The big may not always beat the small, but the fast will always beat the slow. Getting ahead in the energy transition is not a one-off change or a silver-bullet solution, and size is absolutely no insurance for the future of anything let alone energy trading. Just as McDonalds® now looks at and learns from BP Fuels as one of its competitors for convenience fast food outlets, the energy sector must now be smart and realise that fast track innovation can and will come from other sectors, similarly, organisations should look elsewhere to realise the art of the possible.

Scott Logic has written a number of blogs and papers on Open Banking and how APIs and microservice design principles were applied not only to achieve regulatory compliance in retail banking but to create a new fintech ecosystem. One which innovates and delivers new value at a pace not previously seen in the sector. This transition to open banking and beyond is directly relevant and applicable to the energy transition in its use of data previously unleveraged to support new value propositions at scale and speed.

Is the commodity trader being commoditised?

With a growing percentage of renewable sources being included in our nation’s energy mix (which can be viewed on the Scott Logic app Powerwatch) and radical changes to consumers’ typical energy consumption profile, volatility is making energy demand forecasting more difficult. Models which have been used for years are becoming irrelevant, and without change, traders’ margins will be compromised.

With connectivity capabilities such as IoT (Internet of Things), older assets are being connected and all aspects of their operational performance data are being exposed through the use of APIs. Meanwhile, new energy network assets “out of the box” are completely sensitised and connected to modern trading data processing engines.

Nothing is out of reach to the modern trader and their increasingly automated decision making. With smaller and more complex margins spread across numerous energy markets, human forecasting and trading against those forecasts is less profitable. Just like the investment banking sector, algorithmic trading is taking care of more and more of the highly iterated lower value energy trades, freeing the trader to move up the value chain and analyse multiple concurrent markets (a technique known as stacking) to create better margins. Traders increasingly need data science competencies and tools to augment demand factors into energy forecasting.

Automated flexibility trading

The target of NetZero emissions is driving renewables into the energy supply infrastructure at pace, creating new challenges in the balancing and operating of the grid. On Monday 21st September 2020, the National Grid Electricity System Operator (ESO) used batteries to help balance the power grid in Britain for the first time. Tesla became the first user to go live with National Grid ESO’s new application programming interface (API), using its automated real-time trading and control platform, Autobidder, to manage first-time balancing mechanism (BM) access for the battery storage plant. The API rollout marks the latest development in the ESO’s plans to remove barriers to access (through the use of APIs) for a wide range of providers such as batteries and small distributed generators.

Whilst large scale batteries connected into transmission and distribution networks will become increasingly common, it will be the growth of Electric Vehicles (EVs) and their mobile batteries which will make up an increasing proportion of flexibility trading to offset the volatility in power supplies. With recent announcements from the automotive sector of new EVs hitting price points approaching £20,000 by 2023, the scale-up of Virtual Power Plants (VPP) across large numbers of small vehicle hosted batteries is almost upon us.

The trading of energy hosted in batteries in scenarios such as Grid to Vehicle (G2V) and Vehicle to Grid (V2G) is complex from a number of perspectives. Firstly, vehicle batteries are too small on their own to be of value to the grid and must be assembled virtually to present higher levels of power capacity. Secondly, only through agreements and tariffs with the battery owner can it be traded successfully. Thirdly, batteries’ economic life is dramatically impacted by how they are charged/discharged, so trading batteries can’t be done solely based on energy market demands. A very small number (one) of automotive companies has developed automated VPP trading platforms to cover all aspects of G2V and V2G services. The remainder of the transport sector globally is planning to build and share services through industry agreed APIs.

You are not as unique as you think

Do you see the picture, the emerging trends, the fundamental enablers to sustainable change in the energy sector, energy trading and the energy transition? We have given some examples of areas across the energy data network where Modernising Energy Data (MED – Ofgem) has a major if not defining role to play. We could have spent more time discussing de-carbonising technologies and their API connectivity to trading, but we will save that for another day.

The power industry and trading markets must now mobilise if they want to be a successful part of the energy transition. The smart organisations understand that their digital platforms are their differentiating factor, they understand that their legacy infrastructures need to be adapted, extended and interfaced while assuring their businesses that no disruptions to “normal business” will occur. With a strategic approach to systems, software and connectivity by implementing APIs on the edge of modular encapsulated microservices a sustainable capability can be developed at price points more palatable than large scale systems replacement.

If we have learnt a lesson from years of systems redundancy, it is that new systems on their own do not provide a platform for legacy management and long-term value extraction.

So why not accelerate your learning and capability from others and apply it to your energy trading environments. Why not leverage the learning of those who have taken this journey such as the banking sector and their move to Open Banking? You could even work with leading technology companies who helped develop the open banking APIs and continue to play a role.

Why not plug Scott Logic into your Modernising Energy Data programme?

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