Master of Engineering in Electrical Engineering (Smart Grid)

Introduction to Power System Reliability: Definition, Importance, distribution system reliability, reliability indices.
Modelling of Power System Components: Two-state models for reliability analysis, Fault tree analysis, Failure modes and effects analysis, Reliability block diagrams for component reliability analysis, MTTF, MTTR, Failure Rate, Bath-Tub curve.
Probabilistic Techniques for Power System Reliability: Failure probability and reliability, Monte Carlo simulation, Reliability evaluation using probability density function, Failure modes and effects analysis, case studies and simulation. 
Network Modeling for Reliability Assessment: Analysis of systems of independent components, series systems, Parallel systems, Series-parallel systems, bridge network, methods for identification of component importance, Markov modelling, Lifetime models, Data used for reliability assessment, case studies and simulation.
Reliability-Centered Maintenance: Principles of reliability-centered maintenance, Reliability Centered Asset Management (RCAM), Life Cycle Cost Analysis (LCCA), integration of sustainability and resilience in asset management decisions.

Introduction to Distributed Energy Sources (DERs): Overview of the electric power system, Distributed Energy Sources and grid integration of DERs
DERs Technologies: Solar photovoltaic (PV) systems, Wind power systems, Fuel cells, Microturbines, Combined Heat and Power (CHP) systems, Energy storage systems.
Interconnection Standards and Grid
Integration of Distributed Generation: Interconnection standards and regulations, Grid integration requirements, Distributed generation and power quality, Power system stability and control, NEPRA Grid Codes.
Energy Management Systems (EMS): Introduction to EMS, EMS applications for distributed generation, Integration of distributed generation with EMS. 
Distributed Generation Planning and Operation: Distributed generation planning, design, operation and maintenance, Load management and demand response, Case studies of successful distributed enervation projects, analysis of the economic and environmental impacts of distributed generation

Introduction to Reactive Power Control: Importance of reactive power in power system operation, Reactive power sources and sinks, reactive power balance in power systems.
Reactive Power Control Devices and Their control strategies: Capacitors and reactors, Synchronous condensers, Static VAR compensators (SVCs), Static synchronous compensators (STATCOMs), Unified Power Flow Controllers (UPFCs), control of Reactive Power Devices.
Modeling and Simulation of Reactive Power Control: Mathematical models of reactive power devices, Simulation of power system operation with reactive power control, Case studies of reactive power control in power systems. 
Reactive Power Control and Management: Voltage regulation using reactive power, Power factor correction, voltage stability and reactive power, Reactive power dispatch, reactive power management for utility and industrial plant, selection and costing of equipment for reactive power management, harmonic mitigation, reactive power control in distributed energy resources, Case Studies in reactive power control.

Introduction to Machine Learning: Overview of machine learning, Types of machine learning algorithms, Machine learning process and workflow, Supervised Learning and Linear Regression Decision Tree and Random Forest, Naïve Bayes and Support Vector Machine: Unsupervised Learning: Unsupervised learning, Clustering techniques, Dimensionality reduction, Evaluation of unsupervised learning results, Natural Language Processing and Text Mining Deep Learning: Basics of artificial neural networks (ANN), Feedforward neural networks, Activation functions and backpropagation, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Introduction to TensorFlow, Keras, PyTorch.
Time Series Analysis: Time series data and its characteristics, Time series visualization and decomposition, Evaluating time series models, Handling seasonality and trend

Introduction to Data Analytics: Overview of data analytics and their applications in engineering, Types of data and data sources, Data preprocessing techniques, Data visualization techniques, Outlier detection and removal.
Statistical Analysis Techniques: Probability and probability distributions, Time Series Analysis, Hypothesis testing, Regression analysis.
Data Mining Techniques: Association rules, Clustering, Decision trees, Random forests 
Optimization Techniques: Linear and Nonlinear programming, Genetic algorithms, Simulated annealing by using the tools Excel, Tableau, python and others.
Applications and Case Studies: Applications in respective field, Grid Monitoring and State Estimation, False Data Injection Attacks against State Estimation, State Estimation, MMSE State Estimation and Generalized Likelihood Ratio Test, Demand Response, Communications and Sensing.

