AI-powered Microgrids: The Path to Electricity Resiliency and Sustainability

Key Takeaways

AI-driven microgrids improve energy resilience and sustainability but do not guarantee cost savings due to high deployment and operational costs.
Microgrids use off-peak electricity storage and renewable energy integration to reduce reliance on the main grid and provide backup power during outages.
AI-powered microgrids enhance efficiency by predicting energy demand, optimizing power flow, and autonomously restoring operations during disruptions.
While current microgrid costs outweigh financial savings, future advancements in AI, hardware efficiency, and rising electricity prices may shift the economic equation.

Buildings owners in locations that can charge more during peak electricity hours, like California, Illinois, New York, and Texas, pay 50% to 300% higher kWh compared to off-peak hours. Charging significantly more for peak-hour electricity use has led many building owners and operators to investigate ways to reduce energy during peak-hour times.

One method gaining interest for larger smart buildings and campuses is the deployment of AI-driven microgrids. However, when you get into the details, microgrids are no guarantee of cost savings. Instead, they should be viewed as a strategic investment that bolsters resiliency and sustainability.

This article will define what smart grids are, explore the recent advancements with AI, and offer several use case examples.

What Are Microgrids?

Microgrids are energy systems that are designed for use in large buildings or across a campus or municipality. These systems operate independently from the utility company’s main grid and can be integrated with renewable energy sources to supplement power generation.

According to the National Renewable Energy Laboratory, advanced microgrids “enable local power generation assets—including traditional generators, renewables, and storage—to keep the local grid running even when the larger grid experiences interruptions or, for remote areas, where there is no connection to the larger grid. In addition, advanced microgrids allow local assets to work together to save costs, extend duration of energy supplies, and produce revenue via market participation.”

Additionally, microgrids can collect electricity during off-peak hours (known as peak shaving) and store the electricity locally where it can be used during off-peak hours or during times when brownouts or blackouts occur.

Microgrid Technology’s Fusion with Advanced AI

As AI and machine learning capabilities continue to explode, microgrids that leverage AI technology are being described as a “decision-making engine” that controls the majority of the system’s activities and operations in real time. Microgrids now have improved predictive capabilities that can more accurately:

predict upcoming usage demand
optimize power flows within smart buildings or campuses
prioritize power delivery to mission-critical locations
adapt to unexpected power use conditions in real-time

An AI-powered microgrid management system continuously analyzes real-time data to predict energy demands, identify system vulnerabilities, and autonomously restore operations during outages. If gaps exist in the vast datasets it processes, the AI can extrapolate from available information to fill in the blanks. These capabilities make AI-driven microgrids more responsive, optimizing when to generate, store, or sell electricity for maximum efficiency—a huge benefit to smart building owners.

Microgrids Lack Clear Cost Savings so Far

Despite the potential for cost savings, microgrids are still quite expensive to purchase, deploy, and operate. Because of this, the total cost of ownership (TCO) often wipes out the savings gained by lowering off-peak electricity draw from main power grids. Here are two examples that highlight this point.

University of California, San Diego (UCSD): UCSD has deployed and upgraded their campus migrogrid system with AI across their 1,200-acre campus. The TCO for this deployment and ongoing operations with a decades-long lifecycle is estimated to cost $50 to $100 billion. With this system, the university is saving $850,000 a year by taking advantage of peak shaving and the use of alternative renewable energy. Given a large number of state-funded grants, UCSD is expected to have a financial win, saving tens of millions over a 20-year period. However, without the grants, the microgrid would be hard to justify based on potential cost savings alone.

Microsoft Redmond Campus: Microsoft’s technology campus, which spans 500 acres and over 125 buildings, was recently outfitted with a microgrid that was deployed in 2021-23. Over the course of 20 years, the microgrid TCO is estimated to be $50-$70 million, with off-peak and renewal energy use savings in the ballpark of $20-$50 million.

Sparking a Resiliency and Sustainability Conversation

Despite the low likelihood of significant cost savings due to off-peak usage and supplemented renewable energy usage, microgrids offer significantly improved resiliency and sustainability, which can be a strategic investment for smart building owners. Resilience is especially important for organizations that operate facilities where extreme weather or brownouts/blackouts commonly occur that knock out access to the main grid. Microgrids can continue delivering stored power to the entire location or specify mission-critical areas within a building or campus.

Likewise, if sustainability is a priority for organizations due to government regulation or internal policy, microgrids help align with net-zero goals, minimizing environmental impact while simultaneously providing the necessary power to operate.

Microgrid Benefit Trifecta on the Horizon

Today, microgrids deliver business continuity and significantly aid with sustainability goals. However, in the future, expect microgrid hardware, deployment, and operational costs to drop, adding significant cost savings to the mix—especially if electricity costs continue to rise and AI continues to advance.

Potential Next Steps for Building Professionals

Evaluate Peak-Hour Energy Costs – Assess your facility’s energy usage patterns to determine potential cost savings from peak shaving and microgrid integration.
Assess Resiliency Needs – Identify whether your building or campus would benefit from enhanced energy reliability due to frequent blackouts, extreme weather, or mission-critical operations.
Explore AI-Driven Microgrid Solutions – Research available AI-powered microgrid technologies to understand their predictive capabilities and operational benefits.
Conduct a Feasibility Study – Analyze total cost of ownership (TCO) versus potential long-term savings and sustainability benefits, factoring in available government incentives and grants.
Plan for Future Cost Improvements – Stay informed on industry advancements in microgrid affordability, AI efficiency, and evolving electricity pricing trends to determine the right timing for investment.