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COPA-DATA, a Global Silver Sponsor of ARC Advisory Group’s 24th Annual ARC Industry Forum in Bengaluru, was represented by Kishor Mandviya, Director of Business Development, COPA-DATA India, together with Varun Garg, Managing Director, Infrared Power Techsol Pvt. Ltd. Their presentation on AI in the energy segment examined how a strong operational technology (OT) foundation, scalable SCADA, and emerging AI capabilities can support increasingly complex renewable energy operations.
Mandviya focused on the importance of building a robust OT layer capable of collecting, managing, and integrating industrial data, while Garg extended the discussion into solar energy operations, where growing plant scale, hybrid assets, and expanding data volumes are creating new requirements for automation and intelligence.
Their presentation can be viewed on YouTube or here:
Building the OT Foundation for AI
Industrial AI depends on the operational systems beneath it.
Mandviya positioned COPA-DATA’s zenon software platform as part of this foundation, supporting applications across manufacturing, process industries, infrastructure, and energy. The platform is designed around characteristics including scalability, robustness, security, performance, openness, validation, and lifecycle management.
These capabilities become particularly important in OT environments, where systems may be expected to operate reliably for many years while integrating equipment and software from multiple suppliers.
zenon can perform different roles depending on the application, including HMI, process automation, energy data management, utilities supervision, Solar PV SCADA, plant information management, and building automation.
Mandviya also highlighted the growing need to connect operational platforms with enterprise systems and emerging AI applications. Rather than treating AI as a replacement for the OT layer, the presentation positioned it as another layer that depends on access to reliable, contextualized operational information.
COPA-DATA positions scalability, robustness, security, openness, validation, and lifecycle management among the core characteristics required for a flexible industrial software platform
Scaling SCADA for Solar Energy Operations
Garg brought the discussion into the renewable energy environment, where SCADA performs a much broader role than simply displaying plant status.
Solar SCADA systems based on the zenon platform, collect real-time information from inverters, transformers, trackers, weather sensors, and substations. They also support plant control based on load requirements and forecasting, visualize KPIs and electrical information, detect faults, store operational data, generate reports, and exchange information with substations and external systems.
Infrared Power describes itself as an engineering-driven, provider of zenon SCADA and monitoring solutions for renewable energy assets. According to the presentation, the company monitors more than 1.5 GW of capacity across more than 45 sites on four continents.
The challenge increasingly lies in scale.
As generation capacity increases, the number of tags and data points can rise rapidly. This places additional demands on servers, storage, redundancy, communications, and engineering design. At the same time, some sites continue to rely on serial communication technologies, potentially introducing latency into increasingly sophisticated control environments.
Grid integration is also becoming more complex as renewable portfolios expand beyond standalone solar projects to include hybrid configurations and battery energy storage systems (BESS).
These trends make scalable OT architecture increasingly important. The greater the number of assets and data sources involved, the more difficult it becomes to rely on fragmented or highly customized integration approaches.
From Monitoring to AI-Assisted Operations
AI introduces the possibility of using the same operational data for more proactive decision support.
Garg highlighted predictive maintenance as one example. Models trained using historical inverter, string, and sensor information could identify patterns associated with component degradation and help operators recognize potential failures before conventional alarms are triggered.
The presentation also explored how Model Context Protocol (MCP) could simplify the connection between operational data and higher-level applications. The longer-term idea is to reduce the amount of custom integration required between field data, asset-management systems, and AI tools.
Generative AI could further change how operators interact with plant information.
Rather than downloading spreadsheets, navigating multiple dashboards, and manually analyzing historical trends, an operator could potentially ask questions in natural language, such as which inverter underperformed during a particular period and why.
This does not eliminate the role of SCADA. Instead, it changes how users may interact with the information that SCADA already collects and organizes.
Infrared Power sees predictive maintenance, standardized connectivity, and generative AI as potential extensions to traditional SCADA, enabling operators to move from reviewing what happened toward identifying what action may be required next
From Automation to More Connected Energy Systems
The presentation described this evolution as a move from traditional automation toward more self-connecting systems.
In conventional automation, systems operate according to predefined rules and logic. As AI, standardized connectivity, and richer operational data become more widely available, energy operators may be able to build systems that identify patterns, surface recommendations, and interact more dynamically with surrounding applications.
For renewable energy operators, this could become particularly important as solar, wind, storage, grid-control requirements, and new loads become increasingly interconnected.
However, greater intelligence also creates new requirements.
Garg highlighted three areas that will require continued attention: cybersecurity and data privacy, the development of more autonomous grids, and the availability of skilled professionals capable of working across AI and energy technologies.
Cybersecurity becomes increasingly important as more operational assets are connected to external platforms and AI applications. At the same time, more dynamic electricity systems will require increasingly sophisticated coordination between generation, storage, consumption, and grid infrastructure.
The workforce challenge is equally significant. Industrial AI in energy requires expertise spanning power systems, automation, data engineering, software, and AI rather than any one discipline in isolation.
Strengthening the Foundation Before Adding Intelligence
The discussion from COPA-DATA and Infrared Power reinforced a recurring theme in industrial AI: advanced analytics and generative AI are only as useful as the operational foundation supporting them.
Reliable data acquisition, scalable architecture, open integration, lifecycle support, and secure connectivity remain essential even as AI becomes more capable.
For renewable energy operators, that foundation becomes increasingly important as plant sizes increase, battery storage is added, grid interactions become more complex, and data volumes continue to grow.
SCADA will continue to play pivotal role for primarily monitoring and control and toward providing the trusted operational data layer in OT space to AI on which increasingly intelligent energy applications can be built and for more meaningful analytics and insight.