Introduction

In the intricate and dynamically evolving landscape of modern power systems, Power System State Estimation and SCADA Integration are foundational elements for achieving reliable, efficient, and secure grid operation. Supervisory Control and Data Acquisition (SCADA) systems serve as the eyes and ears of the control center, collecting vast amounts of real-time measurement data from across the transmission and distribution networks. However, raw SCADA data often contains errors, noise, and missing values. This is where Power System State Estimation becomes critical: it processes these imperfect measurements using mathematical models to provide a consistent, accurate, and redundant "best estimate" of the entire power system's operating state, including voltage magnitudes and phase angles at all buses. This precise understanding of the grid's real-time condition is indispensable for critical functions such as contingency analysis, optimal power flow, and accurate billing, preventing outages and enabling informed decision-making. Without robust Power System State Estimation and SCADA Integration, utilities cannot truly leverage their operational data to its full potential, leading to suboptimal performance, increased operational costs, and compromised grid reliability.

This intensive 10-day training course is meticulously designed to empower electrical engineers, power system operators, control center personnel, and IT professionals in the energy sector with the theoretical understanding and hands-on practical tools necessary to implement, utilize, and manage advanced state estimation and SCADA integration solutions. Participants will gain a deep understanding of SCADA system architecture, explore various state estimation algorithms, learn about data acquisition and communication protocols, and acquire skills in bad data detection, observability analysis, and the integration of diverse measurement sources like Phasor Measurement Units (PMUs). The course will delve into topics such as cybersecurity for SCADA systems, real-time data validation, distribution system state estimation, the role of state estimation in smart grids, and the challenges of integrating legacy SCADA with modern EMS/DMS platforms. By mastering the principles and practical application of Power System State Estimation and SCADA Integration, participants will be prepared to enhance grid observability, improve operational decision-making, and contribute significantly to the resilience and efficiency of future power infrastructure.

Duration: 10 Days

Target Audience

• Electrical Power Engineers
• Power System Operators and Dispatchers
• SCADA Engineers and Technicians
• Control Center Personnel
• IT/OT Integration Specialists
• Data Analysts in the Energy Sector
• Utility System Planners
• Researchers in Power Systems
• Graduate Students in Electrical Engineering
• Cybersecurity Professionals in Critical Infrastructure

Objectives

• Understand the fundamental concepts and architecture of SCADA systems in power grids.
• Learn about the data acquisition process from field devices to the control center.
• Acquire skills in analyzing various communication protocols used in SCADA.
• Comprehend the definition and importance of Power System State Estimation.
• Explore strategies for applying Weighted Least Squares (WLS) algorithm for state estimation.
• Understand the importance of observability analysis in state estimation.
• Gain insights into bad data detection and identification techniques.
• Develop a practical understanding of Phasor Measurement Units (PMUs) and their role.
• Learn about integrating PMU data into state estimation.
• Master the challenges and solutions of SCADA-EMS/DMS integration.
• Acquire skills in performing distribution system state estimation.
• Understand the cybersecurity risks and mitigation strategies for SCADA/control systems.
• Explore advanced state estimation techniques (e.g., robust, dynamic).
• Develop proficiency in interpreting state estimation results for operational decisions.
• Prepare to design, implement, and manage integrated SCADA and state estimation systems.

Course Content

Module 1: Introduction to SCADA Systems in Power Grids

• Definition and historical evolution of SCADA systems.
• Core functions of SCADA: data acquisition, monitoring, control, alarming.
• Architecture of typical power system SCADA: field devices, RTUs, MTU, HMI.
• Role of SCADA in grid operations: generation, transmission, distribution.
• Benefits and limitations of traditional SCADA systems.

Module 2: SCADA Components and Data Acquisition

• Remote Terminal Units (RTUs): functionality, types, and programming.
• Programmable Logic Controllers (PLCs) in substations and their integration.
• Intelligent Electronic Devices (IEDs) for protection and control.
• Sensors and transducers for measuring electrical quantities.
• Data points: analog, digital, pulse inputs and outputs.

Module 3: SCADA Communication Protocols

• Common communication protocols: DNP3, Modbus, IEC 60870-5-101/104.
• Introduction to IEC 61850 for substation automation and its impact on SCADA.
• Communication media: fiber optics, radio, cellular, power line communication (PLC).
• Network architecture for SCADA communications.
• Latency, bandwidth, and reliability considerations.

