Day three will look forward to future technological trends and explore the potential of deploying technological advances to streamline and enhance a variety of maintenance related practices. From cloud to cybersecurity and a 90-minute, hands-on tutorial around augmented reality smart glasses for use in the field. 10+ key suppliers will also be in attendance to share their solutions and insights to help advance your own solutions with the latest offerings on the market. 

Utility Case Study speakers include:

  • Joris Soens – Fluvius – Head of Assets and Grid Architecture
  • Jorg Kottmann – AXPO – Director of Asset Management
  • Iliana Portugues – National Grid – Innovation and Engineering Leader
  • Mika Loukkalahti – Helen OY – Leading Expert Asset Management
  • Alberto Guerra – Viesgo – Head of Asset Management
  • Rob Ross – Tennet – Asset Strategist
  • Kevin Devillé – Engie – Expert Condition Monitoring
  • Petr Lang – E.ON Distribuce a.s – Head of Strategic Asset Management
  • Michael Weixelbraun – Austrian Power Grid – Head of Asset Management
  • Thomas Castelijns – Enexis – Data Scientist
  • Rasmus Armas – Elektrilevi – Head of Asset Management

Register today:

To find out how you can participate as a Delegate, Exhibitor or Sponsor:

Call:    +44 (0)20 8057 1700

Email:  registration@smartgrid-forums.com

Visit:    Predictive Maintenance 2020

We look forward to welcoming you to the event in January!

PS: Early Bird Rate! Save €200 on delegate places and €1,000 on Exhibitor spaces by booking before Friday 29th November 2019.

PPS: Group booking discount! Save a further 10% on 3+ delegates booked from the same organisation at the same time.


Registration is now LIVE

We are delighted to bring you this premier Predictive Maintenance 2020 conference, exhibition and networking forum. This programme provides utility maintenance leaders with the information and inspiration they need to define their predictive maintenance roadmaps and drive their new technology implementation forward at the speed of the digital age.

Over three intensive days you will hear from 14+ smart utilities on how they have defined their system architectures, optimized their sensor deployment, managed their data quality, and made the migration toward more predictive forms of maintenance whilst maximizing their asset lifecycles and minimizing costs.

You will also hear how state-of-the-art technologies such as AI&ML, Data Lakes, Cloud, Digital Twin, LIDAR & UAV, Augmented Reality and Blockchain are being leveraged in practice to maximize reliability and accuracy of predictive maintenance approaches.

There is no other event like this! If you have heard the predictive maintenance hype and now want to get under the skin of its practical reality, then join us for what is set to be the most technically in-depth review of predictive maintenance experiences within the smart grid specifically.

Discussion themes include:

  • Creating the Roadmap
    Understanding the drivers, building the business case, and determining the longer-term roadmap for predictive maintenance in the smart grid environment
  • Driving Sensorisation
    Determining a cost-effective sensor deployment strategy to plug the gaps in existing data sets, maximise prediction accuracy and improve SAIDI
  • Data Management
    Pooling a wide range of sensor and smart meter data, ensuring its quality and accessibility, and its prediction reliability
  • System Architectures
    Comparing the potential of legacy systems with state-of-the-art data lakes and emerging platform innovations for driving predictive maintenance efficiency and accuracy
  • Future Technologies 
    Evaluating the potential of Digital Twin, Cloud services, AI&ML, LIDAR & UAV, Blockchain and Augmented Reality for the future of predictive maintenance in the smart grid

14+ utility case studies including:

  • Jörg Kottman, Director of Asset Management – AXPO
  • Mika Loukkalahti, Leading Expert, Asset Management – Helen Electricity Network
  • Camiel Oremus, Business Director Asset Management – DNV GL
  • Michael Weixelbraun, Head of Asset Management – Austrian Power Grid
  • Petr Lang, Head of Strategic Asset Management – E.ON Distribuce a.s
  • Rasmus Armas, Head of Asset Management – Elektrilevi
  • Thomas Castelijns, Data Scientist – Enexis
  • Sebastien Michelin, Asset Performance Management Solution Architect for Electric Utilities – Schneider Electric
  • Joris Soens, Head of Assets & Grid Architecture – Fluvius

Join the solution zone:

Would you like the opportunity to raise your brand profile, demonstrate your products and services and share your expertise with the most targeted and influential group of utility maintenance professionals?

Our adjoining exhibition area provides the perfect platform for you to do this and more! Capped at 10 stands we ensure a focused and relevant display of the latest tools, technologies and services for our audience and maximum visibility for each exhibitor

Testimonial from past attendees:

“It was great to hear about the developments and challenges of other utilities in this new environment. Really great presentations including inspirational messages, impressive pilots and great innovative ideas. After this event I believe we are going forward in the right direction and I bring back additional ideas and contacts for our future business cases”

Yamshid Farhat, Smart Grid Engineer – BKW
@ Grid Asset Management 2019

“The combination of presentations related to smart grids and machine learning analytics presented at this event is probably the most relevant for any data scientist within the grid utilities environment”

Tobias Haumann, Data Scientist – Adger Energi Nett
@ Smart Grid Big Data 2019

“An excellent opportunity to look further than the end of your own nose and acknowledge that other people’s solutions to shared problems may be far better than yours”

Julio E. Dominguez, SAS Designer – UFD
@ IEC 61850 Global 2019

Register today:

To find out how you can participate as a Delegate, Exhibitor or Sponsor:

Call:     +44 (0)20 8057 1700

Email:  registration@smartgrid-forums.com

Visit:    Predictive Maintenance 2020

We look forward to welcoming you to the event in January!

