Welcome Your New Expert Interview Series: Jagdish Konathala, New Expert in the Digital Utility Group – [an Energy Central Power Perspectives™ Expert Interview]

With over two decades of experience in data integration, system architecture, and enterprise solutions, Jagdish has played a pivotal role in reimagining how PGE utilizes the PI System for secure, reliable, and high-availability data access. His leadership in establishing PI Governance Groups, advancing system integrations, and collaborating with external vendors has positioned PGE at the forefront of data-driven innovation in the utility sector.

Join us as Jagdish participates in the requisite New Expert Interview to share his journey, the role of Time Series Data in shaping utility operations, and the emerging trends that will impact the sector’s future.

Matt Chester: Can you tell us about your career journey and what led you to your current role at Portland General Electric?

Jagdish Konathala: After completing my Master’s degree, I was fortunate to land a role at a startup, where I was exposed to Python, building custom ETL jobs, and much more. I then moved to California to work in the energy industry. With a strong background in data, I was tasked with leveraging my expertise for a steam management program in the oil and gas sector. When oil prices halted expansion, I worked at a utility on the East Coast on transmission use cases. I then joined PGE to scale the use of PI. I worked closely with OSIsoft/Aveva to rearchitect the PI System from a 4-server setup to nearly 40 servers, ensuring high availability wherever possible. This set us up for explosive growth. I established PI Governance Group meetings and PI System training sessions, which led to increased usage of the PI System.

Over the past eight years, the amount of data stored has increased eightfold, and the number of users has grown tenfold. With a solid foundation in PI System architecture, we are well-positioned to support system integration needs, securely share data with outside vendors, and ensure more reliable data. I am part of the monitoring and diagnostics group, where we use pattern recognition tools to support our generation fleet and catch issues before they occur.

MC: Could you explain the importance of Time Series Data in the energy sector and how it is utilized at PGN?

JK: A typical utility might have EMS, ADMS data, Generation DCS, and SCADA data behind plant firewalls in a high-security/trust zone. Time series data from all these high-trust sources is stored in a time series historian, which, in our case, is the PI System on the corporate side. This data is invaluable for various groups, such as our merchants trading power, dispatching generation resources, monitoring and diagnostics to assist plants with issues, and for settlement and NERC reports. Having all this critical data, which cannot control the equipment due to a one-way firewall, gives us the advantage of democratizing critical operational data. This means making the data available to many end users in the corporate environment, which would otherwise be impossible due to security constraints.

MC: Can you share specific examples of how the PI System has been pivotal in ensuring high availability and secure data access for critical operations?

JK: The PI System has been instrumental in ensuring high availability and secure data access for critical operations through several key features and implementations:

• High Availability and Redundancy: The PI System is designed to maintain uninterrupted access to data and applications even during system failures or outages. This is achieved by configuring redundant systems that allow for fast, automatic switching between primary and secondary servers in the event of a failure. This setup ensures that critical operations can continue without disruption, providing a reliable data infrastructure.
• Data Security and Access Control: The PI System employs robust security measures to protect critical process data. This includes implementing access control mechanisms that ensure only authorized users can access sensitive data. We recently implemented Zero Trust project where we secure the PI system at a network level in addition to application security controls enhancing security while maintaining ease of access.
• Secure Data Exchange: For secure data exchange with external vendors, the PI System utilizes the PI Web API within a Demilitarized Zone (DMZ). This allows for the safe and secure delivery of near-real-time operational data across network boundaries, leveraging REST APIs for efficient data transmission. This approach not only reduces the time and cost associated with data exchange but also ensures that data remains secure during transit.
• Predictive Analytics and Operational Intelligence: The PI System facilitates advanced predictive analytics through the integration of machine learning applications. For instance, we utilize Curtiss-Wright’s Famos for thermal performance monitoring, which has consistently delivered excellent results over the eight years of its implementation. This capability significantly enhances operational intelligence and aids in optimizing critical processes.

Numerous other examples exist, such as merchant operations (trading), market analytics, settlements, and condition-based maintenance, to name a few.

MC: How do you engage with external vendors to optimize data utilization, and what are the benefits of such collaborations?

JK: Wind, hydro, and solar forecasts are essential for any utility pursuing decarbonization objectives. To facilitate the exchange of operational data with vendors, we employ several strategies. Recognizing that many vendors may not have a PI System, we utilize the PI Web API within the Demilitarized Zone (DMZ). REST APIs, being widely understood, enable the secure and efficient transmission of near-real-time operational data across our network boundaries. This approach significantly reduces both the time and cost associated with data exchange, allowing for a more rapid turnaround.

By leveraging the expertise of our vendors, we gain substantial advantages, including the timely delivery of solutions and results. This collaborative approach not only enhances operational efficiency but also supports our broader sustainability goals.

MC: What trends do you see emerging in the field of Time Series Data and system integration within the energy sector?

JK: The overarching theme is decarbonization, which places a strong emphasis on clean energy. This includes onboarding large-scale batteries, resulting in thousands of data points for each battery project, and working closely with vendors. EV charging pattern studies are also immensely helpful. Operational (time series) data plays an important role in executing these projects.

Cybersecurity and resiliency for business continuity are crucial since our PI system is a critical asset. Projects like Zero Trust significantly decrease the attack surface. Making sure critical data is still available in the event of a ransomware attack will immensely help operations.

Another emerging trend is system reliability. Reliability is a key metric in every major department at a utility, and data is no exception. Instrumentation will only increase, and data storage will grow exponentially. Ensuring that all servers in the PI system architecture are reliable, highly available, and deliver accurate data has always been important, and more emphasis will be placed on this front.

As large language models (LLMs) become more accessible, we will see more use cases utilizing LLMs within the enterprise without data leaving the network. Time series data and LLMs are ripe for use cases involving operational data. I am closely exploring these to extract value. I view LLMs as assistants that can do more for less. We plan to embrace them for what they are, build safeguards, and with human oversight, achieve greater outcomes in shorter times with lower costs. It’s an amazing ROI if you ask me!

MC: What value do you hope to gain from your involvement as a member of Energy Central? And what value do you hope to provide with your peers on the platform?

JK: My main goal is to exchange ideas with other experts in this space. We can learn a great deal from each other, which is a valuable trait in the utility sector. With a background in computer science and a role in business rather than IT, I am in a unique position to influence decisions that provide good returns for the company. I am always exploring and researching other avenues in the data space, and I plan to share my successes with everyone on the platform.

By fostering this collaborative environment, we can collectively advance the field of data analytics and drive more effective, data-driven decision-making across our organizations. This exchange of ideas and expertise has the potential to accelerate innovation and create substantial value for all participants.

I encourage interested professionals to reach out and join this initiative. Together, we can harness the power of our collective knowledge to shape the future of data utilization in our industry.

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Thanks to Jagdish for joining me for this interview and for providing a wealth of insights and expertise to the Energy Central Community. You can trust that Jagdish will be available for you to reach out and connect, ask questions, and more as an Energy Central member, so be sure to make him feel welcome when you see him across the platform.

The other expert interviews that we’ve completed in this series can be read here, and if you are interested in becoming an expert, you can reach out to me or you can apply here.