The Smart Grid: How AI Is Powering Today’s Energy Technologies

Like oxygen, the power grid is essential to modern life but is not always top of mind – until problems occur. Today, aging grid infrastructure is taking a beating from severe weather events around the world, resulting in power outages that threaten health, safety, and economic activity. At the same time, a number of other factors are also putting pressure on century-old grids. The way that energy is produced is rapidly changing – more wind and solar, less coal and fossil fuel. This shift requires new processes and ways of managing. The “who” is also shifting, with energy now produced not only by the major energy companies, but also by a plethora of new competitors and prosumers (consumers who produce energy).

And not only is the natural world changing fast, but the technological world is advancing at a gallop as well. Cloud-connected artificial intelligence (AI) technologies like machine learning, data analytics, and the Internet of Things (IoT) are driving the advancement of smart grids capable of managing far more complex power generation and distribution. These technologies herald significant opportunity for those in the complex energy ecosystem that are able to harness them.

What is a prosumer?

Prosumer is a portmanteau word combining “producer” and “consumer.” Energy prosumers typically remain connected to the central grid. However, they are also capable of producing and even storing energy – typically with photovoltaic solar panels and EV batteries.

Depending on the amount of power generated, this energy can either be used to offset monthly bills or be sold back as surplus to utilities companies or other energy distribution services. This model may be applied to both residential and commercial prosumers, with a growing number of businesses plugging their solar panels and EV fleets into the grid.

What is a smart grid?

A smart grid is a network that integrates energy distribution and digital communication technology in a two-way flow of electricity and data. This enables utility companies to optimize the generation, transmission, and distribution of electricity. And it also allows consumers to benefit from the stories all that data is telling – helping them to better understand the energy they use and even the energy they produce and store through things like solar panels and EV batteries.

What is the difference between the traditional grid and a smart grid?

The main difference between traditional systems and smart grids lies in the ability to exchange information in both directions across the network, from utility companies to consumers and vice versa. Some of the top features that differentiate smart grids include:

  1. Technology: AI, cloud, and digital technologies allow all the devices and assets within the grid to communicate, supporting better control and self-regulation.
  2. Distribution: Energy generated by prosumers and other renewable energy sources – such as solar or wind – can be intermittent and uneven. Smart grid technologies help to coordinate, store, and distribute power from such sources into a steady and reliable stream.
  3. Generation: Predictive analytics in smart systems means that high-demand strains can be forecasted and distributed to multiple plants and substations.
  4. Sensors: IoT sensors across the network can help detect risk early on, redistributing power to decrease outages and help balance loads without direct intervention by operators.
  5. Self-repair and predictive maintenance: Sensors can also be used to detect mechanical problems and do simple troubleshooting and repairs, notifying technicians only when necessary – before anything actually breaks down.
  6. Customer choice: More energy suppliers, cooperatives, and micro-generators can join the grid, allowing consumers to have more choice in how they receive energy.

Applications of AI in smart energy solutions: The utilities sector perspective

Artificial Intelligence is the driving “intelligent agent” behind smart grids – evaluating the environment and taking actions to maximize a given goal. AI is fundamental to the integration of renewable energy, the stabilization of energy networks, and the reduction of financial risks associated with instability in the infrastructure.

For instance, the self-learning, adaptability, and calculation capabilities of AI have significant potential to address the intermittent nature of renewable energy. An imbalance in peaks of production and consumption are often represented through “the duck curve” and can make these sources of energy difficult to control. The use of AI in smart grids will help address this challenge by rebalancing inequity between production and consumption loads.

Smart grid technologies help to make utilities sector activities more transparent and competitive. Some of the applications of AI and machine learning in smart grids include: 

Applications of AI in smart energy solutions: The consumer perspective

Recent surveys from the UK and U.S. show less-than-great customer attitudes toward utility companies. With the rise in energy suppliers and prosumers, utilities companies will need to leverage smart solutions to help nurture better customer engagement and satisfaction. Below are some of the ways smart grid technologies can help to improve customer satisfaction:

Recently, a UK distribution system operator announced a pilot project to use smart meter data to help consumers improve energy management, optimize network loads, and reduce carbon emissions. The trial could save customers millions of pounds and potentially reduce millions of tons of greenhouse gas emissions from the UK’s annual carbon footprint. This is just one example of the potential benefits of smart grids for customers and the environment.

Big Data in energy: Why it matters

From the point of view of both customers and utilities companies alike, it’s not simply the ability of these technologies to gather and manage large and disparate amounts of Big Data that matters – it’s the ability to leverage and understand all that data and use it to optimize power usage and inform operations. Big Data is key to helping:

How today’s utilities industry is preparing for the smart grid of the future

There is no question that the future of energy is moving toward more decentralized, flexible, and sustainable power provision. But we are talking about a global industry that is over a century old – and often must rely upon infrastructures from nearly that long ago to serve billions of people and their rapidly changing demands.

Other challenges include complex regulatory changes, the rise of prosumers, and new startups emerging in deregulated regions. Like any journey of business and digital transformation, the move to smarter grid management starts with a few cautious steps before breaking into a run. Utilities sector technologies are undoubtedly powering and enabling the evolution of this sector. However, for meaningful change to occur, utilities companies will need establish strong communication, customer engagement, and change management plans including:

The first step on the journey is to communicate with team leaders and subject specialists across your business, to break down silo walls and find the wealth of information often hidden within. Then, look at how you can implement smart technologies to drive your business forward.

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