Digital Grid Intelligent Operations: Clarifying Underlying Technology Concepts

This article defines Digital Grid Intelligent Operations and clarifies its underlying key technology concepts. Understanding these concepts provides a structured framework for achieving core utility outcomes: self-optimization, adaptive interoperability, and enhanced system resilience.

1. What is Digital Grid Intelligent Operations?

Digital Grid Intelligent Operations is an operating model that defines how people, processes, and technologies deliver value across the grid lifecycle. The model acts across all functional domains of the grid. It involves delegating decisions to assets through Decision Intelligence and leveraging market-driven price signals from transactive energy and flexibility markets, facilitating the transition from reactive to predictive, adaptive, and, where applicable, autonomous operations.

Intelligent operations are enabled by Software-Defined Assets and Digital Twins, which together form Intelligent Industrial Assets capable of dynamically responding to changes in the external environment. Achieving Intelligent Operations requires the holistic integration of Digital Grid Technology Domains. This model enables three core outcomes:

• Self-optimizing Operations – the grid dynamically optimizes its performance.
• Adaptive Ecosystem Interoperability – orchestration with systems such as smart mobility, smart factories, and smart water management systems.
• Adaptive Cyber-physical Security – facilitated by Cyber-physical System Protection Platforms (CPS PP) that actively detect and remediate threats in real time.

Together, these capabilities empower utilities to operate smarter, safer, and more efficiently.

2. Key Underlying Technology Concepts

2.1 Foundational Concepts

"Digital Grid Intelligent Operations is an Operating Model that defines how people, processes, and technologies deliver value across the grid lifecycle."

Digital Grid: The Digital Grid is a Cyber-Physical System of Systems (CPSoS) that orchestrates sensing, computation, control, networking, and analytics to interact with physical assets and humans across all grid functional domains and other digitally enabled ecosystems. It can host higher volumes of renewable energy and enables safe, real-time, secure, reliable, resilient, and adaptable performance, while also facilitating cross-sectoral value creation.

Operating Model: An operating model is the blueprint for how value will be created and delivered to target customers. An operating model brings the business model to life; it executes the business model. It describes how the organization configures its capabilities to execute its actions to deliver business outcomes as defined in the business model.

"The model acts across all Digital Grid Functional Domains."

Digital Grid Functional Domains: Digital Grid Functional Domains are the areas of the grid defined by the functions they perform. They include: Customer, Markets, Service Providers, Operations, Generation (including Distributed Energy Resources), Transmission, and Distribution.

"Achieving Intelligent Operations requires the holistic integration of Digital Grid Technology Domains."

Digital Grid Technology Domains: Digital Grid Technology Domains encompass the following digital technology areas, which together enable the functions of the digital grid:

