Smart Grid & Control Systems Course

Lesson 1 • Transmission Line Modelling

Covers pi-model and distributed-parameter line representations. Enables accurate power flow calculations introduced in the next section.

Lesson 2 • AC Power System Basics

Reviews phasors, real and reactive power, and three-phase systems. Provides the mathematical language used throughout all control and optimisation chapters.

Lesson 3 • Frequency Dynamics and Inertia

Explains the relationship between generation-load imbalance and system frequency. Establishes the physics behind frequency control strategies taught next.

Lesson 4 • Power Flow Analysis

Teaches Newton-Raphson and fast-decoupled load flow methods. Students gain the ability to compute steady-state operating points for control design.

Lesson 1 • Core Smart Grid Components

Identifies the physical and digital elements that constitute a smart grid. Connects hardware layers to the communication and control functions covered later.

Lesson 2 • Traditional vs. Smart Grid Architecture

Contrasts conventional one-way power delivery with bidirectional smart grid topology. Provides the baseline needed to understand every subsequent modernisation concept.

Lesson 3 • Communication Networks in Smart Grids

Covers wired and wireless protocols enabling grid data exchange. Establishes the networking foundation required for control system integration.

Lesson 4 • Standards and Interoperability Frameworks

Introduces international standards bodies and interoperability models governing smart grid design. Ensures students can evaluate compliance requirements in real deployments.

Lesson 1 • Phasor Measurement and Synchrophasors

Details GPS-synchronised phasor data and wide-area monitoring applications. Enables students to leverage high-resolution data for advanced control.

Lesson 2 • State Estimation Algorithms

Teaches weighted least-squares and robust state estimation techniques. Students can assess observability and detect bad measurement data.

Lesson 3 • Instrument Transformers and Sensors

Covers current and voltage transformers, PMUs, and digital sensors. Accurate measurement is the prerequisite for all monitoring and control functions.

Lesson 4 • SCADA Systems and Remote Terminal Units

Explains SCADA architecture, RTU polling, and data concentration. Connects field measurements to the control centre environment used throughout the course.

Lesson 1 • Automatic Generation Control Design

Covers area control error calculation and integral control for secondary frequency regulation. Students can configure AGC for single and multi-area systems.

Lesson 2 • Frequency Control with High Renewables

Addresses frequency challenges introduced by low-inertia inverter-based resources. Prepares students to adapt AGC strategies for modern high-renewable grids.

Lesson 3 • Economic Dispatch Integration

Links AGC to economic dispatch to minimise generation cost while meeting frequency targets. Bridges control engineering and power system economics.

Lesson 4 • Governor and Turbine Control Models

Models speed governors and turbine dynamics for thermal and hydro units. Provides the plant models needed to design closed-loop frequency controllers.

Lesson 1 • Distribution Voltage Regulation

Addresses voltage regulation challenges unique to distribution feeders with DERs. Prepares students to manage voltage in active distribution networks.

Lesson 2 • Automatic Voltage Regulators

Covers excitation system models and AVR control loop design. Students can tune AVR parameters to meet voltage regulation and stability requirements.

Lesson 3 • FACTS Devices for Voltage Support

Introduces flexible AC transmission system devices and their control capabilities. Students can select and model FACTS devices for voltage and stability improvement.

Lesson 4 • Coordinated Reactive Power Dispatch

Teaches optimal reactive power dispatch using sensitivity methods and OPF. Connects device-level control to system-wide voltage optimisation.

Lesson 1 • Distribution System Automation Fundamentals

Covers feeder reconfiguration, fault isolation, and service restoration automation. Establishes the operational context for integrating DERs into distribution control.

Lesson 2 • Inverter Control and Grid Interconnection

Details grid-following and grid-forming inverter control modes and interconnection requirements. Enables students to specify inverter settings for stable DER operation.

Lesson 3 • Distributed Energy Resource Types

Surveys solar PV, wind, battery storage, and fuel cell technologies at the distribution level. Provides the resource knowledge base for DER management design.

Lesson 4 • DER Management Systems

Covers DERMS architecture, aggregation, and dispatch of distributed resources. Students can design a DERMS to optimise DER output within distribution constraints.

Lesson 1 • Renewable Energy Forecasting

Covers statistical and machine learning methods for solar and wind power forecasting. Accurate forecasts are essential inputs to the scheduling and dispatch functions.

Lesson 2 • Unit Commitment and Scheduling

Covers mixed-integer programming formulations for unit commitment over planning horizons. Students can solve day-ahead and intra-day scheduling problems.

Lesson 3 • Demand Response and Flexibility

Explains demand response programme types, aggregation, and dispatch in EMS. Students can incorporate flexible loads into grid optimisation and balancing.

Lesson 4 • Optimal Power Flow Methods

Teaches AC and DC OPF formulations and solution algorithms. Enables students to minimise cost or losses while satisfying network and security constraints.

Lesson 1 • Cryptography and Authentication in Grid Protocols

Applies cryptographic techniques and identity management to grid communication protocols. Ensures students can secure data integrity and device authentication.

Lesson 2 • Cyber Threat Landscape for Grid Systems

Catalogues attack vectors, threat actors, and historical incidents targeting grid infrastructure. Establishes the threat context motivating all subsequent security measures.

Lesson 3 • Resilience Planning and Incident Response

Covers resilience frameworks, recovery planning, and cyber incident response procedures. Prepares students to maintain grid operations during and after a cyber event.

Lesson 4 • Intrusion Detection and Anomaly Monitoring

Teaches signature-based and behavioural anomaly detection for grid control networks. Students can deploy and tune monitoring systems to detect cyber intrusions.