Living on the ‘Grid Edge’: Latest Trends in Clean Energy

When one imagines innovation, perhaps the U.S. electric grid is not the first thing that comes to mind. But the power system is quickly evolving to adapt to the challenges of the 21st Century; new ideas, products, and services are being put to work.
Smart thermostats are being installed in many more states and can enable better two-way communication between customers and energy providers
Credit: U.S. Department of Energy

When one imagines innovation, perhaps the U.S. electric grid is not the first thing that comes to mind. But the power system is quickly evolving to adapt to the challenges of the 21st Century; new ideas, products, and services are being put to work. That was never more evident than at the recent Greentech Media (GTM) Grid Edge Innovation Summit.

Utilities, tech companies, power developers and generators, regulators, and financiers attending the summit shared thoughts on how to make our electric grid more efficient, clean, and reliable.

What does 'grid edge' mean?

According to GTM, grid edge is a term used to describe technologies and business models that advance a decentralized, distributed, and transactive energy grid. This includes physical infrastructure assets (such as smart meters), network or control software, applications, and data analytics tools. That means that utilities, regulators, and companies are creating ways to go beyond the traditional electric grid structure and enable customers to take a more active role in generating and trading electricity. While there are still several challenges to address, grid edge technologies can help contribute to a more efficient, flexible, and reliable electricity system.

1. Behind-the-meter distributed energy resources can provide benefits to the grid

Distributed Energy Resources (DERs), unlike centralized power plants, are spread-out physical and virtual assets that can be aggregated to meet customers’ energy needs. Examples include distributed sources of generation, such as rooftop and community solar, as well as products such as electric vehicles and smart thermostats. Behind-the-meter distributed energy resources are installed on the customer’s side rather than dispatching resources from a centralized power plant. According to GTM, distributed energy resources are expected to double from 46 gigawatts (GW) in 2017 to 104 GW by 2023. For context, the total solar PV capacity installed is currently 55.9 GW, enough to power 10.7 million American homes.

Behind-the-meter distributed energy resources can defer the need for upgrading transmission, generation, and distribution infrastructure. This means that utilities can avoid building new poles and wires that would otherwise be needed to transfer electricity from centralized power plants. New York and other leaders in clean energy are exploring the benefits of these “non-wires alternatives.” Decentralized systems can also help improve the reliability of the grid, especially in times when the electric grid experiences stress. For example, during Hurricane Sandy in 2012, several pockets of New York City that had distributed energy resources like rooftop and community solar that were able to maintain power when the storm led to widespread outages elsewhere.  

2. How we collect vast amounts of data will shape the future of the energy industry and could better inform our energy system

States are increasingly adopting “smart meters” (also known as advanced metering infrastructure) that allow utilities to collect and provide more information about a customer’s energy use through a wireless network. Smart meters have many benefits: they allow utilities to better understand patterns in customers’ energy use, further enabling them to design better programs and respond quickly to longer-term needs. According to GTM, since adopting smart meters, the frequency of utility data collection has increased from 12 meter readings per year to daily readings of data in 15-minute intervals. This is equivalent to checking an electric meter 34,680 times a year! Coupled with products such as smart thermostats that can be programmed remotely, customers and utilities are deluged with information. GTM estimates that by 2023, 55 million smart thermostats will be installed, accounting for 28 percent of U.S. residential households.

How to make use of this information will be key as we move into the future. Utilities and software companies have started to develop new platforms to collect, store, and analyze higher volumes of data. However, there are still many opportunities for enhancement in storing and effectively utilizing higher volumes of information. Monitoring the effectiveness of energy efficiency programs, communicating with customers in case of outages, and providing technical assistance are just three applications of improved data analytics.

While more information helps to improve efficiency, it turns out that more data requires more energy to process and store it. Several companies that host large data servers, such as Google and Microsoft, are procuring renewable energy to support an increasing share of their operations. This is a step in the right direction that recognizes the need to serve our increasing energy needs with clean energy. Further analysis is still needed to fully understand and minimize the environmental impacts of processing vast quantities of data.

3. New analytical tools and advances in computer science can deliver insights that can make our energy system more transparent and efficient

Blockchain

According to Merriam-Webster, blockchain is a digital database containing information (such as records of financial transactions) that can be simultaneously used and shared within a large decentralized, publicly accessible network. This information is stored in a transparent and permanent way. So far, blockchain has been used primarily for transactions in the financial services industry, but it has many potential applications in the energy industry as well.

According to Bloomberg New Energy Finance, there are 135 companies working in the blockchain and energy space, and $143 million was raised in investment deals in this field since 2017. For example, blockchain can be used to better track Renewable Energy Credits (credits issued to keep track of renewable energy generation) by storing the information in a more transparent and granular way. Because blockchain does not rely on a centralized source to store and process information, experts predict that peer-to-peer trading could eventually allow people to directly buy and sell energy generated by rooftop solar or community solar projects to each other.  

One major concern is that blockchain technology can be very energy intensive. Though exact estimates vary based on methodology, some experts estimate that bitcoin, a digital currency and the largest current use of blockchain technology, consumed over 2 GW as of January 2018. This consumption is approximately equivalent to the energy usage of 1.7 million average Americans.

Companies are exploring ways to reduce the energy impact. For instance, relying on methods such as proof-of-authority or proof-of stake validation is far less energy intensive than proof-of-work validation, which is the method that is primarily used today. The proof-of-work systems enable anyone to compete to solve the complex calculations to validate transactions. On the other hand, proof-of-stake systems are validated by consensus by trusted industry validators and this requires a smaller volume of calculations and consumes less energy use.  As demand for blockchain grows, it is crucial that the industry continues to develop and scale technology that can leverage the benefits of transactive energy without leading to major spikes in global energy consumption and emissions.

Artificial intelligence and cloud computing

Artificial intelligence is a field in computer science that trains computers to perform human tasks. Machine learning is an approach within the field of artificial intelligence that allows computers to recognize patterns and draw insights from large amounts of data. Investors, energy service organizations, and utilities are beginning to investigate and invest in the many ways that machine learning can help make the power, transportation, and building sectors more efficient. For example, better analytics can help grid operators more effectively predict and match energy demand and supply. This will be increasingly important as the number of DERs increase and more data becomes available. For example, a utility company in the United Kingdom is using artificial intelligence to predict energy use and help optimize the use of clean energy technology such as battery storage.  

Cloud computing is a technology that delivers computing services – such as access to computing and data storage -  over the Internet. This technology allows us to store and share hundreds of photos, send emails, and stream movies and music, to name a few applications. In the energy world, storing a large amount of data that is collected from devices such as smart thermostats can help utilities design better programs that allow customers to reduce their usage at times where there is highest energy demand, thereby reducing the use of dirty peaker plants and associated emissions.

Making the grid edge mainstream: Challenges and opportunities

As the cost of renewable energy decreases and new technologies enable us to better predict and analyze power systems, there are huge opportunities for radically changing the way we get, use, and interact with the energy system. However, it is imperative that technologies such as blockchain evolve to be more energy efficient and are powered by clean energy. As technology evolves, new regulatory frameworks are starting to be considered to provide states, utility companies, and other players guidance and incentives to innovate. While the industry is headed in the right direction, there is much more that needs to be done to move past pilot programs and incorporate technologies at scale in a way that aligns with the urgent global need to slash carbon emissions and protect air quality. NRDC looks forward to continuing to monitor the potential impacts of these technologies and how they can play a role in the clean energy transition.