Our Patent-Pending Approach Maximizes the Value of Energy Portfolios by +20%
We uniquely account for network effects, the hidden value created when assets are developed or procured in relation to each other, rather than in isolation.
In this study, we used a subset projects from publicly available data of DESRI portfolio. When planning a new project, we demonstrate how incorporating interactions with existing assets can be leveraged to optimize overall portfolio value.
Elahe Naghib, lead inventor of 5 energy patents, introduces the concept of network-aware portfolio planning and provides a high-level intro for this case-study.
Strategic siting of new projects can reduce congestion exposure by the equivalent of 20% of project revenue
By choosing locations that naturally offset price volatility in your existing portfolio, you can capture substantial value through avoided CRR premiums. This analysis shows that network-aware development can offer congestion hedging benefits equivalent to 20% of a project's annual revenue, without relying on purchasing financial instruments.
Imagine you’re deciding where to build a new natural gas power plant. You have several possible locations to choose from. But which location will work best considering your existing operational and planned projects?
We use real market data to compare sites and quantify their “Network Benefit” within the existing portfolio. In this study, we target how well a new plant at each location can offset price spikes and drops at the current assets locations caused by grid bottlenecks.
While the full network effect spans many dimensions including capacity value, energy arbitrage, reliability contributions, and operational synergies. This study focuses specifically on one critical aspect: congestion pricing risk.
In plain terms: Which site helps your current and future assets avoid revenue losses when congestion distorts local prices? The charts below provide a simple, data-driven answer for decision makers.
What this chart shows: Each line represents an existing or planned project in the portfolio. The X-axis shows the percentile ranking of possible locations for building a new complementary power plant. Higher percentiles correspond to better locations for reducing price volatility for that project.
Example: At the 95th percentile, selecting one of the very best locations for hedging Lamesa II’s congestion risk results in a value gain of approximately $17.1 per MWh.
Importantly, you don’t need to choose the absolute best location to benefit—any site chosen with network effects in mind can provide meaningful returns. This means you can factor in other priorities, like permitting or land availability, without sacrificing the core financial advantage of a well-placed plant.
Over time, this translates into substantial risk reduction and cost savings across your portfolio.
What this chart shows: How ERCOT CRR Auction results are used to estimate the dollar value of hedging against congestion pricing by strategically placing a new plant.
Key insight: This curve shows the hourly volatality of the LMP difference between the Lamesa II's location and EB_TOSBATT_2 another pricing node. Because of the high variations CRR bids between this pair is expected. Indeed, participants have placed bids for the time periods where the maximum variability is expected. Using the bids winning prices placed for the bid, we can estimate the value of hedging Lamesa II against congestion pricing by placing a plant at the EB_TOSBATT_2 node. Repeating the experiment for all the nodes in the auction, shows that EB_TOSBATT_2 node is within the top 5% of location for hedging Lamesa II against congestion pricing.