Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.806088
Title: Synchrophasor-based predictive control considering optimal phasor measurement unit placements methods
Author: Okekunle, Dahunsi John
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2020
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Abstract:
A blackout is the total collapse of an electric power grid, due to the inability to balance load demand and power generation. Blackouts generally develop from a series of unattended voltage stability problems, stemming from a combination of human and operational errors, and may have fatal consequences. The report on the blackout incident of August 14 2003, which affected parts of the United States and Canada, particularly emphasised the need for improved wide area monitoring of the grid. In the United Kingdom, the recent blackout of August 9 2019 has reinforced the need for increased grid visibility and data recording. These have led to an ever-increasing interest in a family of measurement devices known as Wide Area Monitoring Systems (WAMS). The most popular device in this family is the Phasor Measurement Unit (PMU), which report voltage and current phasors at rates up to 60 samples/second. PMUs may be used to monitor all or part of the grid to prevent future blackouts with timely control actions. The goal is to ’See it fast: Keep it calm’. Wide-area monitoring enhances the possibility of visualizing the electric grid as a single system. This has led to the extension of the application of WAMS from mainly monitoring to wide-area control in relatively recent research efforts. This work explores how predictive control technique may be used to automate the control of power systems voltages at secondary level using an array of synchrophasors. The intuition is to develop a model-free (or synchrophasor-based) control algorithm, which reduces, as much as possible, the need for human interventions in the mitigation of voltage problems, and is fast enough to be applied online in real-time. Although model-based techniques can be applied online, they may not be fast enough for real-time applications. In addition, this method may depend on components’ parameters, which may not be available in practice. The work is split into two parts. First, novel WAMS deployment algorithms —using multi-variable, multi-objective optimization set-ups, which return optimal placement solutions —are presented. Formulations are described for multi-stage deployments given a limited budget and for application-focused cases. Practical issues which may develop are anticipated and addressed. The formulations were shown to return optimal solutions with qualitative placement specifications. In the second part, methods of realizing models from input-output relationships are developed and described. The first involved a method numerical derivatives based on data that are sampled at PMU rates. This may be seen as a viable alternative to the use of trajectory sensitivity, especially for real-time control design. In the second, subspace algorithm are used to realise models. The process is comprehensively described for secondary voltage regulation in normal and emergency situations. The approach is demonstrated on a number of IEEE test cases and the controller’s performance were found to be satisfactory for non-viable voltage regulations. This research work is particularly relevant in a number of ways. Chief among these is that voltage control problems may be handled in real-time without a knowledge of the model parameters. The model-free approach particularly desired since increasing integration of renewable energy sources means that the electric grid is becoming increasingly complex. Another is that the placement algorithms describe all various practical issues around the measurement-based design, which utilities may found useful, especially when they wish to address budget limitation and device compatibility issues.
Supervisor: Kiprakis, Aristides ; Shek, Jonathan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.806088  DOI:
Keywords: PMU ; MPC ; control ; monitoring ; optimal placements
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