Introduction: Understand the electricity supply industry; Structure, Operation and Management of the Electricity, Supply Chain; Policy – Issues, Priorities, Stakeholders.

Investment in Generation and Transmission: Efficient investment in electricity generation, Market-based investment in electricity generation and Transmission, Power Purchase Agreements (PPAs) and other Contractual Arrangements.

Policies and Standards: Renewable Energy and Environmental Policies, Electricity Market with wind-solar-integrated power systems, Policy – Issues, Priorities, Stakeholders, Influencers; Liberalization, Deregulation and Regulation; Circular debt, Power Capacity.

Regulatory Policy: Overview of regulatory policy, Federal and provincial policy, Feed-in-tariffs (FITs) and net metering policies.

Energy Storage System (ESS): Battery types covering alkaline, Li-ion, Nickle metal hydride, Ni- Cd, Lead acid, LiFePo4 and others, their Characteristics, Ratings, Standards for ESS, technical comparison of ESS technologies.
Battery Management Systems (BMS): Principles and components, Functions of BMS in monitoring, control, and optimization of battery performance. 
Power Conversion Systems (PCS): Role, Types, operation of PCS in energy storage and grid integration.
Energy Management Systems (EMS): Functions and objectives of EMS in energy storage applications, Optimization algorithms for energy dispatch and storage, Coordinated control of ESS components
Power Plant Controller (PPC): PPC and its role in grid stability and reliability, Coordination of multiple ESS and generation units through PPC, Integration of ESS Components: Interface and communication protocols between BMS, PCS, EMS, and PPC.

Renewable Energy Integration Challenges: Impact of variability, unpredictability, and power quality issues, Grid Stability in the Presence of Renewable Energy, methods for assessing and enhancing grid stability in renewable-rich environment, Low Inertia Challenges, Strategies for mitigating low inertia effects through control and grid reinforcement.
Protection Schemes for Renewable Energy Integration: Protection principles, Design and implementation of protection schemes for renewable energy integration.
Grid Codes and Standards: Grid codes and interconnection standards relevant to renewable energy integration, Strategies for managing uncertainty and optimizing resource allocation.
Energy Storage Solutions: Role of energy storage in addressing grid stability and inertia challenges, Integration of energy storage systems into renewable energy projects and power grids.
Advanced Control Strategies: Advanced control techniques for renewable energy integration, Frequency regulation and power balancing in renewable-rich grids.

Smart Grid - Structure, challenges, need for security; European and other country approaches to Privacy and Data Protection in Smart Grids; The Evolution of the Smart Grid Threat Landscape and Cross-Domain Risk Assessment; Resilience Against Physical Attacks; Secure Communications in Smart Grid; Networking and Protocols, Cyber-Secure and Resilient Architectures for Industrial Control Systems; Establishing a Smart Grid Security Architecture; Secure Development Life Cycle; Operational Smart Grid Security; Implementation Experiences from Smart Grid Security Applications and Outlook on Future Research.

Mathematical Background: matrices, state space representation, optimization techniques, egression.
Static State Estimation: Least error squares (LES) algorithm, least absolute value (LAV) algorithm to solve the linear static estimation problem, Linear constrained LAV problem and its solution, on linear LAV problem and its solution.
Load Modeling for Short-Term Forecasting: different models for short-term load forecasting, troducing three models for winter and summer short-term load forecasting, explaining different factors that affect these models for each season, fitting each model to the different techniques that are used to estimate the parameters of the model.
Fuzzy Regression Systems and Fuzzy Linear Models covering fuzzy fundamentals, fuzzy set theory, fuzzy linear estimation and regression, fuzzy Short-Term Load Modeling.
Dynamic State Estimation: Discrete Time Systems, Discrete Time-Optimal Filtering, Recursive Least Error Squares.
Load Forecasting - Load Forecasting using Static State Estimation, Load Forecasting Using Fuzzy Systems, Dynamic Electric Load Forecasting, Electric Load Modeling for Long-Term Forecasting.
 

