Table of Contents
Artificial Intelligence: The Key to Renewable Energy Grid Resilience
- Artificial Intelligence (AI) studies how a computer or machine can simulate cognitive processes to analyse and recognise information with the ultimate goal of expanding human intelligence. There are four main types of AI: reactive, limited memory, theory of mind, and self-awareness.
- When electricity is produced centrally, it needs to be carried across long distances through power lines. If a single line is experiencing technical difficulties, it can leave many homes and businesses without power.
- The role of smart grids is more than just power delivery. It is a two-way connection of energy and information. With AI working within a smart grid, it can take into account millions of variables and data points, such as weather, demand, location, and generation assets.
- When it comes to implementing renewable technologies, there are many forces at play that make it difficult to switch over right away. One of the most significant factors is that destructive fossil fuels can make a lot of money in the short term (despite the fact that they are in limited supply). As a result, some people are not welcoming green initiatives.
With month after month of deadly winter storms and devastating summer wildfires, communities all over the world are left without power. As a result, politicians, energy experts, and customers are asking for investments to support vital upgrades to the ageing grid infrastructure. These improvements are long overdue, so better options must be explored to ensure the future of reliable renewable electricity.
Governments are still spending money on grid infrastructure to update long transmission lines from a centralised power generation source. By taking these measures, they are attempting to solve today’s problems by using the technology of the past. It is now time to welcome Artificial Intelligence (AI) to leverage decentralised renewable generation sources.
If the term Artificial Intelligence (AI) leads you to thoughts of science fiction and a dystopian future, you’re not alone. Thankfully, these concepts don’t correlate with the goals of renewable energy. New technology should not be feared, and through gaining a greater understanding, we can learn how these developments can benefit our energy infrastructure and help improve our natural environment. So let’s take explore some of the reasons why AI may hold the key to the future of renewable energy grid resilience.
What is Artificial Intelligence?
AI studies how a computer or machine simulates cognitive processes to analyse and recognise information that can expand human intelligence.
Before we delve into Artificial Intelligence (AI) and what it can do for the future of renewable energy, let’s start with the basics. Put simply, this trending topic is a computer science that aims to analyse the essence of human intelligence. AI studies how a computer or machine simulates cognitive processes to analyse and recognise information that can expand human intelligence. In recent years, AI has made some fantastic advancements in research and has been widely used in numerous fields.
AI research aims to make machines imitate functions that were previously reserved for humans. Consequently, the extent to which an AI system can replicate human capabilities has become the determining factor that helps us categorise the types of AI that are available today. Subject to how far you delve into the world of Artificial Intelligence, you can come out with varying AI classifications. To keep it simple, we will only mention the four main types of AI:
- Reactive – This AI has no memory and only responds to different stimuli.
- Limited Memory – This is an AI system that uses memory to learn and improve its responses.
- Theory of Mind – AI developments in this category understand the needs of other intelligent entities.
- Self-Aware – This AI system has human-like intelligence and self-awareness.
The application of Artificial Intelligence is becoming ever more prevalent, and it is expected that most industries will adopt it in some form in the future. Currently, AI initiatives in education, medical care, environmental protection, urban management, judicial services and other aspects have been performing well, and the technology is gradually infiltrating into all aspects of life. It is only natural that AI is also being entertained as a tool that might help us address increasing energy demands.
Renewable Energy and Grid Complexity
The millions of individual devices uploading and downloading electricity could potentially create chaos for the central electrical grids.
With the move to an electric world, more energy will need to be generated from decentralised, renewable sources. The giant and dated grids we currently have will need to run alongside microgrids, private solar panels, wind farms, and batteries. As great as this sounds from a sustainability standpoint, these changes will add complexity to energy grids all over the world.
Over the next ten years or so, there is set to be a massive increase in the use of electric vehicles, electric heating systems, and the production of distributed energy resources (DERs) such as solar panels and wind turbines. This will necessitate a delicate balancing act to match supply and demand without collapsing the grid.
In many parts of the world, there is a substantial push towards DERs as businesses, governments, and residential consumers progressively produce their own energy, primarily via solar panels. Many of these solar power systems also store energy in batteries and feed excess electricity back to the central grid. The World Energy Forum has predicted that around 36 million assets (such as solar PV, electric cars and energy storage devices) will be added to the grid across Europe by 2025. Their report suggests that these assets could be worth up to 89 million by 2030. The millions of individual devices uploading and downloading electricity could potentially create chaos for the central electrical grids.
The reliance we once had on a central utility to produce and transmit electricity is diminishing quickly. As a result, the utility companies will soon be forced to shift their business models. It will not be long until they are no longer the sole source of energy. However, this is not the death of the central grid. Instead, it will help to maintain a balance by shifting electrons from various origin points and storage devices to circulate energy where it is needed second-by-second.
