Can a digital version of a real-world asset make the life of DSOs easier? Yes, says Bram Alkema.
Electricity grids are extremely large and complex systems – the US power transmission and distribution grids altogether are often considered to be the largest machine ever built on earth.
They are made up of a large number of disparate elements which, although they are independent, are also highly interconnected. Furthermore, grids are inherently dynamic, as their topology shifts constantly in response to new sources of generation and especially decentralized renewables, new loads, congestion and breakdowns.
The increasing deployment of smart grids, which allow two-way flows of electricity and data, adds further complexity. To manage all this, a complexity simulation tool – a “digital twin” – can play a critical role. This helps to better understand the interaction between grid elements for better, fully-informed decision-making.
One of the main challenges facing DSOs over the past few years has been finding the optimum balance between what they need to spend on running, maintaining and developing their grids and the quality of supply they deliver to their customers.
They are under increasing pressure to achieve more with less expenditure. That requires a fine balance of cost, risk and performance. DSOs are also key enablers of the global energy transition. But adapting distribution grids presents a number of complex investment challenges. As well as catering for new demand and distributed energy resources (DER) integration, there is a need to ensure that supplies remain reliable and secure.
Electricity demand in Europe is expected to rise to approximately 3,530TWh per year by 2030. A recent study by Deloitte suggests that distribution grids will need to handle an extra 730TWh compared with 2017, equivalent to the electricity consumption of France and Italy combined. Transport electrification will see the fastest growth, with predicted year-on-year increases of 11% in Europe over the next decade. Electric vehicles will account for most of this growth. The increasing use of power-to-gas and electrification of heating and industrial processes will also drive demand.
Distribution networks will also need to handle very significant increases in the level of energy coming from DERs, and especially renewables – everything from rooftop solar to offshore wind. More than 500GW of extra renewable capacity is envisaged by 2030. Nearly three-quarters of this will be connected to DSO networks. Ensuring network reliability and service quality are already a major focus for DSOs These will become even more important as homes and businesses head towards 100% electricity dependency. In a similar vein, there is an increased need to ensure the grid remains resilient in the face of extreme weather events linked to climate change.
Increased asset management challenges
In addition to the developments highlighted above, the operation of distribution networks is becoming increasingly challenging because of the rapidly changing landscape of the energy industry and stricter market regulations. Furthermore, DSOs also have to face a growing number of internal obstacles, including ageing infrastructure, growing budget constraints, and the loss of expertise as highly-skilled and experienced staff retire – the “knowhow” drain.
The traditional approach has been to address each of these aspects individually, often in silos.
Yet the many facets of network maintenance and renewal strategies – such as finance, quality of service, safety, or human resources – interact with each other in complex ways that cannot be easily understood and modelled. This is where digital technologies become a critical decision-making tool for efficient asset management.
Data makes the difference
Information is key to effective asset management. As an example, replacing old equipment before it fails often seems wasteful or simply impossible. Yet the data for making an informed decision is often not readily available. Consider the US power grid, where almost 70% of power transformers and transmission lines are over 25 years old.
The maintenance and renewal strategy should be designed on the basis of tangible data and realistic forecasts. Otherwise, it is impossible to find the right balance between minimising the risk of equipment failures, securing acceptable network performance and efficiently managing CAPEX and OPEX.
The information needed to drive decision making is abundant. But it is distributed across various stakeholders within the DSO organization, from asset managers to maintenance and engineering teams, from the finance department to human resources. What is needed is some way to collect and manage this data and to use it as the basis for reliable projections that consider all the many variables. This is where digital technology offers a head start for asset managers.
Recent developments in augmented intelligence have resulted in solutions capable of centralizing data and generating a digital twin of the complete distribution network. This virtual model considers all the constraints imposed by the regulatory environment, business rules, available financial and human resources, and any technical policy in place.
The digital twin
In simple terms, a digital twin is a digital version of a real-world asset. The ability to model a single asset has clear value. But now with the development of enterprise digital twins it is possible to create a model of the whole distribution business encompassing all its assets and interactions. The digital twin accurately reflects the entire physical network and the processes used to manage it (including inspections, repair and renewal strategies).
This enables the creation and testing of different scenarios, the assessment of the impact of various AM policies and strategies on key performance metrics in order to make fully informed decisions based on clear projections.
A key aspect of digital twin technology is the unique capability to deliver interconnected insights. These allow asset managers to quickly identify and measure correlations between distribution grid performance, capital expenditure and maintenance costs and risks.
These insights enable DSOs to make trade-offs between CAPEX and OPEX while mitigating risks and reducing intervention conflicts – all in line with their business objectives. For the projections to be realistic, digital twins must also factor in the aging profile and behaviour of electrical assets. The potential benefits associated with the digital twin approach to asset management are huge and have the potential to take this crucial area to a new level of efficiency.
To achieve this, DSOs need a bigger and better toolbox to move from the traditional ‘connect and forget’ concept towards ‘connect and manage’.
About the author
Bram Alkema is Business Development Manager for Asset Management Solutions at Nexans.