Running One Plant Is Hard. Running Ten Is a Different Game
Why portfolio thinking is becoming essential for multi-plant AD operators
Operating a single anaerobic digestion (AD) plant is already a complex job. Operators are constantly balancing feedstock variability, biological stability, energy efficiency, maintenance schedules and regulatory compliance. There are a lot of moving parts, and even small changes in one area can ripple through the entire system.
Now imagine managing not one plant, but ten.
At that point, the challenge shifts. It’s no longer just about plant operations. It becomes something much bigger: a portfolio management problem.
Across the biogas and biomethane/renewable natural gas (RNG) sector, this shift is already underway. More developers are expanding from single-site projects into multi-plant portfolios. Utilities are investing in several RNG facilities across regions. Agricultural cooperatives and waste management companies are building networks of digesters rather than standalone facilities.
And once you reach that scale, the questions start to change.
Instead of asking “How do we optimize this plant?” operators begin asking something else:
“How do we optimize the entire portfolio?”
The Hidden Complexity of Multi-Plant Operations
Running multiple biogas facilities is not simply a matter of repeating the same model in different locations. Each site develops its own operational personality over time.
Feedstock supply chains evolve differently. Local regulations vary. Equipment (like sensors) ages at different rates. Operators develop their own habits and practices. Even climate and seasonal patterns influence performance.
Over time, these small differences compound.
Multi-site operators often face challenges such as:
Uneven plant performance across the portfolio
Different feedstock availability and quality
Regional policy or regulatory differences
Inconsistent operational practices between facilities
Limited visibility into which plants are truly performing well and why
"Visibility" in this context can actually mean a few things in practice. The metrics that enable meaningful cross-plant comparison include specific methane yield (Nm3 CH4/kg VS), OLR, Levelized Cost of Energy ($/MWh or per Unit of Energy), and feedstock ration or recipe cost ($/tonne).
Without normalizing for digester size and feedstock type, a high-volume plant will always look like a top performer in the portfolio, even if it's running well below its potential.
And without a consistent way to compare assets, optimization then tends to happen in silos. Each plant team works hard to improve its own facility, but the broader picture remains unclear.
The result? Opportunities are missed not because operators lack expertise, but because the system lacks visibility.
The Limits of Site-by-Site Optimization
Traditionally, biogas plants have been managed individually. Each facility controls and monitors its own data, evaluates its own feedstocks and makes operational decisions based on local priorities.
That works well when you have a single plant. But once a company operates several sites, local optimization does not necessarily produce the best portfolio outcome.
Consider a few examples.
A feedstock that produces strong methane yields at one facility might actually deliver higher marginal value at another plant where the digester biology or upgrading system is better suited for it. For example, A substrate with a high C/N ratio that risks TAN inhibition in one digester may be exactly what a nitrogen-deficient digester at another site needs to stabilize its microbial community. This is the exact problem Anessa’s Feedstock Portfolio Optimizer solves, evaluating substrate interactions across all plants simultaneously, not just optimizing each site in isolation.
An equipment upgrade that seems beneficial for a single site may not be the best use of capital when evaluated across the entire portfolio.
A recurring operational issue may appear to be a site-specific problem when, in reality, it reflects a broader design or feedstock management issue affecting multiple facilities.
Without portfolio-level insights, these patterns remain difficult to detect.
Why Portfolio Intelligence Matters
Portfolio thinking introduces a different perspective. Instead of focusing only on the performance of individual plants, operators begin to look at how assets perform relative to one another.
This enables a few powerful capabilities.
Benchmarking performance across plants
Every plant is unique, but that doesn’t mean they can’t be compared. When performance metrics are normalized to account for feedstock types, digester size, and operating conditions, operators can begin to see which plants are truly outperforming others or highlight which plant is furthest from what its feedstock and design combination should theoretically produce.
More importantly, they can start asking why.
Does feedstock strategy drive differences? Operational practices? Equipment design? Environmental conditions?
