The energy revolution is upon us 

Since the Paris Climate Agreement in 2015, nations around the world have been updating their national carbon reduction goals to match the increasing global appetite for decarbonisation. This has resulted in many countries setting carbon neutrality targets in time for the latter half of the century.

The International Renewable Energy Agency predicts that if individual country targets are met by 2050, renewable energy sources could make up 85% of the global power sector. In order to achieve the set targets and simultaneously maintain economic growth, we must increasingly saturate our power grids with electricity from renewable energy sources. This increase is problematic however, given the variable nature of some key renewable energy sources and the unreliability of their supply.

Simply put, many renewable power sources are intermittent – sunshine is not continuous, neither is wind.  This is an issue for a world looking to move away from fossil fuels, which have for so long been a trusted dispatchable energy source. When energy demand was high, we simply burnt more fuel, because we could. Faced by a climate crisis however, this is no longer a suitable option. If we are to maintain flexibility in our energy supply whilst transitioning into a carbon neutral future, we will need to couple Artificial Intelligence (AI) systems with our renewable energy goals. In doing so, we will meaningfully challenge fossil fuels and successfully edge them out of our economies without compromising our growth.

More renewables calls for more Artificial Intelligence 

Currently, renewable energy does not offer us the same luxury of instant supply increase as fossil fuels. Therefore, they cannot independently meet the energy needs entrenched in our 24/7 societies.  This is because leading renewable energy sources promising to become the bedrock of our future are weather dependent (wind, solar), referred to as Variable Renewable Energy (VRE). Unlike fossil fuels, in the absence of the right weather conditions, VRE production cannot be easily ramped up to meet peak demands and avoid blackouts. Moreover, often VRE source may become available when the electricity demand is low. This leads to curtailed energy, aka wasted opportunities to harness the power of renewables. The option of generating and storing this energy at such times is possible, but storage solutions are still very costly and for now, seldom justify the expenses.

Despite the challenges facing mass uptake of VRE, it is increasingly possible to scale up renewable energy generation thanks to AI powered systems. The ability of AI to process large sums of meteorological data will enable us to accurately predict renewable generation capacity days in advance. In parallel, AI software can be applied to the ever-expanding Internet of Things (IoT) data to accurately forecast electricity consumption patterns in our communities. Such application of AI will allow us to precisely predict upcoming supply and demand fluctuations and make calculated choices to ensure a balanced grid, minimum power wastage and maximum cost efficiency. Countries across the world have gradually started applying AI in this way to overcome the intermittency related issues of renewables. A good example is the partnership between IBM and Denmark’s Energinet, where AI is used to optimise renewable generation capacity, test infrastructure resilience and foresee operational limits.

Moreover, we are seeing an increase in AI enabled software that provides smart energy storage solutions, effectively making VRE storage affordable for the end user. An example of this is an AI software called Athena” developed by the California based company Stem. Athena helps entities with on-site VRE generators to effectively plan when to generate and store energy themselves and when to buy energy off the grid based on weather patterns, market prices and forecast demand. AI technology is therefore improving the way those of us with on-site generation capabilities respond to peak energy periods. Thanks to AI we can now choose where we get our electricity from depending on what option makes the most economic and environmental sense. This can help us mitigate the costs of VRE and storage systems, whilst also de-stress the electricity grid and drive down the overall electricity price for consumers. Such freedom of choice will define the future of our energy usage and help us cut our energy bills in an environmentally friendly manner.

