Energy has been, is currently, and will continue to be one of the most important utilities at humankind's disposal. Energy drives economies and helps sustain societies (in both renewable and non-renewable forms), and it dominates global markets. On top of this, as the world continues to tread further into a new digital age (one populated by an abundance of innovative devices and applications), the demand for energy around the world at both enterprise and consumer levels is expected to grow exponentially.
However, while electric grids are a major driver of economic growth and prosperity in many countries, policies mandating how energy is sourced and distributed rarely consider the implications of energy affordability, especially in relation to vulnerable populations or lower-income and disadvantaged communities. Access to clean, affordable energy is a crucial piece of the puzzle when it comes to eradicating poverty, improving our collective health and education, promoting economic growth, and combating rampant climate change.
This problem of energy inequity, while it is certainly one that plagues nations all around the globe, is very much a challenge for many citizens in the United States, in particular. According to DOE's Low-Income Energy Affordability Data (LEAD) Tool, the national average energy burden for low-income households, which makes up 44% of U.S. households or 50 million houses, is 8.6%, three times higher than for non-low-income households which is estimated at 3%. Depending on location and income, energy burden can be as high as 30% in some areas.
"Luckily, the rapid advancement of digital innovation is now a breakthrough part of the solution," said Ollie Hynes, founder of Hub Controls, which has developed an advanced home comfort intelligent automation system based on a low-cost annual subscription. "There are already a variety of technologies that can play a pivotal role in improving energy equity at a consumer level, with the most prominent being artificial intelligence and its automated capabilities. AI is already revolutionizing nearly every industry it permeates, and the energy sector is no different with the help of AI-driven energy systems, especially when used on a large scale."
AI-driven energy systems have shown immense promise in the energy sector, as the technology has the potential to revolutionize the industry toward a digitized, distributed, decarbonized, and democratized energy system. AI technologies are already being integrated into every aspect of the energy sector, from exploration and production to distribution and consumption, as energy companies strive to meet the ever-increasing demand for power while simultaneously reducing their carbon footprint.
The growth of artificial intelligence (AI) in the energy sector has been nothing short of remarkable. AI-driven energy is no longer just a dream, with the AI in the energy and power market coming in at $3.103 billion at the end of 2021. However, experts are predicting swift growth at a CAGR of 24.68%, bringing the estimated value of the AI in the energy and power market to a whopping $14.527 billion by 2028.
"While AI-driven energy systems are already popular among average citizens, the technology can also be applied at a larger scale, as local organizations like the New York City Housing Authority (NYCHA) and other state-level governments can leverage the application to greatly benefit their consumers," Hynes explained.
"For example, most prominently, is the improved efficiency the technology can enable for public housing organizations and local governments, which in turn saves money for both the organizations and their tenants," Hynes said. "By automating repetitive tasks and streamlining workflows, AI technology enables government agencies to allocate their resources more effectively, ultimately leading to improved service delivery for citizens."
On top of improved efficiency, AI also offers enhanced data generation and analysis, which once again can be put towards making energy more affordable for all citizens. Operators can use AI's predictive analytics capabilities to anticipate changes in supply and demand more accurately, leading them to adjust their pricing strategies accordingly. In addition, by predicting when renewable sources are most likely available or economical, operators may be able to offer cheaper rates during these periods, making energy more accessible to consumers of all income tiers.
"An essential benefit of AI-driven energy systems, given the current state of climate change, is their ability to help rescue carbon emissions," Hynes said, noting that the race to Net Zero by 2050 is a key driver and value at Hub Controls. "By using predictive analytics to anticipate changes in supply and demand, local housing organizations can ensure that only enough electricity is generated to meet current needs—which reduces unnecessary production that leads to excess emissions."
Overall, it's clear that AI has the potential to revolutionize the way we produce affordable and clean energy. By utilizing predictive analytics and machine learning algorithms, public housing organizations can increase efficiency while optimizing their use of renewable sources such as solar or wind power. As a result, consumers can enjoy lower costs and greater access to sustainable sources of power than ever before, with AI paving the way for a new era of energy equity.
Edited by
Alex Passett
