How AI and Digital Tools Are Powering the Renewable Energy Transition
- cnasir9
- May 21
- 3 min read
The Park, building cutting-edge digital infrastructure
The renewable energy sector is undergoing a seismic shift across AI and digital – this is game-changing.
Say goodbye to spreadsheets and gut instinct; today, developers and investors need real-time data, predictive analytics and AI-driven insights to build resilient portfolios.
At the forefront of this transformation is Low Carbon. A UK-based company dedicated to combating climate change by developing large-scale renewable energy projects. They specialise in building, owning and operating renewable energy infrastructure, striving to establish a net-zero energy company that safeguards the planet for generations to come
Whilst many other organisations are also doing vital work in this space, what’s interesting about Low Carbon is the digital development going on behind the scenes.
In an exclusive interview, Renewables Reporter, Lily Regardsoe, talked to Siobhan Temple, Chief Technology Officer at Low Carbon. They discussed how the company is building cutting-edge digital infrastructure, setting a new standard for the industry—and why it’s critical for the energy transition.
The Data Foundation: ‘The Park’
Let’s begin with Low Carbon’s secret weapon; a proprietary data platform, dubbed ‘the Park’.
It’s a hybrid data lakehouse that consolidates everything from financial metrics and energy generation to acoustic bee monitoring (yes, bees per megawatt is now a measurable KPI).
"We built ‘the Park’ to optimise workflows, improve accessibility and drive innovation. It’s not just about profitability; it’s about pulling ESG data, supply chain insights and even ecological impacts into one place to see the full picture."
The platform’s ‘Playground’ layer allows data scientists to mine patterns, uncovering opportunities that traditional methods would miss.
"Suddenly, asking how many bees a solar farm supports isn’t crazy—it’s actionable intelligence,"
AI Tools for Smarter Decisions
With this foundation, Low Carbon has developed AI-powered products to streamline its IPP transition:
AI Scout: An LLM-driven tool that scans documents (planning permits, grid queues) to identify high-potential sites and reduce risk.
Python-Based Valuation Models: Replacing clunky Excel sheets with modular "Lego-like" code for faster, auditable financial modelling.
Portfolio Optimiser: A quant-driven tool to balance asset mixes (solar, batteries) and forecast grid pricing impacts.
"Speed and agility are non-negotiable. When market changes hit, our tools adapt instantly. That’s the difference between leading and lagging."
Why Python? The Developer’s Edge
Siobhan highlights Python’s role in accelerating decision-making,
"Excel models were rigid—built individually for each asset. Python lets us swap components like Lego bricks. Need to adjust for battery storage? Change lines of code, not rebuild the entire model."
From an engineering perspective, Python’s flexibility is unmatched. Its open-source libraries (Pandas for data, NumPy for calculations) enable rapid prototyping, while version control ensures transparency, critical for investor audits.
"You can trace every change, see who made it, and roll back if needed. That’s impossible with spreadsheets.”
The Investor Shift: Data as a Deciding Factor
"Five years ago, they’d ask for static reports. Now, they want interactive dashboards showing live asset performance, ESG impact and even how policy shifts affect returns,"
Investors are increasingly demanding granular, real-time insights to de-risk portfolios and maximise value.
Low Carbon’s tools provide that edge. For example, their AI Scout uses natural language processing and AI to extract and summarise over 100,000 planning documents in seconds,
while the Portfolio Optimiser simulates market shocks (e.g., gas price spikes) to stress-test investments.
"Investors don’t just want data—they want foresight."
The Human Factor: A ‘Digital-First’ Culture
"Nobody tells them how to solve problems. We describe the challenge, and they innovate."
Low Carbon’s team—a blend of seasoned energy experts and a whole host of young data scientists—embodies this shift. Siobhan credits their success to a culture of experimentation.
Interns played a pivotal role, developing the AI Scout prototype in weeks.
"The best ideas often come from those unburdened by ‘how it’s always been done,’" she says.
Speed & Agility: The Industry Imperative
For Siobhan and her team, agility isn’t just about business—it’s existential.
“Renewables can’t wait for slow, linear processes. If the wind stops, batteries must react in milliseconds. AI lets us pivot at that speed."
She cites grid congestion as a critical example,
"With our tools, we can adjust dynamically. Without AI, you’re stuck in yesterday’s data."
Concluding Thoughts
Low Carbon’s blueprint offers a roadmap for the industry:
Integrate data across the value chain.
Empower teams to experiment with AI.
Build flexibility to adapt to market shifts.
Siobhan summarises,
"There’s a different way to do this. Digital-first isn’t optional—it’s how we’ll meet net zero."
For investors and developers, the message is clear: The future of renewable energy isn’t just about building assets—it’s about harnessing AI to build them smarter.
Our thanks to Siobhan Temple for her fascinating discussion. For more information https://www.lowcarbon.com/