final sync

latex/presentation.tex

@@ -0,0 +1,191 @@
+\documentclass{beamer}
+
+\setbeamertemplate{navigation symbols}{}
+
+\usetheme{Antibes}
+\usecolortheme{seahorse}
+
+\usepackage[czech]{babel}
+\usepackage{csquotes}
+\usepackage{minted}
+\usepackage[backend=biber]{biblatex}
+
+\title[Expansion of electricity access in Kenya thanks
+to renewable energy sources] % (optional, use only with long paper titles)
+{Expansion of electricity access in Kenya thanks
+to renewable energy sources}
+
+%\subtitle{} % (optional)
+
+\author[Štěpán Beran] % (optional, use only with lots of authors)
+{Štěpán Beran}
+% - Use the \inst{?} command only if the authors have different
+%   affiliation.
+\institute{Faculty of Information Technology CTU in Prague}
+\date % (optional)
+{9. 12. 2024}
+
+\subject{BI-SEP}
+
+% If you wish to uncover everything in a step-wise fashion, uncomment
+% the following command: 
+%\beamerdefaultoverlayspecification{<+->}
+
+
+\begin{document}
+
+\begin{frame}[plain]
+  \titlepage
+\end{frame}
+
+
+\section{Introduction}
+\subsection{Motivation}
+
+\begin{frame}
+    \frametitle{Motivation}
+    Electricity consumption nearly perfectly correlates with GDP.
+    Emerging economies often rely on fossil fuels as their main energy source which brings known risks and problems:
+    \begin{itemize}
+        \item reliance on imports from authoritarian regimes \footnote{see history of oil cartels or Russian invasion of Ukraine}
+        \item exacerbation of extreme weather events caused by climate change
+    \end{itemize}
+\end{frame}
+
+\begin{frame}
+    \frametitle{Motivation}
+    \begin{itemize}
+        \item Oil crisis' of 1970s-80s had devastating consequences.
+        \item The US "shale revolution"~helped satisfy fossil fuel dependent economies and keep oil cheap.
+        \item Low incentive to shift => energy inefficient compared to western Europe.
+    \end{itemize}
+    \begin{figure}[ht!]
+        \includegraphics[width=\textwidth, height=4.8cm, keepaspectratio]{fig/international-efficiency-2022-map.jpg}
+        \label{fig:us-oil}
+    \end{figure}
+\end{frame}
+
+\begin{frame}
+    \frametitle{Motivation}
+    Princeton's Geophysical Fluid Dynamics Laboratory\footnote{\url{https://www.gfdl.noaa.gov/global-warming-and-hurricanes/}} explains that by the late 21st century, assuming anthropogenic global warming of approx. 2°C:
+    \begin{itemize}
+        \item{\textbf{Very Intense Hurricanes}} The global proportion of tropical cyclones/hurricanes that reach very intense (Category 4 and 5) levels is projected to increase (medium to high confidence)
+        \item{\textbf{Overall Hurricane Intensity}} Tropical cyclone intensities globally are projected to increase (medium to high confidence) on average.
+        \item\textbf{Sea Level Rise} Human activities have very likely been the dominant cause of sea level rise since at least 1971 which in turn exacerbates coastal inundation risks associated with tropical cyclones.
+    \end{itemize}
+\end{frame}
+
+\begin{frame}
+    \frametitle{Motivation}
+    Can economies grow without expansion of their reliance?
+    \begin{itemize}
+        \pause
+        \item{Of course they can!} Kenya
+        \pause
+        \item{But also} Austria, Bulgaria, Czechia, Denmark, Finland, France, Germany, Greece, Italy, Kenya, the Netherlands, Norway, Poland, Portugal, Romania, Spain and the United Kingdom \footnote{All economies, which have already surpassed their fossil peak.}
+        \pause 
+        \item{Some can not -} Canada, China, Chile, India, Israel, Ukraine, the United States and Peru
+    \end{itemize}
+\end{frame}
+
+\subsection{Hypothesis}
+\begin{frame}
+    \frametitle{Hypothesis}
+    Hypothesis:
+    \begin{itemize}
+        \item{\(H_0\)} - There is no positive correlation between share of renewable electricity and access to electricity in Kenya.
+        \item{\(H_1\)} - There is correlation between share of renewable electricity and access to electricity in Kenya.
+    \end{itemize}
+    Verification criteria:
+    \begin{itemize}
+        \item{\bf{R-squared} \(R^2\)} - \(R^2 \ge 0.7\)
+        \item{\bf{Correlation coefficient} \(r\)} - \(\ r \ge 0.7 \)
+        \item{\bf{p-value}} - \( \textrm{p-value} \le 0.05 \)
+    \end{itemize}
+\end{frame}
+
+\section{Electrification in Sub-Saharan Africa}
+\subsection{History of investments in electrification}
+\begin{frame}
+    \frametitle{History of investments in electrification}
+    Major time periods in investments into electrification in Sub-Saharan Africa 
+    \begin{itemize}
+        \item{\textbf{1980s}} - Stop migration from rural to urban areas
+        \item{\textbf{late 1980s - 90s}} - High costs and low impact
+        \item{\textbf{90s - now}} - Necessary condition to fight poverty
+    \end{itemize}
+\end{frame}
+
+\subsection{Problems with electrification}
+\begin{frame}
+    \frametitle{Problems with electrification}
+    Electrification of rural areas doesn't come without it's own set of problems such as:
+    \begin{itemize}
+        \item{\textbf{High upfront cost}} - Connecting to grid as well as off-grid\footnote{Can be chaper than connecting to the grid. Discussed in the paper.}
+        \item{\textbf{Lack of productive use}} - Mainly used for home lighting, TVs, etc. Not used enough in agriculture, crafts and services.
+        \item{\textbf{Lack of known impacts}} - Funding is based on supposed impacts with very little empirical evidence.
+    \end{itemize}
+\end{frame}
+
+\subsection{Effects found in other countries}
+\begin{frame}
+    \frametitle{Findings from electrification in India}
+    \begin{itemize}
+        \item {Increased time spent studying}
+        \item {Increased school enrollment}
+        \item {Increased labor supply of both men and women}
+        \item {Increased per capita household income and expenditure}
+    \end{itemize}
+    However most of those benefits accure to wealthier households, while poorer households use electricity to a limited extent.
+\end{frame}
+
+\subsection{Optimal strategy for electrification in Kenya}
+\begin{frame}
+    \frametitle{Optimal strategy for electrification in Kenya}
+    Extensive spatial mapping of existing energy infrastructure in Kenya found that:
+    \begin{itemize}
+        \item{Renewable energy plays a pivotal role in decentralized energy systems allowing energy access in rural areas.}
+        \item{Solar power should dominate remote areas separated more than 10km form the grid.}
+        \item{Solar generation could make electricity available to 5.98 million people.}
+        \item{Hybrid mini-grids could electrify additional 390 thousand people.}
+        \item{Diesel generators could cover 390 thousand people.\footnote{Maintenance \& operational costs are significant for a long term solution.}}
+        \item{It is cheaper to invest in standalone solar solution for "under-grid"~population.}
+    \end{itemize}
+\end{frame}
+
+\section{Conclusions}
+\begin{frame}
+    \frametitle{Findings}
+    \begin{figure}[ht!]
+        \includegraphics[width=\textwidth]{fig/regression.png}
+        \caption{Scatter plot with regression line showing the relationship between electricity access and the share of renewable electricity in Kenya.}
+        \label{fig:regression}
+    \end{figure}
+\end{frame}
+
+\begin{frame}
+    \frametitle{Findings}
+    \begin{itemize}
+        \item{\bf{R-squared:}} The coefficient of determination for the regression model is \(R^2 = 0.704\), indicating a strong relationship between the variables.
+        \item{\bf{Correlation Coefficients:}} 
+        \begin{itemize}
+            \item{\bf{Electricity access and share of renewables:}} \(r = 0.834\), showing a strong positive correlation.
+            \item{\bf{Electricity access and GDP growth:}} \(r = 0.048\), indicating a weak correlation.
+            \item{\bf{GDP growth and share of renewables:}} \(r = 0.125\), also a weak correlation.
+        \end{itemize}
+        \item{\bf{Electricity Access Coefficient:}} The regression coefficient is 0.561, statistically significant with \(\textrm{p-value} < 0.0001\).
+        \item{\bf{GDP Growth Coefficient:}} The regression coefficient is 0.177, not statistically significant with \(\textrm{p-value} = 0.505\).
+    \end{itemize}
+\end{frame}
+
+\begin{frame}
+    \frametitle{Conclusions}
+    While the expansion of renewables correlated with electricity acces in Kenya, there still are problems with expansion of electricity access in Kenya, however
+    \begin{itemize}
+        \item the absence of fossil fuels is not one of them,
+        \item they relate to economically inefficient use and
+        \item further research and revision of government plans is needed.
+    \end{itemize}
+\end{frame}
+\end{document}
+