Using Artificial Intelligence To Balance The Grid
An AI-centred grid system will potentially solve a lot of anticipated issues.
It is now possible to use AI software which helps decentralised energy sources to send any surplus electricity they produce to the grid, while utilities move that power to where it is needed. Likewise, energy storage in homes, cars, industrial facilities, and office buildings can hold excess energy when the demand is low. AI will then send out the electricity when power production is insufficient or unsuccessful.
There are a lot of areas that require careful coordination, forecasting, and optimising to help keep the grid balanced. A good analogy to help understand these complexities is to think of DERs as individual musicians in an orchestra. The utility is like the conductor keeping the orchestra in sync, and the AI composes the symphonies in real-time.
An AI-centred grid system will potentially solve a lot of anticipated issues. Moving away from an infrastructure-heavy system to one that is centred on AI will allow forecasting and control in seconds rather than days. This will result in a more robust and flexible grid that can adapt when unexpected occurrences arise.
Utilities, policymakers and regulatory bodies will need to start thinking about the roles they want to play in decentralised energy resources. The mixture of distributed energy producers will require exceptional coordination and management, and this is something the utilities can take the lead on. Many utility companies are facing a massive drop in customers purchasing electricity as an increased number of homeowners and businesses become energy producers themselves (thanks to rooftop solar panels and other DERs). For example, the size of a European median power plant has already fallen from 800 megawatts in 2012 to 562 megawatts in 2020. The drop will only get larger with time.
The majority of utilities will need to decide whether they will collaborate with existing software companies or develop in-house software solutions. These technological advancements require a massive shift in thinking. There are numerous dynamics to keep in mind – from legacy models of capital investment to energy demand management that impacts a growing number of privately owned assets. At the same time, much consideration will need to be put towards protecting customer data and privacy while safeguarding grid management and cybersecurity.
National and local governments will also have to rethink and accelerate their approaches to infrastructure spending, energy generation methods, and transmission infrastructure. Infrastructure-based solutions may offer more grid stability, but they require a lot of planning, construction and financial resources. Unfortunately, the current economic backdrop and lengthy political debates are likely to slow these much-needed investments. However, time is of the essence and climate change continues to create extreme weather events around the globe.
Investing in the existing centralised grids, with their systems of long wires and transformers, may no longer be the sensible solution to grid resilience. Instead, governments may need to plan for a future where communities and buildings generate their own electricity that is managed in real-time by software and AI.
Policymakers will need to consider the public financing of renewable energy generation and potentially launch incentives for more distributed energy production in homes and private industries. Globally, it may also be necessary for AI software to be regulated in order to ensure that projects operate interactively and transparently in ways that benefit the broader energy landscape.
Introducing Smart Grids
If a single line is compromised, it can result in whole communities downstream from the broken line being left without power.
A smart grid is much more than just a power delivery system. It is a two-way connection of energy and information. However, the future of smart grids goes beyond this to achieve maximum effectiveness and efficiency. It will also include distributed generation and AI.
Smart grid technology is a hot topic in the renewable energy sector as existing power plant systems in many countries are not built to accommodate the diversification of energy sources. When the demand outpaces supply with many existing systems, utility providers source energy from ‘peaker plants’ (backup fossil fuel-powered plants) with a minute’s notice. This just barely avoids a disaster. The problems will only intensify if nothing is done as consumer energy demand is only growing.
Many governments are prioritising their grid infrastructure, such as the U.S. Department of Energy (DOE). They are pushing for smart grid technology, with the aim to fully automate the power delivery network. The goal is to monitor and control every consumer and node to ensure a two-way flow of electricity and information.
The distribution of energy is crucial to smart grid infrastructure. When electricity is produced centrally, it needs to be carried across long distances through power lines. As a result, around 15% of the electricity generated is lost in transmission. If a single line is compromised, it can result in whole communities downstream from the broken line being left without power.
In many areas of the world, if there is a power outage or compromised line, the power company has no way of knowing there is a problem until a disgruntled customer picks up the phone and reports it. This is a backwards way of detecting outages and is a perfect example of the outdated technology that many grids are built on. It highlights one of the main benefits of distributed generation and the smart grid model. If there is energy being produced in multiple places, the power can be diverted from another nearby generation node to supply the areas affected by the compromised line. It enables the grid to become incredibly resilient and may even prevent power from being lost.
Supporting Smart Grids With Artificial Intelligence
AI needs to take into account the millions of variables and data points, including weather, demand, location, and generation assets.
