fix up some typos/errors

output/thesis.tex

@@ -327,7 +327,7 @@
 
         \normalsize
         UNSW Sydney, Australia\\
-        April 2, 2024
+        April 9, 2024
 
         % Except where otherwise noted, content in this thesis is licensed under a Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright 2015,Tom Pollard.
 
@@ -804,7 +804,7 @@ \section{Research framework}\label{sec:intro-research_framework}}
 \end{enumerate}
 
 The links between the research question, the research objectives and the
-research questions are shown in Figure~\ref{fig:research_framework} and
+research methods are shown in Figure~\ref{fig:research_framework} and
 are discussed in greater detail in Chapter \ref{sec:research_framework}.
 
 \hypertarget{contributions}{%
@@ -888,8 +888,9 @@ \section{Structure of the thesis}\label{structure-of-the-thesis}}
 
 \textbf{Chapter \ref{sec:lit_review}} provides relevant context on power
 systems and power system operation, and an overview of the literature on
-the challenges with and the desirable outcomes of designing operational
-practices in electricity markets with growing penetrations of VRE.
+the desirable outcomes of and challenges associated with designing
+operational practices in electricity markets with growing penetrations
+of VRE.
 
 \textbf{Chapter \ref{sec:research_framework}} outlines the motivating
 research question, the research objectives and research methods of this
@@ -930,11 +931,11 @@ \section{Structure of the thesis}\label{structure-of-the-thesis}}
 market participation to date. Then, in a case study of the NEM, I
 examine errors in the NEM's centralised price forecasts, propose a
 hypothesis to explain increasing divergence and the occurrence of price
-swings in these forecasts, and subsequently use the same centralised
-price forecasts to schedule a variety of battery energy storage systems
-for wholesale energy market arbitrage to assess the impact of imperfect
-foresight on arbitrage revenues. I conclude by discussing changes to
-market participant scheduling and market design that could maximise the
+swings in these forecasts, and subsequently use these same forecasts to
+schedule a variety of battery energy storage systems for wholesale
+energy market arbitrage to assess the impact of imperfect foresight on
+arbitrage revenues. I conclude by discussing changes to market
+participant scheduling and market design that could maximise the
 balancing value of resources such as battery energy storage systems.
 \textbf{Appendix \ref{sec:appendix-milps}} presents the mixed-integer
 linear program formulations used in the storage modelling in Chapter
@@ -1006,7 +1007,7 @@ \section{Power systems}\label{sec:lit_review-power_systems}}
 alternating current (AC) power either through a direct electromagnetic
 connection or, if they are inverter-based resources (IBRs)\footnote{These
   include VRE IBRs (solar PV and Type III and Type IV wind turbines),
-  battery energy storage systems and voltage sourcec converter high
+  battery energy storage systems and voltage source converter high
   voltage direct current (HVDC) transmission lines
   (\protect\hyperlink{ref-achillesIntegratingInverterBasedResources2017}{Achilles
   et al., 2017};
@@ -1108,20 +1109,19 @@ \section{Power system operations}\label{sec:lit_review-operations}}
 \hypertarget{fig:power_system_timeframes}{%
 \centering
 \includegraphics[width=1.3\textwidth,height=\textheight]{source/figures/power_system_timeframes.pdf}
-\caption[High-level overview of power system concepts, phenomena and
+\caption[High-level overview of power system concepts, phenomena, and
 processes, services and markets relevant within operational
 timeframes]{A high-level overview of power system concepts, phenomena
-and the processes, services and markets relevant within operational
-timeframes (bounded by the red dashed box). All non-faded text in the
-bottom section indicates a process, service and/or market
-(i.e.~operational practice) related to active power balancing. All bold
-red text in the bottom section indicates a process, service and/or
-market related to active power balancing that is discussed in detail in
-this thesis. Processes, services and markets bounded by the blue dashed
-box occur within scheduling timeframes. Phenomena and stability
-categories, and their timeframes of relevance, are based on those
-discussed in Machowski et al.
-(\protect\hyperlink{ref-machowskiPowerSystemDynamics2020}{2020}),
+and practices relevant within operational timeframes (bounded by the red
+dashed box). All non-faded text in the bottom section indicates a
+process, service and/or market (i.e.~operational practice) related to
+active power balancing. All bold red text in the bottom section
+indicates a process, service and/or market related to active power
+balancing that is discussed in detail in this thesis. Processes,
+services and markets bounded by the blue dashed box occur within
+scheduling timeframes. Phenomena and stability categories, and their
+timeframes of relevance, are based on those discussed in Machowski et
+al. (\protect\hyperlink{ref-machowskiPowerSystemDynamics2020}{2020}),
 Hatziargyriou et al.
 (\protect\hyperlink{ref-hatziargyriouDefinitionClassificationPower2021}{2021})
 and Matevosyan et al.
@@ -1373,8 +1373,8 @@ \subsubsection{Threats to active power
 \paragraph{Power system uncertainty}\label{power-system-uncertainty}}
 
