Grid congestion is limiting the value renewable energy assets can deliver. This is especially painful for projects that are technically complete, fully permitted and financed, yet unable to capture the revenue they planned for.
Many of the conversations around grid congestion come from the perspective of the utility or grid operator, focusing on how they can manage an ever-changing and complex system. This perspective is paramount, but there is another side of the coin. Distributed generation (DG) owners, like independent power producers (IPPs) and commercial and industrial (C&I) portfolio operators, can actively shape grid congestion outcomes. Congestion is not only a technical problem for the electricity grid, it is also a business problem.
Full value
Imagine a portfolio operator managing dozens of small renewable sites. Their projects are built, financed, and ready to connect to the grid. But, with abundant solar resources delivering during peak hours, grid congestion forces curtailment. Now, the asset owner’s expected revenue disappears, not because the assets fail, but because the grid cannot absorb or coordinate them efficiently.
Conversely, imagine a different DG operator, one who has assets that are not operating to their fullest capacity because of classic industry-plaguing problems. In fact, enSights has measured six C&I portfolios (hundreds of assets), and we know that many were only delivering two-thirds of their expected generation. That means the grid operator was planning and counting on that electricity, but it wasn’t being delivered. It is a lose-lose situation, and it is happening with increasing frequency.
Storage allows energy to be shifted, meaning excess renewable energy doesn’t need to be curtailed, but rather dispatched later when the grid is less congested. It is a powerful asset that can help IPPs reach their expected revenue. But storage alone does not solve the problem.
Every battery introduces decisions like when to charge, when to discharge, and which opportunity to prioritize. At scale, these decisions become constant and expensive when handled poorly. Storage is not a simple on-off asset. It is a multi-dimensional system shaped by prices, forecasts, grid constraints, asset health, degradation, and market rules. As storage becomes more distributed, grid congestion becomes a management problem.
Many legacy control systems were designed for site-by-site thinking and have limited visibility to other assets in a portfolio. Managing dozens of storage assets manually is an impossible task. Even managing 10 or 20 storage sites manually requires constant forecasting, scheduling, and reconfiguration. At dozens or hundreds of sites, it becomes operationally unsustainable.
Consider two portfolio operators. One relies on legacy systems and manual processes. Every day begins with hours of planning, spreadsheets, and site-by-site configuration. Congestion forces curtailment and revenue leaks quietly from assets that are technically “online” but economically underperforming.
The other operates with intelligent, portfolio-level coordination. Storage responds dynamically to congestion and energy shifts instead of curtailing. Assets participate in multiple programs without constant manual intervention. Both own similar hardware, but only one unlocks full value. What IPPs are missing is the ability to manage flexibility across entire portfolios, not individual assets. And when assets perform as expected, grid operators can plan with confidence.
Flexible management
The advantage is shifting from who installs the most assets to who operates with the most flexibility. It isn’t set-it-and-forget-it, it’s constant monitoring and adjustment. Doing that at scale is tough with manual labor alone.
Modern energy management platforms must evolve beyond basic control tools into AI-powered digital layers that can create dynamic storage and consumption strategies to mitigate grid congestion. These systems need to coordinate fleets of storage systems and provide unified orchestration across sites, enabling grid-level functions such as frequency regulation, voltage support and congestion relief, and automatically optimize participation in grid-service programs, including demand-response events, ancillary-service markets and capacity incentives.
AI-powered energy business management systems enable IPPs to manage distributed assets at scale, with the granularity to boost their bottom line. Instead of spending hours each day manually scheduling assets, IPPs can review, verify, and refine recommendations in minutes. The value of storage increasingly depends on the software that manages it.
AI optimization only works if the data is trustworthy. As the grid gets more complex, IPPs have to raise the bar on data acquisition and quality. And because this coordination happens digitally, cybersecurity can no longer be an afterthought. It must be built into a project from the beginning. Protecting operational data and control systems with modern security protocols is part of protecting uptime, revenue, and grid reliability.
Market maturity
Grid congestion persists because systems struggle to coordinate distributed assets with speed, confidence and financial precision. Success will depend less on how much capacity gets built and more on how intelligently it is operated. Operators with intelligent management will keep unlocking value, even under a constrained grid.
As the grid evolves, the success of AI-optimized solutions depends on high-quality data and the latest cybersecurity protocols that IPPs must secure to prevent disruption. Grid congestion doesn’t have to slow renewable energy growth if IPPs change how they manage their assets. AI-powered energy business management gives IPPs a way to act now, improving data quality, unlocking flexibility and allowing renewable assets to operate at their full economic value while the grid catches up. Alon Mashkovich
About the author
Alon Mashkovich, CEO and co-founder of enSights, is an entrepreneur with more than 15 years of experience in strategic business development, operations management, energy efficiency, and renewable energy. The former business and energy efficiency consultant saw the challenges that his clients faced with energy management and optimization, which led him to create the energy business management solution enSights with his co-founders.
The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine.
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