Due to the sheer volume of data that is required for an operational smart grid, Artificial Intelligence is an indispensable resource. Here, AI needs to take into account the millions of variables and data points, including weather, demand, location, and generation assets. These technologies can also proactively decide where the power will come from and how much it will cost for every customer. Beyond the millions of switches that need to be flipped each second, many complex decisions must be made from moment to moment. This is when the power of AI becomes really crucial.
Acting on and learning from these patterns and decisions is part of what makes AI so perfect for smart grid implementation. A relevant example of this would be to consider the weather forecasts when deciding mid-term power generation strategies. If it is known that it is likely to rain for two weeks, utilities can actively scale up other energy production sources to offset the loss in solar and soften the knockback.
Another fantastic aspect of AI is the ability for the customers and the grid to be connected directly, which is a win-win situation. For example, customers can opt to have their washing machines start automatically in mid-day when demand may be lower (and energy is cheaper). This will save the customer money on their utilities, help to balance the grid’s overall load and reduce peaks in demand.
Additionally, with smart metering, the customers will be able to monitor every appliance and outlet, providing the bill payer with the full picture of their personal energy use. This can actively encourage energy conservation through sharing hard data on the impacts of even small changes based on their usage. Giving people detailed insights into their energy usage can impart a deeper sense of responsibility. If they can see in real-time what their appliances cost to run or the impact that turning off all the lights has on their energy usage, they may be more likely to make practical changes.
Implementing Renewable Energy and New Grid Technologies
One of the most effective ways to start a successful and meaningful transition is by demonstrating that there is more money to be made in renewable energy than fossil fuels.
When it comes to the implementation of these technologies, there are some unfortunate realities that should not be ignored. While it makes sense to switch everything to green energy and phase out fossil fuels from an environmental standpoint, the reality is, there are far too many forces at play to make the switch right away. One of the biggest factors is that fossil fuels have a history of bringing another kind of green (aka. money) to mind. As a result, some people who are involved in the industry may feel they don’t have much of an incentive to embrace eco-friendly changes with open arms.
One of the most effective ways to start a successful and meaningful transition is by demonstrating that there is more money to be made in renewable energy than fossil fuels. When customers and businesses are told they can potentially reduce their bottom line by switching to renewables, it makes them much more willing to adopt renewables.
Thankfully, renewable energy sources such as solar have become more affordable due to recent technological advancements. For example, solar panels are now cheaper to buy and install (not to mention more efficient), so any renewable energy investment made is likely to be recouped in a timely manner.
Developments such as AI, smart grid implementation, and large-scale distributed renewable energy generation are not abstract, sci-fi technologies of the future. They are here already, so we need to utilise them as much as possible. Given the technology we have access to, it is possible to make the transition to smart grid operations and renewables for many nations. It is now just a matter of turning these possibilities into real and widespread practices. Due to the climate change emergency, combining Artificial Intelligence and clean energy seems to be a smart response to an urgent situation.
Recent events in North America have shown just how vulnerable the current electric grids can be. Just as we should not be attempting to build a more powerful internal combustion engine, we should not be trying to rebuild the grids of the past.
It is a simple fact that AI adds huge value from both cost-saving and resiliency standpoints. We’ve seen fantastic results from AI implementation in other sectors, so we can only imagine the impact it could have at grid-scale. AI is arguably the key to a more resilient, sustainable, all-electric world and the solution for the grids of the future.
Frequently Asked Questions (FAQs)
How do electricity grids work?
The power grid is a network used for delivering electricity to consumers. The power grid includes generator stations, transmission lines and towers, and individual consumer distribution lines. The generator produces energy. Usually, electricity is transmitted at a very high voltage over the power lines that are dotted across the land.
What is a smart grid?
A smart grid is an interactive electricity network that facilitates a two-way flow of electricity and data with digital communications technology. This enables the grid to detect, react and proact to real-time issues and changes in usage. In addition, smart grids have ‘self-healing’ capabilities to fix problems.
Are smart grids better than regular grids?
The benefits associated with smart grids include more efficient transmission of electricity, quicker restoration of electricity after power disturbances, and better integration of customer-owner power generation systems (including renewable energy initiatives like solar panels).
What is grid resilience?
Grid resilience is the ability to endure and decrease the magnitude or duration of disruptive events. It also includes the capability to anticipate, absorb, adapt to, and rapidly recover from such events.
Can Artificial Intelligence help renewable energy?
AI has the ability to maximise the untapped potential of renewables when supported by other emerging technologies, such as smart grids, sensors, big data, and distributed ledger technology. If the renewable energy sector does not embrace AI, it is at risk of falling behind.