FACTS (Flexible Alternating Current Transmission) concepts: Reactive power control in electrical power transmission, principles of conventional reactive power compensators. Introduction to FACTS, types of FACTS controllers.
Static shunt and series compensators: Shunt compensation – objectives of shunt compensation, methods of controllable VAR generation, static VAR compensators – SVC, STATCOM, SVC and STATCOM comparison.
Combined compensators: Unified power flow controller (UPFC) and Interline power flow controller (IPFC) - Introduction, operating principle, independent real and reactive power flow controller and control structure, concepts relating to Reactive power compensation and harmonic current compensation using Active power filters.
HVDC (High Voltage Direct Current) transmission: HVDC Transmission system: Introduction, comparison of AC and DC systems, applications of DC transmission, types of DC links, Layout of HVDC system. HVDC Converters.
Control of HVDC system: Principles of control, Different control features, Introduction to multiterminal DC systems and applications, comparison of series and parallel MTDC systems, Voltage Source Converter based HVDC systems.
 

Energy Auditing: Load calculations, heating load calculation, lighting load calculations, ISO standards, rate of return calculations, life cycle assessment, energy metering, tariff calculations, two-way metering.
Smart Home: Energy efficient loads, smart and energy efficient devices, PV and wind installation, application of IoT in smart home, recent trends and technologies; Smart Home and Building Automation Standards.
Battery Management System (BMS): Operation and working of electrochemical batteries, Lithium ion batteries, battery management system and requirement for sensing and high voltage control, BMS design requirements.
Electric Vehicles (EV): EV vs. gasoline cars, EV working, Electric motors, Regenerative braking, motor selection, storage technology for EV, Charging of technologies for EVs. Standards for smart storage and plug-in electric vehicles, including standards for electric storage, and E-mobility/plug-in vehicles
 

Introduction to Smart Grids: Main features, Drivers for smarter grids, conventional power system and smart grid, micro and nano grids. 
Integration of low-carbon technologies and methods: Low-carbon technologies, Impact on the long-term and short-term security, impact on the energy market, impact on power system operation, smart metering, Demand side management technologies, electricity distribution network, Distribution Management System – off line control, active Network Management technologies – real time control, Role of ICT technologies.
De-carbonisation of heat and transport: Electrification of heating and heat pumps, transport and electric vehicles, Modelling of low-carbon technologies through efficiencies and emission factors
Flexibility in low carbon electricity systems: Sources and potential benefits, Flexibility in the supply side and relevant generator parameters, Demand-side management and its potential benefits, Residential flexible loads and a possible categorization. 
Low-carbon technologies – technical aspects and their impacts: PV and wind impacts and challenges: EV impact and challenges: EVs, specifications and demand, EV changing methods and their impact on distribution networks.
 

Electricity Markets and Pricing: Overview of electricity markets, key players, Factors impacting electricity pricing, Market structures and pricing strategies, Time dependent pricing models, Methods for estimating electricity prices, Monte Carlo Simulation in Electricity Markets.
Electricity Generation and Emissions: Various electricity generation sources (fossil fuels, renewables, nuclear), Balancing Economic Efficiency and Environmental Sustainability: Concept of externalities within energy markets Cost-benefit analysis and social cost of emissions.
Role of Renewable Energy: Role of renewable energy sources in emission reduction, Challenges and opportunities, Grid management and storage solutions.
Policy and Regulation: Environmental policies and regulations influencing the electricity sector.
Modeling Electricity Pricing and Emissions Scenarios: Modeling tools and software, Constructing and analyzing scenarios for electricity pricing and emissions reduction, Real-world case studies illustrating electricity pricing and emissions reduction initiatives.