Academic Year

2025/26

Module

ELEC3575 Electric Power Systems

Semester

1

Credits

10

Coursework Name

Coursework 2

Assessment Weight

70%

Enhanced Module Pass Rules Apply

Y

Learning Outcomes Assessed

· All module learning outcomes (as outlined in the module catalogue and Minerva page)

Submission Deadline

2:00 PM, Tuesday, Week 11, 9^th December 2025

Late Submission Penalties

5% per day as per the Code of Practice on Assessment

Submission Format

Submission is via the Module Minerva page (/Assessment and Feedback/Coursework 2)

Submit your work in PDF/word format.

Marks and Feedback Format

Marks will be published on Minerva. A detailed breakdown of marks and feedback will be provided upon request during in-person consultations.

Marks and Feedback Release Date

Tuesday 20^th January 2026

Rationale

The coursework is designed to evaluate students' comprehensive understanding and ability to analyse power system components, operational principles, and design challenges using mathematical, computational, and conceptual tools, while fostering critical thinking through case studies using different load flow methods."

This aim ties together theoretical knowledge and real-world applications, aligning with the objectives of the LOs

Assessment Details

This coursework has four main parts. You will need to carry out Tasks T1-T7 for answering Questions 1-a to 1-e. Tasks T8-T11 must be carried out for answering Questions 2-a to 2-e. These tasks are just enabling steps you need to take and there is no need for you to show or explain how you conducted the tasks. Questions 3-a to 3-f are some fundamental questions aimed at assessing what you have learned from our discussions in ELEC3575 about electric power system operations and power flow. Part D is about consideration of ethical, environmental and societal factors (in addition to technical ones), when it comes to system planning and network expansion. You must submit your answers to Parts A-D in one single PDF/Word document via the link provided on the module’s Minerva page.

Assessment Criteria

· Correct use of the phasor method for analysing AC systems in steady-state condition.

· Accurate calculations of real, reactive, and apparent power with logical reasoning.

· Application of mathematical methods to solve load flow problems.

· Correct presentation of formulations, workings, units and interpretation of results.

· Accurate explanation of key components role (e.g. generators, transformers, and transmission lines) and the problems they may be facing in the questions and example systems provided.

· Well-organized, clear, and concise responses and use of technical language and logical flow across sections.

Presentation/Formatting

PDF/Word containing answers to the questions asked.

Word/time limit and guidance

There is no strict word limit (except for Part D which has a 1000 wordcount limit), but recommended page limits for each question as outlined.

Referencing

The School of Electronic & Electrical Engineering uses the IEEE referencing style.

Approximate Workload

If you have completed all of the weekly tasks and laboratory sessions, it is expected that it will take approximately 6 hours to complete the coursework.

Academic misconduct and plagiarism

When you submit for assessment, you are declaring to the University that your work is your own. By submitting work, you confirm that you have read and understood the University’s definition of Academic Integrity and the University’s rules on Academic Misconduct and are aware that if you commit an academic misconduct offence there can be serious disciplinary consequences.

For more information about the University expectations of working with academic integrity and support available to you see the Library's academic integrity webpage. If you have concerns, or would like support or guidance, please contact your Academic Personal Tutor or the Module Leader for advice.

For more information on academic misconduct offences, see the Academic Misconduct Procedure which can be found on the Student Cases webpage.

For more information on the declarations of academic integrity for assessments, see the Academic Misconduct Procedure.

You must not discuss or share the content of or answers to this assessment, with any fellow students, any staff or other contacts outside the school or the University’s professional services.

Use of GenAI

Amber: AI tools can be used in an assistive role

This is an Amber Category assignment meaning that you are permitted to use Gen AI tools, but only

for the specific purpose(s) identified.

Gen AI tools CAN be used in an assistive role for this assignment:

· As a support tutor on the use of MATLAB and math of complex numbers.

Gen AI tools CANNOT be used for this assignment:

· For any other functions beyond the one listed above. You must not use Gen AI to produce answers or other content that you directly submit for assessment or to generate pieces of code you use for answering questions.

If you disregard these instructions and use Gen AI for any purpose beyond those permitted, you risk

being accused of academic misconduct.

The use of Gen AI must be acknowledged in an ‘Acknowledgements’ section of any piece of

academic work where it has been used as a functional tool to assist in the process of creating

academic work.

If it is suspected that you have used a Gen AI tool to produce part of your work, but you have not acknowledged this use, this could be investigated under the Academic Misconduct procedure.

The minimum requirement to include in acknowledgement:

· Name and version of the generative AI system used e.g. ChatGPT-4.0

· Publisher (company that made the AI system) e.g. OpenAI

· URL of the AI system

· Brief description (single sentence) of context in which the tool was used.

For example: “I acknowledge the use of ChatGPT-3.5 (Open AI, https://chat.openai.com/) to

summarise my initial notes and to proofread my final draft.”

For further information on Gen AI and University policy on its use in assignments, see the guidance

document for taught students: https://generative-ai.leeds.ac.uk/uol-genai-guidance-for-taught-

students/