 Power system uncertainty refers to \emph{unexpected} changes to active
-power supply and/or demand. Source of uncertainty include demand and VRE
-generation forecast errors, and singular or widespread outage events
+power supply and/or demand. Sources of uncertainty include demand and
+VRE generation forecast errors, and singular or widespread outage events
 triggered by the weather or unexpected system responses and interactions
 (\protect\hyperlink{ref-australianenergymarketoperatorRenewableIntegrationStudy2020}{Australian
 Energy Market Operator, 2020a};
@@ -1389,16 +1389,15 @@ \subsection{Operational
 
 Though governance and operational arrangements vary from jurisdiction to
 jurisdiction, the powers, responsibilities and degree of ring-fencing
-imposed upon the SO are largely dictated by the operational paradigm of
-the control area
+imposed upon the SO are largely dictated by one of two possible
+operational paradigms for a control area
 (\protect\hyperlink{ref-chawlaGlobalTrendsElectricity2013}{Chawla and
-Pollitt, 2013}). Below, I discuss the two possible operational
-paradigms: where the SO is a \textbf{vertically-integrated utility}, and
-where the SO is, at the very least, responsible for operating a
-transmission system that forms the physical basis of a \textbf{wholesale
-electricity market}. In both cases, it is the SO that is ultimately
-responsible for ensuring that the transmission network in their control
-area is operated in a secure and reliable manner
+Pollitt, 2013}): where the SO is a \textbf{vertically-integrated
+utility}, and where the SO is, at the very least, responsible for
+operating a transmission system that forms the physical basis of a
+\textbf{wholesale electricity market}. In both cases, it is the SO that
+is ultimately responsible for ensuring that the transmission network in
+their control area is operated in a secure and reliable manner
 (\protect\hyperlink{ref-roquesMarketDesignGeneration2008}{Roques,
 2008}).
 
@@ -1476,7 +1475,7 @@ \subsubsection{Wholesale electricity
   Ahlqvist et al.
   (\protect\hyperlink{ref-ahlqvistSurveyComparingCentralized2022}{2022}),
   who focus on the level of centralisation in day-ahead timeframes. They
-  categorise the Australian NEM as a decentralised market as
+  categorise the Australian NEM as a decentralised market because market
   participants manage unit commitment. However, the SO still produces
   resource-specific production and consumption targets through a central
   dispatch process that also clears the real-time market. As such, I
@@ -4122,14 +4121,14 @@ \subsection{Performance and efficiency issues of regulation
 \centering
 \includegraphics{source/figures/regional_SCADA_frequencies.eps}
 \caption[System frequency (as registered by phasor measurement units and
-AEMO\textquotesingle s AGC) during the power system event on the
-25\^{}th\^{} of August, 2018]{Regional phasor measurement unit frequency
-data and AGC reference frequency data from AEMO's NSW control centre
-(obtained using NEMOSIS
-(\protect\hyperlink{ref-gormanNEMOSISNEMOpen2018}{Gorman et al., 2018}))
-during the power system event on the 25\textsuperscript{th} of August,
-2018. Note that the AGC reference frequency deviates in the opposite
-direction to local frequency in QLD and SA.}\label{fig:regional_freq}
+AEMO\textquotesingle s AGC) during the power system event on the 25th of
+August, 2018]{Regional phasor measurement unit frequency data and AGC
+reference frequency data from AEMO's NSW control centre (obtained using
+NEMOSIS (\protect\hyperlink{ref-gormanNEMOSISNEMOpen2018}{Gorman et al.,
+2018})) during the power system event on the 25\textsuperscript{th} of
+August, 2018. Note that the AGC reference frequency deviates in the
+opposite direction to local frequency in QLD and
+SA.}\label{fig:regional_freq}
 }
 \end{figure}
 
@@ -7962,7 +7961,7 @@ \section{Options for improving scheduling}\label{sec:info-discussion}}
 \end{itemize}
 
 \hypertarget{sec:info-conclusion}{%
-\section{Conclusion and policy implications}\label{sec:info-conclusion}}
+\section{Conclusion}\label{sec:info-conclusion}}
 
 With growing deployments of flexible yet potentially energy-constrained
 VRE and ESRs and increasingly active demand-side resources,

source/09_intro.md

@@ -28,15 +28,15 @@ I focus on three aspects of this question that are encompassed by the following
 
 2. *To better understand how balancing flexibility capabilities in scheduling timeframes are changing during energy transition, and how these changes might impact the suitability and design of more decentralised operational balancing practices.*
 
-3. *To explore how more decentralised operational balancing practices can be configured to maximise the deployability of  balancing flexibility in scheduling timeframes.*
+3. *To explore how more decentralised operational balancing practices can be configured to maximise the deployability of balancing flexibility in scheduling timeframes.*
 
 I attempt to achieve these objectives through the following three **research methods**:
 
 1. Review of academic and industry literature on the design of operational balancing practices from the Australian NEM and other jurisdictions.
 2. Analysis of system and market data from the Australian NEM to provide empirical evidence for techno-economic modelling assumptions and to support the discussion of policy options.
 3. Techno-economic (market) optimisation modelling. This includes the modelling of market regions of the NEM, and of market participation schedules for battery energy storage systems engaged in energy arbitrage.
 
