Boosting Organizational Intelligence With a Modern Data Architecture

As utilities work toward a more renewable energy portfolio, they can derive valuable insights and revenue from their data.

Jan 7, 2025 | By Marc Smith

With shifts toward decarbonization and renewable energy, utility companies have a unique responsibility to meet customer demands while satisfying investor stakeholders. Fortunately, with the power of data, utilities can not only develop a better strategy to reach their goals but also track their performance incentive progress.

In our previous article, we explored the concept of modern regulatory frameworks, including the shift to performance-based regulation (PBR). Now we’ll dive further into how utilities can improve performance outcomes through increased intelligence that powers smart grids.

Increasing Intelligence Through Smart Grids

In addition to innovative generation and demand-side technologies, utilities are also investing in a broader interconnected system of intelligent networks. This grid modernization is enabled largely through the ubiquity of smart meters and other data sensor-based collection systems. There are also several demand-side control systems being deployed to manage the distributed, two-way nature of the power grid.

Along with grid modernization comes increasingly rich network data. There are substantial opportunities to leverage this utility data to unlock demand-side grid resources, increase situational awareness and resiliency of the grid, and meet performance incentives to drive desired outcomes.

Incentives for Sharing Utility Data

Utility firms work with multiple public and private stakeholders to help ensure safe, reliable and affordable energy throughout the energy transition. These stakeholders need real-time energy cost and usage data to understand and make informed decisions for questions such as:

• What customer renewable programs are effective in changing usage patterns?
• Are programs effectively time shifting loads and generating more distributed energy resources (DER s) grid services?
• What impacts do DERs have on circuit and transformer reliability?
• How effective are resilience programs to support climate adaptation?
• Can the network support the growing demand for electricity through electrification?

Utilities tend to have the clearest insight into this data, and they use the information to make decisions on how to best deploy capital and achieve profitability. Obtaining performance incentives in a modernized regulatory framework requires working with regulators to ensure data transparency.

More transparent energy and utility data enable customers and providers to make more efficient decisions to reduce costs and increase the value of their energy systems for their specific needs. Additionally, public policy entities can use utility data to foster system optimization, and utilities can generate new revenue streams from the sale of nontraditional products and services.

Sharing this valuable data across multiple stakeholders requires a data marketplace that enables access and collaboration in a managed way. Providing this level of transparency also requires effective data governance, including customer consent. Alternatively, utilities can share anonymized data as part of an evolving platform function. But even this option will still require clear policies and processes, including external data sharing agreements, terms of use, data anonymization and data quality.

Embracing a Modern Data Architecture

The prospect of sharing aggregated data through a marketplace requires the implementation of data systems to support data aggregation, analysis and sharing. A modern data architecture is crucial for utilities to support the energy transition and provide the necessary transparency to stakeholders to meet performance incentives. Integrating this data into a single data platform requires state-of-the-art data management techniques and analytical processing in scalable, high-performing and secure cloud environments.

Utilities are embracing data modernization, not only to enhance data transparency but also to integrate large volumes of high-granularity, high-frequency data from many disparate operational systems. This includes multiple types of data, such as data around customers, programs, assets, inspections, weather data and geospatial information, as well as real-time sources.

In addition to providing multiple end points to consume data for visualization and analysis, this integrated modern data architecture also creates a foundation for digital twins. The goal of a digital twin is to create a virtual representation of a physical object, system or process. This digital replica is designed to mimic the real-world counterpart as closely as possible, using real-time data and simulation models that allow for surveillance, monitoring and optimization of the network. Digital twins are the ultimate tool to enable decision-making around efficiency, reduced downtime and maintenance costs.

Data as a Strategic Asset

It all starts with data. Treating your data as a strategic asset requires a clear strategy and a mature operating model for data governance and management. With a comprehensive strategy in place, you can then shift your focus to data modernization for strategic use.

Your data strategy should define exactly what data assets your business has and how you can derive key intelligence to monetize that data within your organization to achieve business outcomes. The resulting data intelligence is the final and most valuable step in the data value chain, where your business can clearly drive economic value from this intangible asset—putting your data to work.