Sohail Khan

Sohail Khan

PhD Electrical Engineering (Power Systems) | Energy Data Analyst | Team Mentor | Aspiring Energy Data Scientist

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

open_positions

portfolio

projects_completed

projects_in_progress

publications

Dynamics of wind-turbine driven Self-Excited Induction Generator with online parameter calculation

Published in In the proceedings of IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society, 2013

Use Google Scholar for full citation

Recommended citation: Sohail Khan, Mohsin Shahzad, Peter Palensky, Khurram Jahangir, "Dynamics of wind-turbine driven Self-Excited Induction Generator with online parameter calculation." In the proceedings of IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society, 2013.

A replicator dynamics method for the unit commitment problem

Published in In the proceedings of 2014 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2014

Use Google Scholar for full citation

Recommended citation: Sohail Khan, Hadrien Bosetti, Peter Palensky, Wolfgang Gawlik, "A replicator dynamics method for the unit commitment problem." In the proceedings of 2014 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2014.

Co-simulation based platform for thermostatically controlled loads as a frequency reserve

Published in In the proceedings of 2016 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2016

Use Google Scholar for full citation

Recommended citation: Aadil Latif, Sohail Khan, Peter Palensky, Wolfgang Gawlik, "Co-simulation based platform for thermostatically controlled loads as a frequency reserve." In the proceedings of 2016 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2016.

Stochastic Battery Model for Aggregation of Thermostatically Controlled Loads

Published in In the proceedings of 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan, 2016

Use Google Scholar for full citation

Recommended citation: Sohail khan, Mohsin Shahzad, Usman Habib, Wolfgang Gawlik, Peter Palensky, "Stochastic Battery Model for Aggregation of Thermostatically Controlled Loads." In the proceedings of 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan, 2016.

Optimal energy interruption planning and generation re-dispatch for improving reliability during contingencies

Published in In the proceedings of 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020

Use Google Scholar for full citation

Recommended citation: Sohail Khan, Sawsan Henein, Helfried Brunner, "Optimal energy interruption planning and generation re-dispatch for improving reliability during contingencies." In the proceedings of 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020.

Evaluation of sensitivity based coordinated volt-var control and local reactive power for voltage regulation and power exchange across system boundaries in smart distribution networks

Published in Electric Power Systems Research, 2021

Use Google Scholar for full citation

Recommended citation: Sohail Khan, Paul Zehetbauer, Roman Schwalbe, "Evaluation of sensitivity based coordinated volt-var control and local reactive power for voltage regulation and power exchange across system boundaries in smart distribution networks." Electric Power Systems Research, 2021.

Calculation of reactive power requirement for voltage improvement at Mardan station

Published in In the proceedings of 2022 7th Asia Conference on Power and Electrical Engineering (ACPEE), 2022

Use Google Scholar for full citation

Recommended citation: Salman Khan, Arsalan Masood, Sohail Khan, Arqum Shahid, "Calculation of reactive power requirement for voltage improvement at Mardan station." In the proceedings of 2022 7th Asia Conference on Power and Electrical Engineering (ACPEE), 2022.

talks

AI in Power System Planning and Operation

Published:

The talk explores the transformative role of AI in power system planning and operation and give direction regarding research and development in this area.

Type-1 Hypervisor and Container Orchestration Platform on High-Performance Computing Cluster for AI and Big Data Applications

Published:

We are in the midst of a significant transformation focused on integrating large-scale simulation, generative AI, and machine learning technologies across various domains. This shift underscores a critical demand for professionals capable of establishing and managing High-Performance Computing (HPC) clusters and associated platforms. In my current role within the organization, my responsibilities encompass the installation of software stacks and networking infrastructure on our HPC platform (refer to attached details). Notably, we have successfully implemented a type-1 hypervisor alongside its pertinent components to oversee virtual machine and container workloads on the HPC cluster. Furthermore, our deployment of Kubernetes as a Container Orchestration Platform has streamlined client services. During this forthcoming presentation, I will present the best practices involved in deploying these systems and explore their diverse applications.

teaching

ECE-822 Advanced Power System Analysis

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2022

Course Description: This course is the part of MS Energy Power System course titled “Advanced Power System Analysis”. The course will provide a rigorous understanding of electrical power system such as, per unit system of calculations, modelling of transformers, generators, and loads, understanding of one-line diagram, bus admittance matrix, load flow analysis, different type of faults and artificial intelligence (ai) in power system. advanced power system analysis is a core-course in the electrical engineering program and is a pre-requisite for several other technical electives. The students are also acquainted with the applications of optimal power flow by introducing different methods of economic dispatch and energy conservation.

ECE-823 Advanced Power System Operation and Controls

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2023

Course Description: This course deals with different aspects of power system operation; monitoring and control with a view to enrich knowledge of students in this important area of power engineering

Artificial Intelligence for Smart Energy Systems

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2023

Course Description: This course aims teach you how to digitalize the ‘conventional’ energy system and which digital technologies plays a key role. The digitized grid operations then open ways of the application of AI, machine learning, blockchain and computer simulations. The objective of this transformation is to make the energy system sustainable, affordable, available, and secure. This course teaches about the opportunities of a digital grid and the various digital technologies to achieve this. The course consists of an introductory and four-course content modules, each touching upon a different facet of the digital transformation and application of artificial intelligence in the energy system: • The Digital Transformation of the Energy System • Computational Methods for Energy Networks • Decision Support in Integrated Energy Systems • AI-Based Data and Machine Learning Approaches

RSE-871 Artificial Intelligence in Railways

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2023

Course Description: This course delves into the fundamental concepts and algorithms that underpin modern artificial intelligence, with a specific focus on their application in optimizing rail infrastructures worldwide. As we strive to enhance the efficiency of rail systems while maintaining stringent quality standards and ensuring passenger comfort, the integration of artificial intelligence (AI) becomes imperative.

