Dr. Matthew Green is Senior Vice President at TRC. He has more than two decades of experience driving transformative energy initiatives.
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In my prior article for Forbes, I discussed how the U.S. power grid is being strained to its limits because of a perfect storm of pressures on the aging electrical infrastructure. The electric power industry is approximately 5% of the U.S. GDP, but it is the first 5% because all other industries rely on it. The core of the U.S. power grid was largely built when most people still watched TV in black and white, and a large portion of this infrastructure is either approaching the end of its usable life or is already well past its intended lifecycle. That aging infrastructure is also being tested with challenges it was never designed to face, including skyrocketing demand, accelerating security threats, extreme weather events and increasing systemic vulnerabilities.
Our power grid has never been this vulnerable, and that poses a growing threat to the entire U.S. economy. Those risks make grid modernization an urgent issue not only for the utility industry and government officials, but for every leader in the business community.
We need to modernize the grid in ways that truly meet the needs of our economy. Incremental change is not enough. Bolder steps are required to truly address the scale and urgency of this issue, and that includes a fundamentally new approach to the way the utility industry conducts planning for the grid.
For decades, the utility industry has used deterministic forecasting as its strategy for grid planning.
Deterministic planning worked well when demand growth was slow, steady and highly predictable. That approach works as long as the variables are small, the unknowns are few and reality does not shift away from the rigid underlying assumptions in your plan. But what happens when change accelerates, the variables become volatile and every week brings more unknowns?
Those conditions are fundamentally at odds with deterministic planning. And the power grid is now facing them at an unprecedented scale.
Those traditional, deterministic planning processes require rigid assumptions with few variables and a low rate of change. That approach quickly falls apart when reality shifts away from those rigid assumptions, which is why traditional utility planning processes are struggling now as they face rapid change on so many fronts. Those changes include skyrocketing load projections, unpredictable demand patterns, climate change-driven natural disasters, the rising use of distributed energy resources, changing load characteristics, growing grid complexity and the impact of new technologies.
We need a new approach to managing this critical infrastructure for our economy, but what is the alternative to deterministic planning? The answer is probabilistic, systems-based planning, which is built for adaptability for changing variables and unexpected challenges. This planning model bases decisions on probabilities for a range of variables, rates of change and potential outcomes—all across a wide range of scenarios. And probabilistic planning can also pivot quickly as circumstances change, allowing utilities to be far more nimble.
This shift from deterministic to probabilistic planning is a shift in mindset first and foremost. However, there are certain processes and technologies that provide a foundation for effective probabilistic planning. Utilities should invest in the digital infrastructure needed to support integrated planning, including system modeling, data management and scenario/version—all of which turn the data utilities are already gathering into an engine for smarter planning. Utilities should also conduct an integrated system inventory across transmission, distribution and DER assets to establish a unified baseline for planning—a process that delivers a range of benefits beyond creating a baseline for probabilistic planning.
Utilities should also establish metrics to measure planning flexibility, predictive accuracy and improvements in resiliency—as well as cross-functional collaboration and reporting to compare scenario outcomes with actual performance data and refine models iteratively. In this way, probabilistic planning is able to adapt rapidly to emerging circumstances and continue to drive smart decisions.
What does this approach look like in practice? Utilities that opt for probabilistic planning conduct data-driven scenario analyses with inputs that include statistical distributions of potential load demand, weather conditions and other variables. For example, probabilistic planning can forecast how load demand will evolve and where congestion will emerge. It can also forecast which generation and distribution assets will be under significant pressure in the future and which are likely to be underutilized. This provides critical decision-making insights about where to make major upgrades vs. where to defer or right-size planned upgrades in areas where load growth will not be as strong.
Another example of probabilistic planning is peak demand planning. Too often, deterministic planning has led to misallocation of resources that impaired utilities’ efforts to pursue equally important goals like overall grid modernization, resilience and affordability. Instead of planning for a single forecasted peak in a rigid way that neglect other important priorities, utilities who use probabilistic planning can evaluate risk across a distribution of outcomes and align investments with actual system behavior.
Probabilistic planning is a gamechanger for navigating so many of the challenges that utilities face, including skyrocketing demand from data centers, rapidly evolving load shapes, the rise of renewables and EVs, stronger storms with longer storm seasons and more. Adopting this smarter, more flexible approach to planning is a critical step toward addressing these challenges while building the grid we need for the future of the economy.
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