PS: Early Bird Rate! Save €200 on delegate places and €1,000 on Exhibitor spaces by booking before Friday 29th November 2019.

PPS: Group booking discount! Save a further 10% on 3+ delegates booked from the same organisation at the same time.


Save the Date for Predictive Maintenance 2020

We are delighted to announce the dates and location for the premier Predictive Maintenance 2020 conference, exhibition and networking forum. Please mark your diary, alert your colleagues and line manager, and invite your technology partners along for this intensive, immersive and inspiring meeting designed specifically to address the information needs of utility maintenance professionals.

Sensorisation of the grid is presenting invaluable opportunities for utilities to shift from scheduled maintenance practices to data driven predictive maintenance strategies, in order to maximise asset lifecycles whilst reducing operational costs and increasing workforce efficiency. But with the opportunities that predictive maintenance promises come significant challenges around developing the systems, processes and internal skillset, to apply predictive maintenance to a range of assets and under a variety of conditions.

Predictive Maintenance 2020 draws together utility maintenance professionals from across Europe for three intensive days of implementation case-studies, technology innovation discussions, and power networking with a focused and motivated group of maintenance professionals, to help you drive your predictive maintenance strategy to the next level.

As we finalise the programme please find below a preview of the speakers and discussion topics being planned, to give you a flavour of what’s to come.

Speakers Confirmed to Date:

  • Iliana Portugues, Innovation and Engineering Leader – National Grid
  • Michael Weixelbraun, Head of Asset Management – Austrian Power Grid
  • Rob Ross, Asset Strategist – Tennet
  • Jörg Kottman, Director of Asset Management – AXPO
  • Petr Lang, Head of Strategic Asset Management – E.ON
  • Rasmus Armas, Head of Asset Management – Elektrilevi
  • Alberto Guerra, Head of Asset Management – Viesgo
  • Anna-Lilly Brodersson, Asset Portfolio & Risk Management – Stromnetz-Berlin
  • Mika Loukalatti, Leading Expert, Asset Management – Helen OY
  • Kevin Devillé, Expert Condition Monitoring – Engie Laborelec
  • Joonas Koivuniemi, Head of Business Development – Empower
  • Santiago Gallego, Associate Director, Asset Management 4.0 & Digital Operations –Boston Consulting Group
  • Luay Baltaji, Cybersecurity Specialist – PwC
  • Camiel Oremus, Business Director Asset Management – DNV GL
  • Rafael Martins de Souza, Data Science & Machine Learning and Economics –FGV/CERI
  • Marc Roberts, Manager – IBM
  • Steven Hagner, Asset Management Solutions – ABB

Topics to be Discussed:

Drivers for Change in Maintenance:
Addressing the driving forces necessitating the shift towards a predictive approach

Strategic Panel –  Business Case for Predictive Maintenance:
An expert panel leading the conversation around the business case for predictive maintenance

Creating the Roadmap to Predictive Maintenance:
Creating the roadmap for migration from time-based to predictive maintenance practices

Maximising Asset Life Cycles:
Exploring how to leverage data for new insights into asset health and to obtain maximum value from existing asset fleets

Risk Management:
Creating a risk management framework that addresses the evolving needs of the smart grid

Predictive Maintenance System Architecture:
Establishing a system design that effectively integrates new and legacy technologies to adapt to the increased demands of the digital grid

Sensor Deployment:
Developing a cost effective sensorisation strategy that delivers high levels of data accuracy and ensures grid asset health

Sensor Performance:
Maintaining grid operational reliability in the absence of sensor data accuracy during the initial stages of sensorisation

Data Lakes:
Leveraging the potential of data lakes to generate quick insights from raw data and enhance your predictive maintenance strategy

Technology Innovation Panel:
Technology innovators will present their experiences of applying predictive maintenance tools and technologies in the smart grid domain

Data Quality:
Overcoming the quality challenges associated with legacy data to enable reliable predictive maintenance services

Smart Meter Data:
Leveraging smart meter data to gain deeper insights into the low voltage network asset health to determine the maintenance requirements

Workforce Development:
Reconfiguring your maintenance workforce and implementing a workforce development programme to upskill and empower your field force around predictive maintenance

Outsourcing Field Forces:
Managing outsourced field forces to ensure maintenance quality, data integrity, and cost-efficiency in the migration to predictive maintenance

Cybersecurity:
Evaluating the cybersecurity risks inherent in predictive maintenance and devising a strategy to ensure effective prevention and monitoring of assets as the number of sensors in the grid increases

Digital Twin:
Evaluating the potential of digital twins in enabling advanced predictive maintenance both for individual assets and the grid overall

AI & ML:
Assessing the potential of AI & ML to process high volumes of grid data and provide advanced insights to support predictive maintenance procedures

LIDAR & UAV:
Examining the full potential of LIDAR & UAV technologies to facilitate airborne analysis of hazards to power grid infrastructure and enable advanced maintenance strategies

Blockchain:
Exploring the potential of next generation data collation methods to enable real-time, multi- party data insights to support predictive maintenance

Tutorial – Augmented Reality:
Exploring the potential of next generation technologies to provide field forces with real time maintenance guidance on a wide range of assets from a central facility

Register today:

To find out how you can participate as a Delegate, Exhibitor or Sponsor:

Call:     +44 (0)20 8057 1700

Email:  registration@smartgrid-forums.com

Visit:    Predictive Maintenance 2020

We look forward to welcoming you to the event in January!