COMP201 Data Structures and Algorithms

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2023

Course Description: Data structures and algorithms is one of the core courses in computing and focuses on efficient storage of data in memory to facilitate their subsequent processing. It mainly covers elementary data structures and associated algorithms to manipulate them. Topics include lists, stacks, queues, arrays, trees, graphs, sorting and searching. This course offers the students a mixture of theoretical knowledge and practical experience. This includes sequential storage (lists, queues, and stacks), hierarchical storage (trees), and association/adjacency storage (graphs). Students will also become familiar with algorithm analysis and design techniques.

ECE-261 Introduction to Embedded Systems

Undergraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2024

Course Description: Introduction to Embedded Systems, General Purpose vs. Embedded Computing, Multicore processors, Components of Embedded System, Microprocessors vs. Microcontrollers, Processor Architecture, Neumann vs. Harvard, RISC vs CISC. Memory, Registers, Cache, RAM, SRAM, DRAM, ROM, PROM, EEPROM, FLASH. Introduction to AVR microcontroller, ATMEGA328P architecture and features, Internal Registers, Memory, ATMEGA328P Instruction Set. Machine code, Addressing modes and Instruction Set, I/O Programming, Arithmetic and Logical Instructions, Branching Instructions, Generating Delays, Interrupt handling, Timers, PWM using Timers, DC motor interface, Communication Ports programming, UART Bluetooth Module Interface, AT Commands, ADC, Successive Approximation ADC, Temperature Sensor, Keypad & LCD Interface, Revision of selected topics.

ECE-141 Introduction to Robotics

Undergraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2024

Course Description: “Introduction to Robotics” provides a comprehensive overview of the fundamental principles, technologies, and applications in the field of robotics. The course begins with an exploration of the definition and diverse applications of robotics, accompanied by a historical perspective on the evolution of robotic systems. Students delve into the anatomy of robots, examining components such as sensors, actuators, manipulators, and end-effectors, gaining an understanding of their structure, design, and functionality. Robot kinematics is thoroughly covered, encompassing topics such as motion, positioning, forward and inverse kinematics, as well as various types of joints and configurations. Emphasis is placed on sensor technologies, including proximity, vision, and touch sensors, and their integration for data processing. Similarly, students explore the realm of actuators, learning about motors, servos, pneumatics, and techniques for actuator control and manipulation. Programming robots constitutes a significant portion of the course, with an introduction to popular robot programming languages such as ROS, Python, and C++. Students learn the basics of control and various programming paradigms. Robotics perception is addressed, focusing on computer vision techniques for object recognition, tracking, and mapping. Robot motion planning is explored, covering path planning, trajectory generation, collision avoidance, and obstacle detection. Additionally, students delve into robot localization and mapping techniques, including Simultaneous Localization and Mapping (SLAM), odometry, and sensor fusion. The course also covers robot control systems, encompassing feedback control, closed-loop systems, PID controllers, and motion control strategies. An introduction to artificial intelligence (AI) in robotics is provided, highlighting machine learning applications and ethical considerations. The societal impact of robotics, including its implications for jobs, privacy, and ethical considerations, is also discussed. Throughout the course, students engage in hands-on labs and projects, where they assemble, program, and experiment with robotic systems, culminating in the development of simple robotic systems. Emerging trends and technologies in robotics, such as soft robotics, swarm robotics, and human-robot interaction, are explored to provide students with insights into future developments in the field.

COMP-832 Knowledge Representation and Reasoning

Undergraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2024

Course Description: Knowledge engineering is the science of solving problems by applying human knowledge on the facts and then using reasoning to reach a conclusion. The facts are based on data which needs to be transferred to a database to apply human-like reasoning. Typically, an AI problem has a solution based on human interpretation of the problem. Knowledge engineering is the process of imitating how a human expert in a specific domain would act and make decisions. In this course, a student will learn how to use human knowledge in AI to solve real life problems.

Artificial Intelligence for Smart Energy Systems

Postgraduate course, Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Sino-Pak Center for Artificial Intelligence, 2024

Course Description: This course aims teach you how to digitalize the ‘conventional’ energy system and which digital technologies plays a key role. The digitized grid operations then open ways of the application of AI, machine learning, blockchain and computer simulations. The objective of this transformation is to make the energy system sustainable, affordable, available, and secure. This course teaches about the opportunities of a digital grid and the various digital technologies to achieve this. The course consists of an introductory and four-course content modules, each touching upon a different facet of the digital transformation and application of artificial intelligence in the energy system: • The Digital Transformation of the Energy System • Computational Methods for Energy Networks • Decision Support in Integrated Energy Systems • AI-Based Data and Machine Learning Approaches