Buy vs Build: Weighing the Options for Renewable Energy Digital Infrastructure
What is a Digital Control Platform?
A Digital Control Platform is the foundational data infrastructure that connects, collects, normalises, and manages operational data from renewable energy assets. It serves as the central nervous system for modern energy operations, ingesting data from inverters, turbines, battery energy storage systems (BESS), meters, weather stations, and dozens of other data sources across distributed solar, wind, and storage facilities.
A Digital Control Platform (DCP) eliminates siloed information across diverse equipment and sites, enabling consistent analytics, faster decision-making, and accurate performance benchmarking. This data standardization reduces integration costs and unlocks actionable insights that would be impossible with fragmented, vendor-specific systems.
The challenge? Every renewable energy IT leader faces the same dilemma: should you build this critical infrastructure yourself, or purchase it from a vendor?
PART 1:
The Build Trap – Why Smart IT Teams Get Stuck Reinventing the Wheel
The IT Team’s Dilemma
When faced with implementing a DCP for managing renewable energy assets, technical teams consistently find themselves pulled toward building custom solutions. This pattern repeats itself across organisations, driven by a constellation of deeply held beliefs that seem rational on the surface but often lead to costly delays and long-term technical debt.
The Builder’s Mindset reflects a deeply ingrained engineering belief: if I can build it, I should. This isn’t arrogance—it’s what draws talented people to engineering. Engineers are instinctively problem solvers who see every technical challenge as an opportunity and call to action. When you’ve developed the skills to architect systems and write elegant code, it’s genuinely satisfying to apply those capabilities to build something from scratch.
The Uniqueness Assumption compounds this tendency. Technical teams genuinely believe they understand their requirements better than any vendor ever could. “Why would we pay someone else to deliver what we can build ourselves?” More critically, there’s a conviction that the unique challenges of their specific operations—their portfolio mix, their operational philosophy, their competitive strategy—are fundamentally different from what a software vendor can truly understand. Those vendors don’t live in our world, the thinking goes. They build generic solutions for a broad market, but we face specific problems that require intimate domain knowledge.
But here’s the reality: most technical challenges are common across similar IPPs and O&Ms. Internal teams inevitably invest significant resources solving problems that every renewable energy operator faces, building capabilities that don’t actually differentiate their business.
The Control and Cost Appeal completes the picture. Building in-house promises complete control over features, security, integrations, and future development. There’s no waiting for a vendor to implement features, no negotiating with account managers, and no worrying about vendor roadmaps diverging from your needs. Add the cost assumption—”building will be cheaper in the long run because we won’t pay recurring vendor fees”—and the case seems ironclad. The math appears straightforward: build once, use forever.
The Reinvention Reality
The reality of building a comprehensive data infrastructure platform for renewable energy operations tells a very different story. What starts as a focused project to solve specific data consolidation challenges quickly reveals layers of complexity that few organisations anticipate.
Data Collection and Normalisation Challenges hit first. Teams dramatically underestimate the engineering effort required for reliable data collection across diverse equipment manufacturers, protocols, and plant configurations. You’re building connectors for dozens of equipment types—handling Modbus, OPC, DNP3, and proprietary protocols, normalising data formats across different manufacturers, managing communication failures, dealing with firmware updates that break integrations. When equipment firmware updates break your integration, you’re on the hook to fix it. When new equipment arrives on-site, you need to extend your platform to support it.
The normalisation challenge isn’t a project, it’s a perpetual process. Plants go through repowering with new equipment. Assets are bought and sold, bringing different configurations into your portfolio. Naming conventions and units of measure vary widely from vendor to vendor and even model to model. The challenge is particularly acute in the PV segment, where no formal standards are widely accepted. Multiply this across tens of thousands of data points, and you’re building a massive translation layer requiring constant attention. These are problems every renewable energy operator faces, yet internal teams find themselves attempting to solve them from scratch—a never-ending maintenance burden that diverts resources from higher-value work.
