In April 2016 Manchester eScholar was replaced by the University of Manchester’s new Research Information Management System, Pure. In the autumn the University’s research outputs will be available to search and browse via a new Research Portal. Until then the University’s full publication record can be accessed via a temporary portal and the old eScholar content is available to search and browse via this archive.

Estimation of Dynamic Load Model Parameters using Real-time Measurements and a Flexible Phasor Data Concentrator

Nechifor, Alexandru

[Thesis]. Manchester, UK: The University of Manchester; 2017.

Access to files

Abstract

This thesis presents the development of an advanced monitoring platform aimed at increasing the transmission/distribution network operator’s understanding of load dynamics. The advanced monitoring platform is capable of real time estimation of dynamic load model parameters, based on measurements received from substation installed Phasor Measurement Units. The underlying communication infrastructure is represented by a Wide Area Measurement System enabled by flexible 4G routers running the Linux operating system. The thesis contributions include a new improved load model, a new Phasor Data Concentrator and development of the advanced monitoring platform according to enterprise standards. Results from both load modelling and data concentrator perspectives are seamlessly integrated into the platform, developed according to a set of enterprise standards ensuring high levels of scalability, reliability and security. Two exponential recovery load models from the existing literature (ERL1 and ERL2) are first presented and their limitations are investigated. The dynamics of ERL1 and ERL2 are modelled by first order differential equations, hence the inability to track the inherent oscillatory response of loads with a high share of induction motors. To address this shortcoming, a new improved load model (OCL) is proposed, comprising a second order differential equation. The mathematical framework for ERL1, ERL2 and OCL is rigorously derived and presented. Detailed testing and comparison of ERL1, ERL2 and OCL is undertaken using synthetic signals generated in Matlab, dynamic power system simulations in DIgSILENT, signals generated within a controlled laboratory environment, and real substation data. A new Phasor Data Concentrator (PDC) is developed, in order to gain full control over the Phasor Measurement Unit (PMU) data flow and reduce data processing delays. The new PDC uses a multiplexing technique to manage threads and significantly reduce latency. The data processing delays obtained for the new PDC are much lower than values reported in the available literature and values obtained during laboratory testing of another freely available PDC technology. The new improved load model and PDC are integrated into a real-time platform compatible to the Java EE7 enterprise standards. Benchmark tests show a high level of scalability and reliability for the resulting real-time load modelling platform.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Electrical & Electronic Engineering (42 month)
Publication date:
Location:
Manchester, UK
Total pages:
164
Abstract:
This thesis presents the development of an advanced monitoring platform aimed at increasing the transmission/distribution network operator’s understanding of load dynamics. The advanced monitoring platform is capable of real time estimation of dynamic load model parameters, based on measurements received from substation installed Phasor Measurement Units. The underlying communication infrastructure is represented by a Wide Area Measurement System enabled by flexible 4G routers running the Linux operating system. The thesis contributions include a new improved load model, a new Phasor Data Concentrator and development of the advanced monitoring platform according to enterprise standards. Results from both load modelling and data concentrator perspectives are seamlessly integrated into the platform, developed according to a set of enterprise standards ensuring high levels of scalability, reliability and security. Two exponential recovery load models from the existing literature (ERL1 and ERL2) are first presented and their limitations are investigated. The dynamics of ERL1 and ERL2 are modelled by first order differential equations, hence the inability to track the inherent oscillatory response of loads with a high share of induction motors. To address this shortcoming, a new improved load model (OCL) is proposed, comprising a second order differential equation. The mathematical framework for ERL1, ERL2 and OCL is rigorously derived and presented. Detailed testing and comparison of ERL1, ERL2 and OCL is undertaken using synthetic signals generated in Matlab, dynamic power system simulations in DIgSILENT, signals generated within a controlled laboratory environment, and real substation data. A new Phasor Data Concentrator (PDC) is developed, in order to gain full control over the Phasor Measurement Unit (PMU) data flow and reduce data processing delays. The new PDC uses a multiplexing technique to manage threads and significantly reduce latency. The data processing delays obtained for the new PDC are much lower than values reported in the available literature and values obtained during laboratory testing of another freely available PDC technology. The new improved load model and PDC are integrated into a real-time platform compatible to the Java EE7 enterprise standards. Benchmark tests show a high level of scalability and reliability for the resulting real-time load modelling platform.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:309834
Created by:
Nechifor, Alexandru
Created:
28th June, 2017, 16:07:08
Last modified by:
Nechifor, Alexandru
Last modified:
4th January, 2021, 11:26:26

Can we help?

The library chat service will be available from 11am-3pm Monday to Friday (excluding Bank Holidays). You can also email your enquiry to us.