• Engineering Technology (ET): Engineering Technology (ET) refers to the set of models, data, processes, and software tools used to design, analyze, optimize, and manage the long-term lifecycle performance of physical assets. ET provides the rigorous engineering data (e.g., design specifications, material properties, performance curves, and Digital Twin base models) that ensure the asset's structural integrity, operational capability, and regulatory compliance throughout its entire service life. For example, in the Digital Grid, ET includes the original finite element analysis (FEA) models and material stress specifications that define the maximum safe wind load for a turbine's tower over 20 years, and it manages the thermal degradation models and insulation life curves, which are used to set the optimal long-term operating limits for a substation transformer.
• Consumer Technology (CT): Consumer Technology (CT) refers to all electronic devices, software, and systems designed and primarily managed for personal, non-industrial use by the end-user. These technologies are optimized for user experience, accessibility, and high volume/low cost, operating outside of the strict, real-time safety and utility control domains of OT and ET. CT includes customer-facing applications and devices that allow end-users to manage, monitor, and influence their energy consumption or production. For example, in the Digital Grid, CT includes Smart Thermostats and Home Energy Management Systems (HEMS), which allow customers to optimize their own energy use, and standard Electric Vehicle (EV) chargers and smart appliances whose primary function is convenience but whose interruptible load can be aggregated by the utility's IT/OT systems for demand response.
• Information Technology (IT): Information Technology (IT) is the common term for the entire spectrum of technologies for information processing, including software, hardware, communications technologies, and related services. In general, IT does not include embedded technologies that do not generate data for enterprise use.
• Operational Technology (OT): Operational Technology (OT) refers to the hardware and software that detects or causes a change, through the direct monitoring and/or control of industrial equipment, assets, processes, and events. Unlike IT (which focuses on business data) or CT (which focuses on consumer convenience), OT is mission-critical, demanding high reliability, deterministic timing (low latency), and robust cybersecurity to ensure physical safety and process integrity. In the Digital Grid, OT includes Supervisory Control and Data Acquisition (SCADA) systems, protection relays, industrial controllers (like PLCs), and AMI smart meters used for real-time sensing and control (OT assets enhanced with IIoT capabilities); for example, the OT system executes a high-speed command to trip a substation circuit breaker to prevent system damage or remotely adjust the setpoint of a transformer's voltage regulator.
• Internet of Things (IoT / IIoT): The Internet of Things (IoT) refers to the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment. IoT systems are defined by their wide-scale, distributed connectivity, allowing vast numbers of devices to exchange data and are built primarily upon standard Internet protocols. While the term generally covers all connected devices, the Industrial Internet of Things (IIoT) refers specifically to IoT deployed in industrial and utility environments (like the Digital Grid) that require stricter standards for security, reliability, and scale. For example, a consumer-grade IoT device is a residential smart speaker that senses voice commands, whereas an IIoT device would be an AMI smart meter or a substation sensor that communicates critical, mission-specific power flow data to the grid operator, classifying it as an OT asset that uses IIoT technology.
• Communications: Supports real-time and non real-time data exchange across assets and systems.
• Data and Analytics (D&A): Data and analytics (D&A) refers to the ways organizations manage data to support all its uses, and analyze data to improve decisions, business processes and outcomes, such as discovering new business risks, challenges, and opportunities.
• Cyber-Physical Security / CPS Protection Platforms (CPS PP): Cyber-physical systems (CPS) protection platforms are products that use knowledge of industrial protocols, operational/production network packets or traffic metadata, and physical process asset behavior to discover, categorize, map, and protect CPS in production or mission-critical environments outside of enterprise IT environments.

2.2 Intelligent Industrial Assets (IIAs) Key Concepts

"Intelligent operations are enabled by Software-Defined Assets and Digital Twins, which together form Intelligent Industrial Assets capable of dynamically responding to changes in the external environment."

 Intelligent Industrial Assets (IIAs): IIAs are assets with fully accessible and compatible datasets that support lean, automated, and end-to-end processes that simultaneously optimize operations, engineering, maintenance, planning, and economic performance for current market conditions. IIAs combine pervasive AI, machine augmentation, and unified IT/operational technology (OT) designs to maintain ongoing operational excellence while dynamically responding to changes in the external environment.

"The model involves delegating decisions to assets through Decision Intelligence."

Decision Intelligence (DI): DI is a practical discipline that advances decision-making by explicitly understanding and engineering how decisions are made and how outcomes are evaluated, managed, and improved through feedback. In the context of IIAs, DI enables assets to optimize multiple objectives—such as maximizing power generation while minimizing equipment wear—at the asset (IIA) level, and to support coordinated optimization across interacting assets at the system/grid level. DI leverages multi-objective optimization, machine learning, generative AI, and digital twins to simulate “what-if” scenarios, evaluate trade-offs, and execute autonomous control. It enables assets to operate as proactive, self-optimizing, and adaptive agents within the digital grid.

"Intelligent operations are enabled by Software-Defined Assets..."

Software-Defined Asset (SDA): A Software-Defined Asset (SDA) encapsulates and virtualizes its hardware capabilities to allow remote management of its local configuration (e.g., setpoints) and constraints. This enables optimization of its capabilities, states, and performance across control, automation, function, and topology to achieve higher local performance goals. SDAs can also orchestrate with other assets and/or systems to achieve higher global performance goals without violating asset-specific decision envelopes.

