Co-founder and CEO of Bidgely , which develops energy analytics for utilities based on data and artificial intelligence .
When we think about how to reduce the high carbon emissions of the energy industry, large renewable energy projects come to mind. The downside is that adding wind and sunlight requires a lot of investment and time.
The IEA reports that by 2022, renewable energy will power 22% of US electricity generation, with modest growth of 24% expected through 2023. Climate change requires urgent action and society needs solutions that can be implemented quickly and at scale.
As utilities bring more clean energy to the grid to meet zero targets, the current grid infrastructure is not designed for it. Aging, finite power lines can't handle things like rooftop solar panels and distributed power supplies that pull power and feed it into the grid. However, without this capability, utilities cannot deliver enough energy to meet the growing demand for green power, which will fuel grid expansion and further electrification.
In anticipation of renewable energy development, do we have solutions to reduce the increase in emissions?
With advances in participatory artificial intelligence, there are new opportunities to create green, sustainable, and equitable networks that enable society to achieve climate change goals.
Immediate action
Building large renewable power plants can take years and cost millions. For example, onshore wind projects can last four to eight years, while offshore projects can last more than ten years. The average cost of installing a 2MW wind turbine is $3-4 million. However, energy efficiency efforts can be scaled up in four to six months at an average project management cost of $28 per megawatt.
While not everyone can install a solar or wind turbine, an average 2.75 megawatt wind turbine can only power 940 homes a month, but anyone can generate electricity because it can help meet zero targets. increase efficiency.
The impressive emissions reductions achieved with previous AI-driven efficiency programs are possible with modern infrastructure and are equivalent to the impact of thousands of solar panels or hundreds of wind turbines and years of development.
Engaging consumers in AI-powered energy efficiency solutions has an immediate impact through lower commission rates and creates a profitable bridge to start working now with long-term renewable energy investment planning.
Medium and long-term action
The number of wind and solar projects is slowing grid aging and preventing residential and commercial customers from connecting to new power sources. By the end of 2021, more than 8,100 energy projects, mostly wind, solar and battery projects, were pending approval to connect to the grid , compared to 5,600 that stalled the system, according to the New York Times .
The New York Times also reported that PJM, the largest US regional carrier, received so many interconnection requests that it had to block new requests until 2026 to work on a package of proposals.
By then, major clean energy projects should begin, including the country's largest $9.8 billion offshore wind farm. Once built in Virginia Beach, the project could save government customers up to $6 billion in its first 10 years of operation.
Focusing on efficiency now will help avoid overloading renewable energy production and will allow large projects like this to take giant strides toward a greener grid when they finally come online.
The role of AI expansion in energy efficiency
While improving energy efficiency is not a new idea, artificial intelligence enables real-time data analysis and insights into energy use, which can contribute to efforts to reduce carbon emissions in a number of ways.
• Education and Influence. Utility companies can use artificial intelligence to better communicate and serve customers. With AI-powered personalized intelligence behind the meter, consumers can better understand the impact of their behavior and make changes, e.g. B. Choosing cleaner, cheaper electricity to charge EVs at the right time.
• Identification of energy losses. AI can identify energy consumption data from various sources such as smart meters or landfills. For example, AI algorithms can identify patterns in energy use in homes and businesses and recommend ways to reduce energy use and save money by optimizing heating, cooling, cooling, lighting, and other devices.
• Energy demand forecast. AI can analyze historical energy usage patterns and other data to predict future energy needs. This information helps utilities plan how to optimize their power generation and distribution systems to avoid disruptions and ensure power is available when and where it's needed.
• Smart Grid Management. AI can help utilities coordinate a bi-directional power grid, improve processes, and reduce losses through automated control and communication functions. A better understanding of what's going on in the network and a better ability to manage it in real-time can lead to higher levels of reliability, security, and efficiency.
• Emissions monitoring. Measuring greenhouse gas emissions using artificial intelligence technologies enables utilities, municipalities, businesses and other organizations to track and hold stakeholders accountable for their sustainability commitments.
While AI-based solutions can offer many benefits in the energy sector, challenges remain with AI in general, particularly when it comes to cybersecurity and ethics. The aging energy infrastructure presents unique challenges for collecting accurate data. Fortunately, with smart investments like smart meters, the industry is moving towards the benefits of AI.
Shaping the future of clean energy together
Similar to the telecommunications and Internet revolutions, technology is moving from a centralized network controlled by the manufacturer to an interactive and environmentally friendly model.
Artificial intelligence applied to energy saving measures ensures that people are increasingly turning to ecological values and open to learning how they can help reduce emissions by saving money and collecting energy. AI plays a key role in helping the public and utilities better understand these strategic improvements.
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