The Distributed Management Problem emerges when organisations purchase inexpensive plant-based data collectors or protocol converters as a middle ground. These low-cost devices create a new problem: dozens or hundreds of distributed devices that lack remote management capabilities. Without centralised orchestration, proper access controls, comprehensive backup systems, and robust disaster recovery capabilities, you’ve traded one problem for dozens of others.
Long term operating costs are often overlooked when making buy vs build decisions. What seems cost-effective per-site becomes extremely expensive when managing software updates, security patches, and configuration changes across hundreds of remote sites. Each site becomes a unique implementation with subtle configuration differences. When an edge device fails at 3 AM, who responds? When a security vulnerability is discovered, who patches hundreds of remote installations? Your IT team spends more time keeping the system running than extracting value from the data it collects. These operational realities transform what seemed like a one-time development project into a permanent operational burden.
The build trap isn’t about whether your team is capable—they likely are. It’s about whether building and maintaining a comprehensive data infrastructure platform is the highest priority and best use of your organisation’s limited technical resources. When you’re in the renewable energy business, every hour your best engineers spend maintaining data collection is an hour they’re not spending optimising energy production, improving forecasting accuracy or identifying the root causes of underperformance.
PART 2:
What IT Teams Should and Shouldn’t Build
A globally adopted commercial solution is the more cost-effective means for addressing the core data requirements all renewable energy companies have in common. The leading solution in the space has proven scalability across massive portfolios while minimizing maintenance and operating costs. Critically, a commercial Digital Control Platform can be deployed in days and connect dozens of plants and tens of thousands of pieces of equipment in a matter of weeks–dramatically speeding the path to digital transformation compared to months or years of custom development.
Before discussing where to invest your limited engineering resources, it’s worth being explicit about the foundational requirements common to all renewable energy operators—requirements best addressed by a proven commercial solution rather than custom development:
Plug-and-play data collection infrastructure is the foundation—the ability to easily integrate any renewable energy data source and reliably consolidate data in the cloud. The experience should be as simple as a mobile phone app store: pre-built plugins downloadable from a central hub in seconds that start collecting and normalising data immediately. One compelling reason to rely on a commercial solution is access to a vast library of such plugins, kept up to date as firmware evolves and new equipment models emerge.
Security and regulatory compliance are mission critical, not merely table stakes. Requirements are ever evolving, and most IT teams don’t have the requisite domain expertise to keep up. Cybersecurity controls and immutable audit trails to support compliance with critical infrastructure regulations should be built into the architecture.
Equally critical is centralised management of remote data collection technology—centralised monitoring, patching and updates, backup and recovery, and remote deployment of new plugins when firmware is updated or equipment refreshed. Without these capabilities, managing security across hundreds of distributed sites becomes an operational nightmare.
Cloud operations infrastructure handles the undifferentiated heavy lifting—storage systems for time-series data, backup processes, disaster recovery capabilities, and scaling infrastructure that grows with your portfolio. Critically, it should enable secure data sharing with partners, vendors, and third-party applications without compromising control or creating cyber risks.
Before developing a digital control platform in-house, executive decision makers should ask themselves: what are the true costs—including salaries and benefits—of reinventing the wheel? Consider not just the initial development investment, but the ongoing cost of maintaining a home-grown solution as technologies and regulations evolve. Finally, they should factor in the flight risk of internal experts: when they leave, they take irreplaceable institutional knowledge with them. Who maintains the home-grown system then?
The question isn’t whether you can build it. The question is whether you should, and what you’re giving up by making that choice.
Where to Invest in Building
Differentiated Applications are where your team should invest their time and expertise. Your proprietary forecasting models, unique optimisation algorithms, custom analytics that answer your investor’s specific questions, and specialised integrations with your internal systems represent genuine competitive advantages. These are worth building because they make your organisation distinctly better at what you do.
Consider what truly differentiates leading renewable energy operators: the ability to predict equipment failures before they impact production, optimise dispatch decisions in real-time based on market conditions and storage capacity, or provide investors with insights that go beyond standard performance metrics. While these capabilities rely upon quality, accessible data, the real return on investment comes from focusing engineering resources on extracting insights—not on building and maintaining the data infrastructure itself.