"...and Digital Twins."

Digital Twin: A Digital Twin is a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organization, person, or other abstraction. Data from multiple digital twins can be aggregated for a composite view across a number of real-world entities, such as a power plant or a city, and their related processes. In the context of a digital grid, any asset (e.g., generator, substation, transformer, or home energy system) may have a digital twin for real-time analysis, simulation, and predictive decision intelligence.

2.3 Operating Environment Concepts

"The model leverages market-driven price signals from Transactive Energy and Flexibility Markets."

Transactive energy: Transactive energy (TE) is a set of techniques to manage the generation, consumption, and control of electric power within an electric power system using economic or market-based signals to move energy and account for grid reliability constraints. TE is an economic-value-based network control concept that shares benefits and responsibilities. It is an effective enabling mechanism to exchange information to integrate and orchestrate distributed energy resources (DERs) into local energy markets.

Flexibility Markets: Flexibility markets are digital, market-based platforms that provide balancing resources—such as spinning reserves, energy storage, and demand-side flexibility—to manage variability from intermittent renewable energy sources. By integrating distributed energy resources, large generators, and flexible loads, these markets maintain grid stability, optimize operational costs, minimize renewable curtailment, and support decarbonization goals, leveraging real-time analytics, AI-driven forecasting, and automated dispatch systems.

"Implementing Decision Intelligence in practice requires governance mechanisms that formalize asset identity, automate decision execution, and enforce operational limits. These mechanisms include Energy Asset Passports, Smart Contracts, and Operational Envelopes.”

Energy Asset Passport (EAP): EAP is a secure, unique digital identity assigned to an operational asset within a Cyber-Physical System. It contains verifiable metadata—such as manufacturer, specifications, compliance status, operational history, and lifecycle events—and ensures tamper-resistant provenance. By providing fully accessible, reliable, and interoperable asset information, EAP enables IIAs to coordinate with other assets, execute automated workflows, and maintain trust across the digital grid.

Smart Contract: Smart contracts are blockchain-based, immutable records that automatically execute actions when triggered by defined events. Within IIAs, they link digital twins, asset condition, and operational rules to enable autonomous maintenance, energy transactions, or other coordinated actions. Smart contracts ensure IIAs can act decisively and transparently without human intervention, supporting predictive and adaptive operations.

Operational Envelope: Operational envelopes define the range of safe operating conditions for an asset, including limits on power output, temperature, or other parameters. By encoding these limits into IIAs’ controllers or smart contracts, operational envelopes ensure that autonomous or adaptive actions remain within safe and reliable bounds, enabling IIAs to self-optimize while protecting physical assets and the grid.

Together, these technical capabilities empower utilities to operate smarter, safer, and more efficiently.

3. Conclusion

Grasping the foundational technology concepts of Digital Grid Intelligent Operations empowers utilities to build and operate grids that are resilient, efficient, adaptive, and capable of intelligent, autonomous decision-making. This understanding underpins optimized asset performance, reliable system operation, and seamless integration across digital grid ecosystems.

Alaa Mahjoub is an independent Digital Business Advisor and Operational Technology SME with decades of experience in electric utilities, petroleum, transportation, and defense. His expertise extends across governmental and private sector organizations in the EMEA, Far East, and the United States. Over his career, Alaa has actively contributed to Industrial Automation and Control Systems (IACS), Digital Business Transformation, Enterprise Architecture (EA), Data and Analytics (D&A), as well as Command, Control, Communications, Computers, and Intelligence (C4I). He has spearheaded critical initiatives in these areas at TRANSCO, ADCO, DoT, Injazat Data Systems, and the Egyptian and Kuwaiti Ministries of Defense. Alaa holds B.Sc. and M.Sc. degrees in Computer Engineering from the Military Technical College (MTC) and Cairo University, respectively. He has authored, lectured, and reviewed numerous research papers for the IEEE, Cigre, the Arab Union of Electricity, and the SPE. His current research focuses on Cyber-Physical Systems in the energy and utilities domain.

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