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EE50234: Applied electrical power system analysis

Academic Year: 2018/9
Owning Department/School: Department of Electronic & Electrical Engineering
Credits: 6      [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 2
Assessment Summary: EX 100%
Assessment Detail:
  • Examination (EX 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must take EE30215
Description: Aims:
To provide details about electrical power system analysis techniques.
To identify the need for various analysis methods within electrical power system operation and planning.
To use case studies and practical coursework to identify appropriate analytical methods for a range of power systems problems.

Learning Outcomes:
To state the reasons for the use of various complex analysis tools in the planning and operation of modern electrical power systems.
To describe the characteristics of the modern analytical tools needed for "Big Data" analytics, load and generation forecasting for systems with embedded generation and large-scale renewable resources, planning studies and operational optimisation.
To use statistical modelling, machine learning or optimisation techniques as appropriate.
To use standard software and suitable data structures to implement the analysis of modern and future electrical power systems, which includes smart-meters, embedded generation and energy storage.

Skills:
To solve appropriate numerical problems (T & A).
To analyse and optimise the performance of the principal subsystems in an existing electrical power system (T & A).
To successfully apply fundamental principles of electrical power systems to a range of technical problems (T & A).
To synthesise a comprehensive and critical review of an appropriate technical area (F & T).

Content:
The component parts of modern electrical Power systems: conventional generation; transmission grid; distribution networks; renewable generation resources; embedded generation; energy storage; electric vehicles; smart meters.
Modelling the behaviour of the modern electrical power system using methods such as "Big Data", statistical modelling, Markov Chains and machine learning.
Optimising the planning and operation of the modern electrical power system using techniques such as Mixed Integer Linear Programming and Monte-Carlo.
Practical implementation of analytical solutions for modern electrical power systems using software packages, such as Matlab and SPSS and languages, such as Python and R.
Programme availability:

EE50234 is Compulsory on the following programmes:

Department of Electronic & Electrical Engineering

Notes:

  • This unit catalogue is applicable for the 2018/19 academic year only. Students continuing their studies into 2019/20 and beyond should not assume that this unit will be available in future years in the format displayed here for 2018/19.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Undergraduates: .
  • Postgraduates: .