The passage of historic new federal legislation last week gives some of the most concentrated support ever to the renewable energy sector. It will surely spur further growth in an industry already challenged with adjusting to constant changes in supply and demand in energy markets. With the number of renewable projects using wind turbines, solar panels, and hydropower slated to grow quickly in the coming years, operators can benefit greatly by using artificial intelligence (AI) solutions to maximize uptime and optimize production and delivery of energy.
President Biden’s recent signing of the expansive Inflation Reduction Act authorized the spending of billions of dollars for clean energy tax credits and a potential sea change in how residential property owners will get their power in the future. Among the many provisions of the bill, it provides:
- $260B in clean-energy tax credits that will require more renewable energy production
- $80B in new rebates for electric vehicles, green energy at home, and more
- $27B ‘green bank’ to attract private investors for renewable energy and climate change purposes
This spending package represents the country’s most significant investment in renewables and initiatives to combat climate change to date, by a wide margin. And environmental advocates are no doubt watching to see how quickly one of the world’s primary generators of carbon and greenhouse gases can shift away from fossil fuels and other business-as-usual energy sources such as nuclear, which contributes to climate change through the need to mine and process natural resources.
The case for going all in on renewables is made strongly in a recent paper by the Royal Society of Chemistry, with its participants noting the urgent need to reduce carbon dioxide emissions and the positive economic effects of a switch to creating all energy from wind, water, and solar across the globe. The paper notes that traditional energy production processes lead to energy insecurity in many parts of the world through a combination of decreasing availability of fossil fuels and uranium, reliance on expensive centralized power plants and refineries, disruptions in supply caused by war and other issues, and long-standing environmental damage caused by mining and drilling.
Moving entirely to renewable energy by 2050, according to the paper’s research, would reduce overall end-use energy by 56% due to a combination of efficiencies gained over combustion and eliminating energy needed for mining/drilling, refining, and transport. Energy costs for the private sector would also be slashed by 62.7%, for a savings of more than $11T globally per year. Also, the transition to renewables across the globe would produce a net increase of 28.4M new, full-time jobs.
As pressure and expectations grow, SparkCognition Renewable Suite is ready to help
These projections come as oil and natural gas producers face growing pressure from global investors to move toward low-carbon energy production. Some conglomerates call for major companies in all sectors to take “necessary actions on climate issues.” While not explicitly stating that corporations that prioritize net-zero or low-carbon business practices will receive preferential treatment for investments and loans, the message is clear that a move toward renewable energy, among other steps, is preferred.
With so much attention on climate change and the transition to renewable energy, there are many entry points for AI technology to make an impact. SparkCognition Renewable Suite has demonstrated benefits for wind and solar energy operators, including those moving to integrate battery storage to add flexibility over production cycles and reduce risk from curtailments and other market forces.
By providing analysis of fleet-level sensor data to manage asset health and predict failures far in advance, renewable assets will stay productive longer with lower O&M costs. And by forecasting productivity against demand models, Renewable Suite improves the profitability of projects as contract pricing continues to decrease due to the growth of producers in the market.
Beyond the direct improvements to asset health and economic performance in the renewables market, public and private-sector leaders across the globe see huge potential for AI in achieving drastic reductions in greenhouse gas emissions. A new report from AI For The Planet Alliance found that 87% of the more than 1,000 survey respondents see AI as a valuable asset in the fight against climate change.
There is less consensus, however, about exactly how AI can best be used in climate-change-related efforts, but improving processes around the manufacturing of industrial goods and public sector uses such as transportation were two of the leading opportunities for improvement. Others included energy, general automotive, and health care.
There may be a need for further public sector investment or emphasis for AI to realize its full potential in stemming the impact of climate change. Among the respondents, 78% cite insufficient AI expertise as an obstacle, 77% cite limited availability of AI solutions as a roadblock, and 67% point to a lack of confidence in AI-related data and analysis.
Those expectations and the proven abilities of AI technology to both find efficiencies and bring greater operational stability for major asset fleets have created a moment for machine learning to help improve the way people live and work around the world. From established solutions like SparkCognition Renewable Suite to the latest advancements in climate change best practices, it’s clear that the reduction of greenhouse gas emissions globally will happen with a significant helping hand from AI technology.
Click here to learn more about how Renewable Suite can improve performance for wind, solar and battery storage needs.