Operational Research in the Energy Industry (P00721)

? Credit Points : 5 ? SCQF Level : 11 ? Acronym : MAT-P-OREI

OR techniques are widely used to model and optimize the use of power systems. This course will introduce two key applications: the optimal power flow problem, and system reliability assessment.

This course is divided into two sections:

Optimal power flow (OPF) models. The physical laws which govern electrical power flows must be included in any optimization model on a power network (referred to as optimal power flow models). This course will introduce the necessary physical constraints, building on the students' knowledge of conventional network optimization models. The
counter-intuitive properties of power prices, which arise from this inseparability of the physics of the power system and the economics of power markets, will be discussed. Security constraints, which ensure that the system can survive network component faults, will be introduced. Finally, a range of applications in system planning and
operations will be presented.

System reliability assessment. There has been renewed interest in reliability assessment over recent years, because of issues arising from intermittent renewable generation, and also (in the Great Britain market) regulatory requirements on network performance measures.
Exact, approximate, and simulation-based assessments of the ability of a system's generation capacity to meet demand will be presented. The important current questions surrounding wind generation's ability to support demand will be discussed. Common models for network reliability assessment, considering the consequences of network
component unavailability, will then be described. The necessary mathematical tools will be reviewed at the start of this section.

Entry Requirements

? Pre-requisites : PGs only

Subject Areas

Home subject area

Operational Research, (School of Mathematics, Schedule P)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Block 3 only

? Contact Teaching Time : 10 hour(s) per week for 1 weeks

Summary of Intended Learning Outcomes

Understanding of power network optimization problems, including security constraints, and their implementation in a modelling language.

Ability to assess the adequacy of a system's generation capacity to support demand, and the inclusion of network effects in such models.