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Enhancing Utility Business with Data Analytics, Blockchain, and Artificial Intelligence

image credit: Port of Rotterdam
Julian Jackson's picture
writer and researcher BrightGreen PR

Julian Jackson is a writer whose interests encompass business and technology, cryptocurrencies, energy and the environment, as well as photography and film. His portfolio is here:...

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This item is part of the Special Issue - 2021-12 - Data Analytics & Intelligence, click here for more

Big changes are impacting the energy business. We need to rapidly transition away from carbon-intensive fossil fuels to renewables before climate catastrophe gets worse than it already is. Unfortunately, society is limited not necessarily by technology but by existing systems. Large power generation facilities, linked by an extensive grid all over the country, are the opposite of flexible microgrids using advanced data technology to supply energy to smart appliances.

In modern "western" societies, we have already sunk a considerable amount of capital into existing systems, so we need to make those more agile: we can't knock them down and start again. Many developing countries, which never had the chance to create these structures (and often have the blessing of plenty of solar power capacity), can leapfrog old technology to their benefit.

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By merging AI, advanced data analytics, and the burgeoning technological breakthrough that is blockchain, developed economies can reduce energy costs, increase energy efficiency, reduce carbon emissions while still providing the electrical energy to keep society running.

What is the Blockchain?

A blockchain is a secure and decentralized immutable database shared by all parties in a distributed network where transaction data can be recorded and transparently accessed. Although many uses of blockchain are financial assets, e.g., Bitcoin, the underlying technology can have many use cases. In the same way that an internal combustion engine can power a family car, a farm tractor, or a huge truck – they are all used differently, but the underlying technology is the same.

The synergies possible in the utility field by combining all three technologies (and others like IoT, electric vehicles) will be increasingly important in the future. Let's look at a couple of use cases.

Distro: The Port of Rotterdam

The Port of Rotterdam in the Netherlands is one of the busiest ports in the world. In August 2020, the first high-frequency decentralized energy trading platform was successfully piloted there. Jointly developed by S&P Global Platts and BlockLab, Distro is a new microgrid electricity trading platform that uses AI and blockchain's distributed ledger technology to provide energy efficiencies.

The Distro platform optimizes supply and provides power to local consumers using high-frequency trading. Local energy prices can fluctuate rapidly within the system, depending on power needs. The result was an 11 percent reduction of energy costs for end-users while energy producers received 14 percent more revenue. Battery storage returns on investment were boosted by 20 percent. In addition, 92 percent of all solar power generated was consumed by local businesses, a significant efficiency gain.

Innowatts – Merging Smart Meters and Data Analytics

Houston-based Innowatts' software transforms how energy providers understand and serve their customers. The platform uses AI and knowledge from more than 45 million global meters to help energy retailers, utilities, and grid operators process data, understand their customers, and make businesses operations automated and smarter. By using AI and machine learning, they enable more precise business decisions. Using this technology, companies such as Portland General Electric report a more reliable grid, increased profits, better customer experiences, and lower carbon emissions.

Using this AI-enhanced platform, utilities can analyze and apply insights from large volumes of historical meter data in a fraction of the time it takes with internal or alternative vendor solutions. By having a superior understanding of the data, better business decisions can be made, for example identifying the unique drivers of every load profile, including weather and daily use patterns. Segment those patterns and engage those customers most effectively.

Is AI the Way Forward with Carbon Capture?

Energy-intensive industries need to reduce their GHG emissions as much as possible. Studies show that using AI to analyze the emissions pathways makes substantial reductions in damaging carbon releases feasible. Boston Consulting Group estimated that by using AI, companies could achieve 5  to 10 percent of the 50 percent reduction needed by 2030. That would be a cut of between 2.6 and 5.3 gigatons of CO2e globally. Numerous other projects are in pilot stages using advanced bioreactors to process waste to absorb CO2 while producing useful end products – such as clean water for agriculture. Optimizing these will involve data analytics, AI, ML, and probably blockchain-based accounting systems for immutability and transparency.

There are numerous options for innovative projects to benefit society by deploying the most advanced technology to overcome humanity's severe problems in the next few decades. The synergies possible from these new technologies will be essential in striving for a better world in the light of the need for more clean electricity as we move away from fossil fuels.

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