Solar

Data risk: The overlooked problem curtailing solar plant performance

As the renewable market continues to expand, data quality issues will become more apparent, writes PVCase CEO David Trainavicius.
Data risk: The overlooked problem curtailing solar plant performance
(Photo by American Public Power Association on Unsplash )

Contributed by David Trainavicius, Founder and CEO of PVcase

The renewable energy market is booming – and rightfully so. But beneath the surface, there’s a silent technical problem that degrades the performance of projects. We call it “data risk,” the loss of data and data quality as project designing moves from one software platform to another.  

Most renewable developer executive teams have never heard of this problem, but they are beginning to feel its effects. Left unchanged, data risk could significantly curtail the success of the entire clean energy transition. 

I’ve been working in the renewable industry for more than a decade – including nearly a decade as a solar project engineer – and I’ve seen how easily data can get compromised. A typical renewable energy project involves a myriad of vendors, each performing a bespoke role. Those include market analysis, financing, site selection, design, yield estimation, construction monitoring, operation and maintenance, and asset management. 

Completing these steps can require 30 or more different companies, suppliers, and consultants, and all must be involved in the data foundation of a project. Each of these collects and provides data in a different way, using different software, units of measurement, and margins of error.

Here’s what that might look like in practice: Company A sends a spreadsheet of data to Companies B, C, and D to conduct their own analyses and complete their respective parts of the project. 

Each company then creates its own data analysis based on the spreadsheet. Company B rearranges the data to suit its needs. Company C sends its analysis back in a giant PDF. And Company D completes its work in a different unit of measurement. 

It’s then up to Company A to compile all the data – an incredibly time-consuming and labor-intensive process. Inevitably, pieces of data are lost, outdated, or altered – creating data risk. 

It’s like an old-fashioned game of “telephone” in which every repetition can change the meaning. But this happens repeatedly with thousands upon thousands of data points throughout the process. 

If just one data point is slightly off or defunct early in the development process, it can cause a cascade of errors. It doesn’t take much degradation or loss of data, particularly at the early design stages, to inadvertently build flaws into projects and how they’ll operate. 

That can cause a myriad of issues. For example, a developer might compile data for a solar project and determine that they can install a 100MW power plant. They secure funding based on that estimate. But then, when they get further along in the process, they discover they can only install 70MW. They then have to return to their investors and report that their calculations are 30 percent off, which may negate their initial business model. 

Additionally, right now, many renewable leaders are experiencing underperformance in their systems but can’t pinpoint the cause. Some are selling off assets due to that underperformance. 

The financial consequences are monumental. At an average solar project price of $1.5 million per MW and at least 300 GW of projects under development in EMEA and the Americas, according to BNEF, compounding data risk issues could jeopardize investments worth more than $450 billion. 

Data risk isn’t just harmful for project leaders in the short term. It also affects the entire renewable energy industry. When energy plants consistently underperform expectations, it’s difficult to get funding for future projects. It also reduces trust in the industry throughout the process: For project owners, power off-takers, host communities, and policymakers. 

Ultimately, that slows our progress in cutting carbon pollution – at a time when we need to be reducing emissions faster and at a bigger scale. 

Companies can’t simply hire more people to handle quality control. We’re already experiencing a dire shortage of skilled workers in the renewable energy market. It also wastes precious time and resources – and increases the chance of error – to use significant staff resources on such tasks. 

Technology will provide the needed support. While some software exists to compile data, it is nowhere near comprehensive and advanced enough to handle a renewable project from start to finish. That needs to change. We need a software solution that integrates all the steps of project development and design into a single platform. 

We haven’t seen the full repercussions of data risk quite yet. But as the renewable energy market continues to expand, these issues will become more and more apparent. 

On the flip side, if we can eliminate data risk, developers could complete projects faster, more accurately, and with fewer resources. And those projects could meet their promised performance goals. Ultimately, that would accelerate our transition to a net-zero economy. 

About the author

David Trainavicius is founder and CEO of PVcase, a leading SaaS firm with customers in 80 countries, whose software makes engineering and building renewable energy projects less labor-intensive, time-consuming, and complicated. He previously consulted for more than 100 companies and helped investors develop projects in Europe worth over €500M.

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