The energy transition is bringing increased decentralization of energy supply

As the energy transition moves ahead, our communities become increasingly saturated with renewable power generation capabilities. Instead of having select large power suppliers, renewable energy will be increasingly harnessed from a variety of entities across communities. This means power will be supplied from a multitude of entities that vary in size and capacity. This is what the energy sector refers to as the dawn of Distributed Energy Resources (DER). Given this diversification of energy supply, it is becoming necessary to transform our energy grids into ones able to manage multiple flows of electricity from different sources (DER), with different supply reliabilities. Essentially, it is all about modelling a sharing economy onto our energy grid, which will allow us to decentralise energy supply, minimise wasted energy and maximise economic benefits for all energy market participants. To achieve these goals, we need to ramp up the transition towards “smart grids”.  The conventional grid system will no longer be able to sustain the decentralised nature of power generation and the many variables associated with its proper management. Instead, AI powered smart grid systems will take over to support the transition towards renewable energy societies.
The sheer amount of data generated by DER and IoT requires AI systems to help make sound decisions about our energy flows. This reality has spearheaded the development of Virtual Power Plants (VPP) smart grid systems. As a network of distributed power sources, a VPP acts as an AI powered control system that aggregates the decentralised renewable energy units to balance supply with demand and help integrate VREs into the existing power grid. AI powered VPPs capitalise on the electrification of our households, businesses and infrastructure, devices that are able to “talk to each other” and share energy consumption data to ensure power is used efficiently across the whole community. Moving a step further, AI powered VPPs can also analyze the energy consumption data of willing entities and provide them with options for selling excess energy back to the grid.  These AI mechanisms will therefore make us more conscious energy consumers, whilst reducing our overall energy costs.

It is such AI innovation that will help us succeed in the energy transition, effectively catapulting the world into a renewable energy powered and economically efficient future. Gradually, we are taking our first steps into this future, with AI enabled VPP technology already being deployed in community clusters across the globe. Small scale “community” VPPs are laying the groundwork for villages and towns to effectively become self-reliant renewable energy powered societies. Utility and technology businesses are scrambling to hone the emerging VPP culture, with multiple companies, including Tesla, already offering VPP services to renewable energy powered homeowners.

Increased automation does not have to increase risk

As we digitally interconnect more of our infrastructure and increasingly use integrated cloud systems to manage our communities, we are exposing ourselves to new vulnerabilities. What makes AI enabled power grids so effective and promising are also the reasons which put our energy sector at risk of cyber attacks and data breaches. These are high level risks, but ones which we are increasingly learning to mitigate. As with any new technology for key infrastructure, it must be developed in conjunction with security mechanisms. The power sector is no exception. Cyber defence capability development for our future power grids is crucial. However, this cannot be achieved solely through technical defence mechanisms. Every one of us needs to understand and take steps to limit the vulnerabilities inherent in our automated systems. Having an interconnected, decentralised and digitally optimised society gives each citizen an increased responsibility to sanitise their digital space. Digital hygiene practices will therefore become critically important for the safety of our societies. It is a notoriously challenging outlook when one realises that with growing digital connectivity of society, finding a weak link to exploit in the system seems likely. However, this is only if we assume that AI powered systems will be developed ahead of cyber defence capabilities. Current trends indicate however, that AI powered cyber defence mechanisms will become the cornerstone of national security.  Security of our utilities concerns national security. As such, the energy transition must be viewed through a wider lens of the fourth industrial revolution. As technology continues to develop, all aspects of our lives become more automated and integrated. Our defence capabilities will follow suit.

We must have confidence in our ability to overcome the challenges that we will face, whilst not letting this confidence preclude the development of necessary cautionary measures.

If we are to fulfill our ambitions of becoming carbon neutral in the nearest future, we must couple our goals with technological innovation. Artificial Intelligence will revolutionise our societies in more ways than we can imagine – may it be in the service of a sustainable and climate conscious future.


Written By Ketevan Papashvili

Co-Founder of the AIBE Summit



Air Travel and AI, Ready for Takeoff ?
The Air Travel Industry has seen multiple changes in its market throughout the past century. With the digital revolution currently underway actors in this sector need to embrace emerging...
Manipulation and Disinformation: AI-driven Personalisation in the Media
The Individual and Societal Effects of AI-driven Personalisation in the MediaNever has technology permeated society so deeply. Nonetheless, our digital ecosystem seems to struggle in reconciling the...
GPT-3 : The paradigm shift in AI
OpenAI released its beta version of GPT-3 (Generative Pre-trained Transformer 3) on June 11th, its brand new autoregressive language model that uses deep learning to produce human-like text. Since...
AI and Grand Strategy. False Promise or Whispered Dream?
Eschewing the typical approach of past articles, this piece takes a look at AI and grand strategy through the central contention of Goliath, a new book on war and politics by former paratrooper and...
AI in Recruitment: Who’s reading your CV?
You do not need to have finished your studies to realise it: internships and job positions are incredibly competitive. Around the world, students and graduates are trying to be offered a place...