AI in Protection, Control, and Cybersecurity for Modern Power Systems

In AI in Protection, Control, and Cybersecurity for Modern Power Systems, you'll learn ...

• The responsible integration of artificial intelligence into power system protection, control, and cybersecurity while maintaining professional engineering oversight
• The application of AI-assisted techniques to relay setting analysis, disturbance classification, adaptive protection, and modern grid operating challenges
• The cybersecurity, model risk, testing, and reliability requirements associated with deploying AI in safety-critical power system environments
• How to establish governance, validation, change control, and professional accountability for AI-enabled protection and control systems

Overview

Preview a portion of this course before purchasing it.

Credit: 1 PDH

Length: 13 pages

This course examines the responsible integration of artificial intelligence and machine learning into safety-critical electric power system applications. The course establishes that AI should augment professional engineering judgment rather than replace it, with licensed engineers retaining responsibility for protection settings, control actions, validation, and system performance. It reviews the fundamental protection principles of dependability, security, sensitivity, and selectivity and explains how modern grid conditions—including inverter-based resources, bidirectional power flows, changing topology, and growing data volumes—create opportunities for AI-assisted engineering.

The course explores AI applications in relay setting analysis, disturbance and fault classification, adaptive protection, and operational monitoring while emphasizing the need for human oversight and fail-safe conventional protection. Cybersecurity considerations include network segmentation, access control, data integrity, adversarial machine learning, and protection of AI models and data pipelines. The course also addresses model benchmarking, worst-case testing, reliability validation, version control, audit trails, and continuous improvement. Throughout, applicable NERC, NIST, IEC, IEEE, ISO, and professional ethics requirements reinforce a governance framework designed to make AI implementations secure, transparent, auditable, and professionally defensible.

Specific Knowledge or Skill Obtained

This course teaches the following specific knowledge and skills:

• The fundamental protection principles of dependability, security, sensitivity, and selectivity that AI-enabled solutions must preserve
• The modern grid conditions that create challenges for conventional protection, including inverter-based resources, bidirectional flows, changing topology, and expanding data volumes
• The use of AI and machine learning for relay coordination studies, setting recommendations, online setting checks, and disturbance classification
• The opportunities and limitations associated with adaptive protection in DER-heavy feeders, microgrids, and changing transmission-system conditions
• The safeguards required for adaptive protection, including pre-validated setting groups, conservative fallback settings, communication-failure responses, and human oversight
• The cybersecurity controls needed to protect AI-enabled operational technology, including network segmentation, authentication, access control, encryption, and data integrity
• The identification and mitigation of adversarial machine-learning risks such as malicious inputs, false data injection, model tampering, and abnormal model behavior
• The evaluation of AI model performance using accuracy, precision, recall, error, bias, latency, throughput, fault-record playback, and edge-condition testing
• The model lifecycle and change-management practices required for versioning, validation, documentation, peer review, auditability, and continuous improvement
• How to maintain engineer-in-the-loop accountability and professional defensibility while aligning AI implementation with applicable NERC, NIST, IEC, IEEE, ISO, and engineering ethics requirements

Certificate of Completion

You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 10 questions. PDH credits are not awarded until the course is completed and quiz is passed.