empower communities, and improve energy security by offering energy independence and protection during emergencies. To put it another way, it's a smart way to meet growing demand, while improving sustainability.13
Already decentralized networks are taking shape in the UK. Aberdeen City Council, for example, turned to district heating – the supply of heat from one source to a district or group of buildings – to solve the problem of fuel poverty in some of the city's housing stock, reducing typical fuel costs for tenants by 50 percent and cutting carbon emissions by 45 percent in the process. The council has plans to extend the network beyond the 1,500 flats and handful of municipal buildings initially connected in the scheme, and the team is also helping other local authorities realize the same benefits.14
Elsewhere in the UK, Bristol City Council has been working with the Carbon Trust to develop four district energy schemes across the city with a goal of reducing carbon emissions, cutting costs, and supporting future development in the city.15 Meanwhile, in the US, startups like Urban Energy are enabling distributed energy by turning rooftops in New York into community solar gardens.
In other words, public bodies and consumers are already beginning to realize that they can do it better than established energy providers and are taking control of their own energy destiny.
Overcoming the challenges
But it's not all rosy. One of the main challenges with decentralized energy is the lack of institutional knowledge and experience on how to develop and implement such projects, although organizations like the Carbon Trust and Urban Energy are helping to solve this.
Another challenge is how to cope with fluctuating demand patterns within these smaller grids (unlike, say, huge energy providers that can easily produce enough power at peak demand times). This is where technologies like AI can help (more on the digitization of energy coming up later). Using data from smart sensors, and smart energy storage solutions, decentralized systems can better manage local energy requirements and ensure power is supplied where and when needed. An example of this comes from Cornwall's Local Energy Market, which announced in 2019 that it had reached a “flexibility breakthrough” after installing a combination of solar, battery systems, and monitoring equipment into 100 homes and 125 businesses across Cornwall, England.16
Related to this is the term “Internet of Energy” (IoE). Like the Internet of Things (see Chapter 2), the IoE relies on smart devices to increase efficiencies and improve control. As an example, US-based startup Lumidyne Consulting's SPIDER system applies data modeling to distributed energy resources, to predict impact on energy demand and aid the planning of energy distribution. Or there's British startup Distributed Energy, which provides demand management solutions to manage small and mid-sized companies' power requirements, enabling greater adoption of renewable energy. Tools like this will help to manage risk and uncertainty in decentralized networks and make moving away from standard grids a viable option for more energy users.
Trend 3: The Digitization of Energy
This final trend goes hand in hand with the first two. The future of the energy sector will involve smart, decentralized grids that can understand which houses and buildings need energy at which time. With the energy being produced by an increasing variety of zero-carbon sources, technology will play an essential role in managing these complex energy networks of the future.
What do we mean by digital transformation?
To realize this vision of smarter, more diverse energy grids, we need intelligent devices and technology that: a) help us communicate with the grid so demand can be monitored and managed, and b) help us all reduce our energy consumption. I briefly alluded to some examples in the previous section, but let's see what else is involved in the digitization of energy (many of which are key tech mega-trends covered in the previous chapter). Together, these digital solutions have given rise to the term Energy 4.0, a play on Industry 4.0 or the fourth industrial revolution that I referred to at the start of Chapter 2.
AI and predictive analytics : These are used to analyze and predict demand, adjust where power is drawn from on distributed grids, and predict equipment failures. GE, for example, uses AI to predict failures ahead of time at wind and solar plants.17
The Internet of Things: In particular, the use of smart home thermostats and home energy management systems such as Google Nest is helping consumers cut their energy usage and heat their homes more efficiently.
Blockchain: From secure, smart contracts to facilitating distributed networks, blockchain could be a transformative technology for the energy sector. In one example, Turkish startup Blok-Z's blockchain technology enables anyone to access economical, transparent and traceable green electricity.
Quantum computing: The sheer power of quantum computers is ideally suited to solving the unique and vast challenges facing the energy sector. As an example, US-based startup QC Ware provides quantum computing solutions to help optimize energy use (including energy prediction and demand management).
Digital twins: A digital twin is an advanced digital duplicate of a real-life object, system, or process. By using information gathered from IoT sensors in the real world, organizations can model changes and try them out in the digital twin without making expensive or high-risk alterations to the real-life counterpart. BP, for example, uses digital twins to model new oil field production.18 In another example, MHPS-TOMONI's digital twin technology can create a virtual replica of a power plant or even an entire grid.19
As that last example suggests, these technologies don't just apply to innovative decentralized energy grids and renewable sources. Even with traditional, centralized operators, digital innovation can help energy providers cope with uncertainty, make better decisions, and improve efficiency in an increasingly competitive field. According to McKinsey, energy companies that have invested in digital innovation have seen up to 10 percent improvements in production and yield, and up to 30 percent improvements in costs.20
Overcoming the challenges
So far, these digital technologies haven't been fully exploited by the energy sector. Finding the value from digital can prove tricky, particularly for traditional energy companies who can be slow to change.
Largely this is because energy providers face some unique complications, such as health and safety risks, the large amount of capital invested in existing assets (such as power plants, pipelines, and offshore platforms), and the capabilities of frontline workers (who are often operating in remote or hard-to-reach locations). What's more, many oil and gas companies are entrenched in an engineering mindset – which tends to favor caution, in-depth planning, and a “right first time” approach – versus the flexible, agile, fast-moving mindset that digital transformation often requires.
Many sectors are coping with similar challenges, but the energy sector must contend with them all at the same time,