When your engineering team isn’t consumed by maintaining data pipelines and troubleshooting connectivity issues, they can focus on building machine learning models that identify degradation patterns across your fleet, developing algorithms that optimise maintenance scheduling based on weather forecasts and crew availability, or creating dashboards that help asset managers make faster, better-informed decisions.
The goal is to spend your engineering resources here, where the return on investment is highest. Every hour your best engineers spend on undifferentiated infrastructure is an hour they’re not spending on capabilities that create measurable competitive advantage.
PART 3:
The Hybrid Approach
The renewable energy industry will not benefit from more organisations investing in building data collection infrastructure from scratch, or from more operators being locked into inflexible vendor platforms that exercise lock-in through data control.
What’s needed is a fundamentally different approach—one built on a best-in-class unified data foundation. A Digital Control Platform can serve as the OT data lake that powers your custom analytics and reporting. It can also connect you to a thriving ecosystem of pre-integrated digital solutions, each designed to extract actionable insights from your operational data through the platform’s API.
The beauty of the hybrid approach is that you don’t have to choose just one path. Organisations can pursue both buy and build strategies simultaneously—building proprietary applications while leveraging third-party solutions—to assemble the optimal digital ecosystem for their unique operational needs.
Building effective data infrastructure for renewable energy operations starts with accepting a fundamental truth: some problems are worth solving once for the entire industry, while others are genuine sources of competitive advantage. The key is correctly identifying which is which.
The Extensible Foundation
A true digital control platform delivers value through its architecture. All PV plants and wind farms are assembled from common infrastructure elements—inverters, turbines, weather stations, and the like. The platform should come with a vast library of pre-built plugins for collecting data from all common equipment and maintain those plugins over time as firmware and protocols evolve. The plugins normalise data at collection, then reliably and securely centralise all OT data in a cloud datastore.
The key is what happens next: a high-performance RESTful API and real-time streaming interface make your data easily accessible whilst eliminating the cyber risks of allowing third parties to connect directly to local plant SCADA systems. This architecture gives you complete control over who accesses your data and how it’s shared, enabling you to build your differentiated applications on a solid, secure foundation.
In practice, this means starting with a robust platform that handles data collection, protocol handling, normalisation, edge management, and secure transport. These are solved problems that don’t need your custom attention. Look for platforms that handle the maintenance burden of supporting hundreds of equipment types and protocols, but don’t lock you into their analytics or visualisation tools.
Build your differentiated logic on top: your custom forecasting models, specialised analytics, unique optimisation algorithms, and proprietary workflows. This is where your engineering talent should focus because this is where you create value that competitors can’t easily replicate.
Maintain a clean integration layer that keeps these components loosely coupled via APIs. If you need to change your analytics approach, you shouldn’t have to rebuild your data collection infrastructure.
The Path Forward
The choice isn’t really between building and buying—it’s about building the right things. Let a proven Digital Control Platform handle data collection, normalisation, security, and cloud infrastructure. Direct your engineering talent toward the proprietary forecasting models, optimisation algorithms, and custom analytics that create genuine competitive advantage.
When evaluating your strategy, ask a simple question: are your engineers solving problems unique to your business, or reinventing solutions that every operator needs? The complexities of maintaining data infrastructure at scale—across hundreds of sites, dozens of equipment types, and ever-evolving security requirements—consume resources that should be focused on capabilities that differentiate your operations.
Choose a platform that puts you in complete control of your data from the source to the cloud. If the commercial solution you’re looking at limits what you can collect or how you can access or share your data, it’s the wrong platform. Build where it matters, buy where it doesn’t, and architect the integration layer that keeps both options open.
This flexibility becomes even more critical as AI is rapidly maturing. A widely adopted Digital Control Platform makes clean, gap-free, normalised data easily accessible to a growing ecosystem of solutions that can extract increasingly valuable insights from your operational data. We’ll explore how AI is transforming renewable energy operations in an upcoming post.