Module 4: Fundamentals of Power System State Estimation

• Definition of state estimation: why it's needed, its role as a data filter.
• Power system state variables: voltage magnitudes and phase angles.
• Measurements in power systems: active/reactive power, voltage, current.
• The measurement redundancy concept.
• Basic mathematical formulation of the state estimation problem.

Module 5: Weighted Least Squares (WLS) State Estimation

• Principles of the Weighted Least Squares (WLS) algorithm.
• Measurement model: linear vs. non-linear equations.
• Jacobian matrix and its role in WLS.
• Iterative solution process for WLS.
• Impact of measurement weights on estimation accuracy.

Module 6: Observability Analysis

• Definition of power system observability.
• Methods for determining system observability: topological and numerical.
• Identifying unobservable parts of the grid.
• Strategies for making unobservable systems observable (e.g., adding measurements).
• Impact of measurement outages on observability.

Module 7: Bad Data Detection and Identification

• Sources of bad data in SCADA measurements: sensor errors, communication errors, human errors.
• Residual analysis and statistical tests for bad data detection.
• Bad data identification techniques: largest normalized residual test.
• Dealing with multiple bad data points.
• Impact of bad data on state estimation accuracy and grid operations.

Module 8: Phasor Measurement Units (PMUs) and Synchrophasors

• Introduction to PMUs: technology, capabilities, and synchronized measurements.
• Synchrophasor data: high-precision, time-synchronized voltage and current phasors.
• Applications of PMUs in grid monitoring and control.
• Architecture of Wide-Area Measurement Systems (WAMS).
• Comparison of PMU data with traditional SCADA measurements.

Module 9: State Estimation with PMU Data

• Integrating PMU measurements into traditional state estimators.
• Advantages of PMU data for state estimation: improved accuracy, faster convergence.
• Hybrid state estimation: combining SCADA and PMU data.
• Challenges of PMU data integration: data volume, communication latency.
• Future of state estimation with increasing PMU deployment.

Module 10: SCADA and EMS/DMS Integration

• Role of State Estimation within Energy Management Systems (EMS).
• Integration of SCADA data with Distribution Management Systems (DMS).
• Data flow and interfaces between SCADA, EMS, DMS, and other utility systems.
• Challenges in integrating legacy SCADA systems with modern IT/OT platforms.
• Standards for utility system integration.

Module 11: Distribution System State Estimation (DSE)

• Specific challenges of state estimation in distribution networks (radial topology, high R/X ratio).
• Modeling of distributed energy resources (DERs) for DSE.
• The role of smart meters and other smart grid sensors in DSE.
• Techniques for DSE: pseudo-measurements, linearized models.
• Applications of DSE in Volt/VAR optimization and outage management.

Module 12: Cybersecurity for SCADA and Control Systems

• Identifying cybersecurity threats to SCADA and state estimation systems.
• Attack vectors: network-based, physical, insider threats.
• Security standards and best practices for Industrial Control Systems (ICS).
• Measures for securing SCADA communications and data.
• Incident response and recovery for cyberattacks on critical infrastructure.

Module 13: Advanced State Estimation Techniques

• Robust state estimation methods for handling gross errors and outliers.
• Dynamic state estimation: incorporating system dynamics and Kalman filters.
• Probabilistic state estimation: accounting for measurement uncertainties.
• Network topology processing and parameter estimation.
• State estimation for highly renewable-penetrated grids.

Module 14: Practical Implementation and Software Tools

• Overview of commercial power system analysis software (e.g., PSS/E, DIgSILENT PowerFactory, ETAP).
• Building models for state estimation in simulation software.
• Hands-on exercises: running state estimation, bad data processing.
• Configuring measurement sets and evaluating estimator performance.
• Visualization of state estimation results and operational insights.

Module 15: Future Trends in Grid Observability

• The role of artificial intelligence and machine learning in state estimation.
• Blockchain for secure and verifiable grid data.
• Edge computing for localized state estimation in microgrids.
• Enhanced observability for resilient grid operation.
• Evolution of standards and regulatory requirements for grid data.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.