In the solar industry, companies regularly finance 25-year revenue streams based on energy assumptions made before detailed layouts even exist, and no one blinks an eye. It’s a documented fact that solar assets in the US underperform, on average, by 8.6%, yet the industry continues to make critical financing decisions with incomplete information. While equipment optimisation can help raise performance, approaches such as reducing data loss in early development stages and adding missing business context should not be ignored. Especially due to repeated software transitions, data loss and missing business context can create cascading inaccuracies that compromise project bankability.
It all starts with how the business context is set – i.e. what objectives, assumptions and constraints are defined to guide a modelling task. Sadly, it’s common for teams that are responsible for delivering an energy model not to be fully informed on the business context, leading to less granular, less bankable designs.
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Commonly omitted business contexts include:
- Interconnection constraints: point-of-interconnection (POI) limits, curtailment assumptions, grid availability timelines
- Commercial targets: lifetime cost of energy thresholds, power purchase agreement structure, merchant vs. contracted strategy
- Construction reality: grading limits, pile design assumptions, access & logistics, EPC preferences
Another pitfall to watch out for is incompatibility during times of transition. Even if you’ve provided perfect inputs, incompatibility between software programs can create a “lost in translation” situation.
These transitions can occur during handoffs between internal and external stakeholders, such as EPCs, migration or translation between different software applications and design-to-energy-modelling software transitions. Why does this occur? The quick answer is that most energy modelling software simply cannot accept realistic design detail. Add to this that many development teams don’t have enough time or resources to recreate high-fidelity designs and an unawareness of the benefits of accurate data.
What usually gets lost in translation:
- Detailed inverter load ratio distributions
- 3D tracker placement and slope information
- Site-specific terrain and grading context
- Buildable design components (roads, electrical groups, cost data)
The consequences of simplification are not small, especially when considering that the current workarounds require manual data entry. See the following two cases how a more aligned and detailed transition unlocked benefits to finances and performance.
Rather than accept the status quo as “inevitable”, development teams are better off searching for solutions so that their early-stage energy modelling can be truly bankable.
Bankable design brings bankable energy closer
With industry headwinds as strong as they are, “bankability” is now a ubiquitous topic across solar industry conversations. Yet, “bankable design” remains an ill-defined concept. Working with dozens of engineering, site optimisation and project development teams, we have identified key requirements of bankable design:
- Site-specific: accounts for terrain, constraints, environmental factors
- Buildable: includes realistic components such as roads, electrical groups, equipment
- Economically grounded: detailed cost estimates for all components
A key benefit of bankable design, which is unlocked once data drops are eliminated, is that it can bring more design reality sooner. When using the correct automation and optimisation tools, teams can increase detail without increasing time or cost by creating faster feedback loops and unearthing realistic constraints earlier in the process.
Modern software is becoming increasingly interoperable, but users still need to select wisely. First, it’s wise to use building information modelling (BIM) software specifically designed for solar PV. This helps ensure design software outputs are compatible with energy modelling inputs. Looking for software pairs capable of bidirectional data exchange will also help maintain design bankability. Investment into licensing and training on a software platform can lock your team into a platform for years, so be sure to include a software vendor’s future upgrade plans in your evaluation criteria. They should be nimble enough to integrate new partnerships and functions as the industry demands, not just maintain their current offering.
Engineering workflows in solar are steadily evolving as time pressures shift away from tedious manual data entry and file exports toward more connected, intelligent systems. In the near term, improvements to formats such as PVC 2.0 are helping streamline data exchange between tools, reducing friction and minimising the risk of errors during handoffs.
Over the long term, the industry is moving toward fully bidirectional software integrations in which a change in design automatically propagates to energy models in real time. This kind of seamless connectivity has the potential to fundamentally reshape how teams collaborate and maintain accuracy across the project lifecycle.
Our challenge today is ensuring that data loss and gaps in business context don’t continue to create blind spots. These disconnects can lead to inaccurate energy models and, ultimately, underperforming projects. Addressing this requires a more disciplined approach from the outset: adopting bankable design practices early, leveraging integrated software tools, and ensuring that critical information is preserved at every stage of the process. The potential impact is significant: more accurate energy models that translate into better-informed financing decisions, reduced risk for lenders and more reliable solar projects throughout their lifespans.
Maksim Markevich is chief technology officer at PVFARM