-The links between the research question, the research objectives and the research questions are shown in [@fig:research_framework] and are discussed in greater detail in [Chapter @sec:research_framework].
+The links between the research question, the research objectives and the research methods are shown in [@fig:research_framework] and are discussed in greater detail in [Chapter @sec:research_framework].
 
 ## Contributions
 
@@ -64,15 +64,15 @@ Additional contributions related to this thesis include:
 
 This thesis consists of 7 chapters and 4 appendices.
 
-**[Chapter @sec:lit_review]** provides relevant context on power systems and power system operation, and an overview of the literature on the challenges with and the desirable outcomes of designing operational practices in electricity markets with growing penetrations of VRE.
+**[Chapter @sec:lit_review]** provides relevant context on power systems and power system operation, and an overview of the literature on the desirable outcomes of and challenges associated with designing operational practices in electricity markets with growing penetrations of VRE.
 
 **[Chapter @sec:research_framework]** outlines the motivating research question, the research objectives and research methods of this thesis in detail.
 
 **[Chapter @sec:fcs]** considers the question of how frequency control arrangements should be designed with growing penetrations of VRE. In this chapter, I first provide an overview of typical frequency control arrangements, with a focus on restructured electricity industries in North America and Europe, and the main challenges faced in their design. I then describe the NEM's frequency control arrangements and the specific challenges posed by increasing penetrations of VRE. Based on an analysis of the performance of the NEM's frequency control arrangements in responding to these challenges, I conclude this chapter by offering four key insights to policy-makers.
 
 **[Chapter @sec:reserves]** focuses on understanding balancing flexibility *capabilities* available in scheduling timeframes as VRE and storage become a larger part of system resource mixes. In this chapter, I first provide an overview of how balancing flexibility is enabled and procured in the NEM before describing a methodology to quantify available reserves and footroom across deployment horizons for various resource types. I then quantify the available reserves and footroom in two regions of the NEM for existing resource mixes in 2020 and potential resources mixes in 2025, with two scenarios for the latter. From the findings of this case study, I explore the role of reserve products in securing balancing flexibility. **[Appendix @sec:appendix-reserves_assumptions]** outlines the sources for key input data and assumptions, and provides further details regarding how these data were used in the analysis.
 
-**[Chapter @sec:info]** explores how future pricing information and market participant operational strategies affect the *deployability* of balancing flexibility from energy storage resources. In this chapter, I first summarise market information, participation and clearing processes in the NEM in addition to providing context on grid-scale energy storage resource deployment, operation and market participation to date. Then, in a case study of the NEM, I examine errors in the NEM's centralised price forecasts, propose a hypothesis to explain increasing divergence and the occurrence of price swings in these forecasts, and subsequently use the same centralised price forecasts to schedule a variety of battery energy storage systems for wholesale energy market arbitrage to assess the impact of imperfect foresight on arbitrage revenues. I conclude by discussing changes to market participant scheduling and market design that could maximise the balancing value of resources such as battery energy storage systems. **[Appendix @sec:appendix-milps]** presents the mixed-integer linear program formulations used in the storage modelling in [Chapter @sec:info], and **[Appendix @sec:appendix-discounting]** describes the methodology used to model a storage scheduler discounting price forecasts (one of the formulations used in the storage modelling in [Chapter @sec:info] and described in [Appendix @sec:appendix-milps]).
+**[Chapter @sec:info]** explores how future pricing information and market participant operational strategies affect the *deployability* of balancing flexibility from energy storage resources. In this chapter, I first summarise market information, participation and clearing processes in the NEM in addition to providing context on grid-scale energy storage resource deployment, operation and market participation to date. Then, in a case study of the NEM, I examine errors in the NEM's centralised price forecasts, propose a hypothesis to explain increasing divergence and the occurrence of price swings in these forecasts, and subsequently use these same forecasts to schedule a variety of battery energy storage systems for wholesale energy market arbitrage to assess the impact of imperfect foresight on arbitrage revenues. I conclude by discussing changes to market participant scheduling and market design that could maximise the balancing value of resources such as battery energy storage systems. **[Appendix @sec:appendix-milps]** presents the mixed-integer linear program formulations used in the storage modelling in [Chapter @sec:info], and **[Appendix @sec:appendix-discounting]** describes the methodology used to model a storage scheduler discounting price forecasts (one of the formulations used in the storage modelling in [Chapter @sec:info] and described in [Appendix @sec:appendix-milps]).
 
 **[Chapter @sec:conclusion]** concludes the thesis. In this chapter, I summarise the contributions of this thesis and highlight avenues for further work.