That gap between actual and modelled methane yield is where the most recoverable value sits. Our simulation module benchmarks various operational paths for the plants to help operators choose the best strategies based on simulated outcomes.
These insights often reveal opportunities for improvement that would never appear at a single site.
Identifying systemic issues
When performance challenges appear across multiple facilities, they may signal broader operational patterns rather than isolated problems.
Portfolio visibility helps operators distinguish between site-specific issues and systemic inefficiencies. That distinction matters when deciding where to focus engineering resources, training, or operational improvements.
Smarter feedstock allocation
Feedstock is one of the most valuable and variable inputs in the biogas industry. Different substrates produce different methane yields, require different pre-processing steps, and influence digester stability in unique ways.
Portfolio intelligence allows operators to evaluate where each feedstock generates the highest marginal methane value. Instead of simply sending material to the nearest facility, companies can begin making decisions based on portfolio-level performance and revenue potential.
Prioritizing capital investments
Every multi-site operator faces the same question: where should the next dollar of capital be invested?
New gas upgrading equipment, improved pre-processing systems, additional digesters, or heat recovery upgrades can all improve plant performance, but resources are always limited.
Portfolio analytics allow operators to evaluate which investments generate the greatest return across the entire asset base, rather than relying solely on site-level preferences.
Centralized Intelligence, Local Expertise
One common concern with portfolio management is the fear that centralized decision-making might override the experience of local plant teams.
In reality, effective portfolio management does the opposite.
Centralized intelligence provides a broader view of performance trends, operational data and financial outcomes. Local operators continue to apply their expertise on the ground, but with better context and better tools.
In other words, portfolio thinking does not remove local autonomy. It simply ensures that decisions are aligned with overall portfolio performance.
The Role of Digital Tools
Managing this level of complexity manually is extremely difficult. Data often lives in different systems, formats and spreadsheets across multiple sites. Comparing performance between facilities becomes time-consuming and sometimes impossible.
This is where digital platforms are beginning to change how the industry operates.
Anessa’s suite of solutions, including AD•A, AD•M and AD•O, was developed specifically to address these challenges across the lifecycle of biogas and RNG projects.
Anessa AD•A helps developers and portfolio owners evaluate new projects, test feedstock scenarios and understand how new assets will be used and integrated into existing portfolios.
Anessa AD•M focuses on real-time plant monitoring, operational analytics and performance, helping teams identify inefficiencies and maintain stable operations.
Anessa AD•O enables operators to optimize operational strategies (like feedstock recipe generation) and understand performance under changing conditions.
Together, these tools create a consistent data framework across multiple facilities, allowing operators to compare assets, simulate improvements and make more informed decisions at the portfolio level.
Instead of treating each plant as an isolated system, operators can begin to view their infrastructure as an interconnected network of assets.
A New Way of Thinking About Biogas Infrastructure
The biogas industry is evolving. What began as a collection of independent projects is gradually transforming into a broader infrastructure network.
Utilities are developing regional RNG portfolios. Agricultural cooperatives are building clusters of digesters. Food and Waste management companies are integrating organics processing with electricity and alternative fuel production.
As this shift continues, the skills required to manage these systems will evolve as well.
Operating one plant will always require strong engineering and biological expertise.
But operating ten or twenty requires something more.
It requires portfolio thinking.
The operators who embrace this development will be better positioned to allocate resources efficiently, improve plant performance across assets and build resilient biogas infrastructure capable of scaling with the growing demand for renewable energy.
For investors and developers, this will bring bankability and exit value. A portfolio managed through standardized digital infrastructure with auditable performance records is more attractive to lenders and project finance teams, and a biogas asset with a documented Digital Twin history carries a higher resale and refinancing value because it de-risks future performance for buyers.
Because in today’s energy landscape, the question is no longer simply how to run a successful plant. It is how to run a successful portfolio of plants.
