The demand for more power—delivered reliably, safely, and with resilience—has never been greater. The growth in cloud computing and electrification is fueling demand dramatically, while extreme weather and cyberthreats are placing the grid at higher risk.
Amidst this unprecedented change, utilities are turning to artificial intelligence (AI) and machine learning (ML) as powerful strategic weapons. An IBM study found that three-quarters of energy companies have implemented artificial intelligence (AI) in their operations or are exploring the idea.
Impactful use cases for AI and ML in utility operations abound. For example, these technologies can predict asset failures, analyze vegetation for heightened fire risk, detect cyber threats, improve demand forecasting based on patterns, reduce unplanned downtime, improve field crew productivity through smarter scheduling, and optimize the grid based on historical use, consumption trends, weather forecasts, and other critical information. AI is especially adept at analyzing massive volumes of data—a capability which utilities can use to spot trends that warrant action and make the most informed decisions.
Data holds the key to turning AI into an operational advantage, but siloed legacy systems and disparate data sources create formidable obstacles for utilities. The following steps can improve data preparedness for utilities that are ready to transform their operations with AI-enabled applications.
Unify Your Data Sources
An effective utility operation depends on data from many sources, including supervisory control and data acquisition (SCADA) systems, advanced metering infrastructure (AMI), outage management systems (OMS), and the geographic information systems (GIS) that provide a complete view of the grid and utility network. Utilities are also operating asset management, work management, and customer information systems that may not integrate with each other—along with smart grid devices and IoT devices.
Given this complicated web of systems and data sources, it’s imperative for utilities to unify their data, integrate systems in real time, and create a single source of truth about network assets. This step is critical to leveraging AI-powered tools and solutions to their fullest.
Develop a Data Management Strategy
Another vital step in preparing for this transformation is the development of strategies for aggregating and managing the data AI will rely on to improve utility operations. This can include meter data, historical data on grid and network performance, microgrid and islanding data, distributed energy resource (DER) data, and many other types.
Utility data management is a complex undertaking that involves tasks such as these, at a minimum:
- Implementing a data warehouse solution ideally suited to handling utility-specific data
- Developing data integration strategies for microgrid controllers and third-party applications
- Establishing data-sharing protocols with DER owners and aggregators
- Developing the necessary data infrastructure to support microgrid management and islanding operations
- Creating a wide variety of data models, including those that enable microgrid performance analysis and optimization and others that integrate various DER types
- Establishing scalable storage, archiving and retrieval processes for a high volume of data, along with retention policies that balance the need for historical data with the associated costs
Several specific data types require additional data management considerations. For example:
- The proliferation of intelligent grid sensors and IoT devices requires edge computing strategies that support data streaming for real-time monitoring and integrate weather, satellite, and other data to improve resilience, while maintaining governance.
- Gas pipeline integrity management demands the ability to consolidate inspection, maintenance, and risk management data, create quality standards for pipeline material and installation data, and facilitate the required regulatory reporting.
- Gas demand forecasting and supply management requires effective management of historical consumption, weather, and market data, along with access to real-time gas flow monitoring and balancing information and reliable meter readings.
Ensure Data Quality and Integrity
AI algorithms demand high-quality, consistent data. Before adding AI-enabled tools and solutions, consider implementing measures for validating data on transformers, pipelines, and other assets in real time, and establishing data quality metrics specific to utility operations.
GIS data is especially vital to effective field operations, allowing utilities to model and analyze the network with accuracy. So it’s vital to implement processes that ensure GIS data is always accurate and keep data consistent across GIS and other systems. As utilities incorporate increasingly advanced geospatial data from sources like LiDAR (light detection and ranging), it’s equally important to develop strategies for integrating this information while maintaining its integrity.
Shore Up Data Governance
Operating in a highly regulated industry demands attention to data monitoring, control, and governance to ensure compliance. That’s why any strategy for incorporating AI into the utility’s operations must be grounded in a sound data governance approach.
Automated reporting mechanisms, strict data quality controls, and complete audit trails can facilitate timely and accurate regulatory submissions. It’s also critical to define ownership for every data utility type data, develop clear data standards and naming conventions, and implement catalog solutions customized to your data types and use cases. A cross-functional data governance committee that spans operational functions is vital to data stewardship.
Enhance Data Analytics for Better Operational Intelligence
A wide range of data analytics can enhance operations, providing a window into key functions like predictive maintenance, energy demand and load forecasting, demand response, and outage management. AI initiatives are more effective when the utility is better prepared to leverage these metrics.
Before moving ahead with AI full-steam, utilities should take measures such as these to improve their data analytics capabilities:
- Aggregate and consolidate asset performance, load, weather, outage, grid topology, pricing, and operational data, along with maintenance records
- Develop data pipelines that facilitate real-time asset health monitoring and demand response program data integration
- Create data feeds and pipelines for real-time power outage management and restoration, along with dynamic load forecasting and pricing
- Implement data streaming mechanisms that improve real-time grid and network monitoring, factoring in SCADA, grid sensor, and grid state estimation data
- Integrate real-time pricing data with customer systems, while leveraging data to facilitate timely customer notification
Epoch Solutions Group: The Partner that Helps Prepare Your Data for AI
Preparing your data to leverage the power and value of AI is a complex effort. That’s why leading electric and gas utilities partner with the industry specialists at Epoch Solutions Group.
We help utilities prepare for the AI transformation through our industry-leading technology solutions and unrivaled capabilities:
- The EpochField map-first mobile workforce management platform empowers your utility to digitally transform, automate, and streamline field service operations. This single application improves all field workflows and facilitates geospatially enabled back-office scheduling, work type authoring, and work order creation. Available on premise or as a SaaS solution, it’s the foundation you need for AI-ready data—simplifying data integration while ensuring quality and fidelity.
- The EpochSync Pro tool synchronizes data between Smallworld Version Managed Data Stores and Esri ArcGIS Enterprise Geodatabases—providing a flexible, scalable way to integrate data across multiple geospatial systems with consistency and reliability.
- The Epoch UN Blueprint provides a structured process to speed and streamline your transition to the geospatially enabled Esri Utility Network, setting a foundation to implement AI technologies effectively across the operation.
- With extensive expertise in geospatial software implementation, Epoch Solutions Group delivers valuable insights on managing and integrating the geospatial data that’s critical to utility-specific AI applications.
- Our focus on the utility industry affords our team the knowledge and experience to offer tailored solutions that help prepare your data to leverage AI in utility operations.
Building the foundation to facilitate AI implementation is critical for electric and gas utilities that are ready to tackle the challenges of a rapidly changing industry and future-proof their operations. By leveraging Epoch Solutions Group’s deep industry expertise and purpose-built technology solutions, you can create an AI-ready data infrastructure, accelerate your AI transformation, and position your organization for long-term success.
Contact an Epoch Solutions Group sales consultant or visit our website to learn more.