Big data and modelling data: Encoord on data in energy

As data takes centre stage in the energy industry, new means of tracking and modelling will be required to catalogue and interpret this data. JP Casey speaks to Encoord’s Carlo Brancucci about data in the energy industry, and the company’s SAInt platform.

Encoord’s Carlo Brancucci

Credit: encoord.


he global energy industry has undergone some of the most dramatic changes over the last few years. With external forces such as the need to decarbonise, and internal pressures such as the desire to incorporate data into operations, driving power production and management, the energy industry of the future, and indeed of the present, is significantly different to the one of the past.

Using financial value as a benchmark reveals this trend. In 2020, the value of big data within the energy industry was expected to grow at a combined annual growth rate (CAGR) of 10.22%, itself an impressive figure, but one that has since been revised upwards to a CAGR of 11.28% up to 2026.

Zooming in on just the smart meter industry, itself something of a standard-bearer of greater integration of data into the decision-making process, this sector saw its value more than double from $6.3bn in 2011 to $13.1bn in 2018.

Energy producers, as well as consumers, have also experienced this phenomenon, with products such as digital twins now more commonplace than ever in the industry. Yet with an increasingly complex array of programmes and systems in place to track, manage and manipulate data, could the sector be in danger of saturating itself with information?

We speak to Carlo Brancucci, co-founder and CEO of energy software company Encoord, about the digitisation of energy, and its SAInt network planning software.

JP Casey: Do you think there will be an increased need for modelling and predictive software in the energy industry?

Carlo Brancucci: In order to reach a carbon-neutral future energy, planners will need to stop planning energy networks independently and begin to model them as coupled networks. When they are not modelled as coupled networks, planners can miss out on decarbonisation opportunities, or even worse, a failure in one network that could lead to the failure in another energy network.

An example of this was earlier in 2021, when power was cut to millions of Texans for several days as plummeting temperatures created cascading impacts on the electricity, gas and water networks.

Frozen gas wells and supply lines, coupled with power plant equipment malfunctions caused by weather, and scheduled maintenance, rendered an estimated 45GW of electricity generation offline and led to dozens of deaths. Proactive coordinated planning of the natural gas and electricity networks could have contributed to the prevention of the energy network failures.

How would you define “coupled” energy networks, and what role could they play in the future of the global energy sector?

Coupled energy networks are created when any two different networks, like electricity, gas, heat, or liquid networks interact with each other at a coupling point. Examples of coupling points of energy networks include gas-fired power plants, as they generate electricity and consume natural gas; and power-to-gas facilities, as they consume electricity and create gas, such as hydrogen, which can be injected into gas pipeline networks.

Planners can take advantage of these interacting energy networks and unlock new flexibility and energy storage options. As we introduce more intermittent renewable energy sources to our networks, there is an increasing need for flexibility in electricity grids.

Taking advantage of the flexibility and storage options where energy networks interact will help decarbonise the electricity generation sector and will also be important in creating carbon neutral fuels for hard-to-electrify industrial processes.

Coupling energy networks, in a way, is like benefitting from a good public transportation network. There are different types of transportation options and depending on your goal – fastest, least expensive, smallest carbon footprint – you will need to take a different combination of transportation options.

If you had to only take one mode of transportation it may be too expensive, too long in duration, or may emit a lot of carbon dioxide, but having a choice between transportation modes gives you flexibility to meet your goals.

What is SAInt and how could it be used to inform decision-making in the energy industry?

SAInt, short for Scenario Analysis Interface for Energy Systems, is a comprehensive energy network planning software that can run simulation and optimisation models of both independent and coupled energy networks. By modelling the integration and coordination of coupled energy networks, SAInt can help decision-makers plan for the decarbonised energy networks of the future.

With SAInt, modellers no longer need to iterate between different modelling software to analyse the interdependencies between different energy networks. In a single platform, SAInt can model electricity and gas networks and can quantify the synergies and interdependencies between the two networks. It can also model scenarios with increased integration of renewable energy sources and hydrogen.

With integrated wind and solar meteorological datasets to support robust modelling of variable renewable energy generation, SAInt makes it easier to model increased amounts of renewable energy and its effect on energy networks.

Examples of ways to use SAInt include power system planning to inform integrated resource plans; optimise investments in generation, storage, and transmission assets; and perform renewable integration studies.

[Another example would be] studying how the operation of electricity and gas networks can be coordinated to enable higher penetrations of variable renewable energy sources – such as wind and solar power – into the power system by operating gas-fired power plants more flexibly.

What challenges remain ahead of a broader adoption of SAInt, and how do you plan to overcome them?

Obtaining data from multiple energy networks in one region [is one challenge]. For a long time, energy network operators have been planning energy networks independently. Because of this, there is usually a lack of data communication between operators of different energy networks. The good thing is that more data is becoming available every year which can make the use of tools like SAInt more valuable.

[Another challenge is] getting planners who have been using other planning software to switch to SAInt. There is a long education period to learn with any planning and modelling software. We are finding some groups prefer SAInt because of its intuitive interface and ability to model multiple networks in a coupled way.

[The final challenge is] getting planners to find the value in planning software as some do not use any planning software. There are plenty of decision-makers who are not using energy network modelling tools to make decisions.

Educating planners on the value of modelling tools to gain insights on the impact of potential decisions is a huge challenge but also a large opportunity. The increased availability of data and computational power that we see every year makes tools like SAInt more valuable and more impactful.

How could a greater prevalence of modelling services aid in decarbonisation efforts?

Greater prevalence of modelling services will enable energy network planners to create a roadmap to decarbonisation. If energy networks were planned in a coupled manner, planners and operators would be able to unlock flexibility and storage opportunities between energy networks and would allow utilities and grid operators to invest in the assets and upgrades that can help achieve decarbonisation at a faster rate.

An increase in renewable penetration as a part of the energy mix also means increased short- and long-term variability. In order to achieve decarbonisation goals, network operators will have to leverage all types of flexibility both in their own energy networks to fill the gaps of generation, and will benefit from leveraging the opportunities at the interface of other energy networks.