latex/report.tex

@@ -86,7 +86,7 @@ This presents a a developmental challenge. How can electricity access be expande
 \subsection{Effects of electricity access in Kenya}
 Kenneth Lee discussed the problems of microgrids as a potetntial solution to such problem in rural Kenya with pay-as-you-go business model allowing consumers to buy products on credit. However, they identified that the main problem of rural Kenyan electricity access was not the remoteness of villages, but high cost of installation of low-voltage distribution transformer, which cost around \$398~USD, while the annual per-capita income was bellow \$1000~USD in most rural households. Vast majority of the population without electricity access in Kenya was therefore not off-grid but "under-grid" per se and installing solar microgrids is not a viable long term solution. In their survey of new installation, they did not see significant impacts in the short term with no clear indication as to why. And included an important note from Khandker et al. about rural electrification in India \cite{khandker-benefits-of-rural-el}, the gains from rural electrification could be much greater for wealthier households which could exacerbate economic inequalities.
 
-\subsection{Renewable energy consumption and economic growth accross countries}
+\subsection{Renewable energy consumption and economic growth across countries}
 In Bhattacharya et al. study about the effect of renewable energy consumption on economic growth \cite{renewables-and-economic-growth}, they studied data of the top 38 countries in the Renewable Energy Country Attractiveness Index developed by Ernst \& Young Global Limited from 1991 until 2012. They found that those countries could be separated into three major groups which will be discussed in more detail later.
 \begin{itemize}
     \item{\textbf{Positive impact:}} Austria, Bulgaria, Canada, Chile, China, the Czech Republic, Denmark, Finland, France, Germany, Greece, Italy, Kenya, Republic of Korea, Morocco, the Netherlands, Norway, Peru, Poland, Portugal, Romania, Spain and the United Kingdom
@@ -201,11 +201,11 @@ The following figure \ref{fig:regression} shows significant correlation between
 The author concludes that there is a strong positive correlation between the share of renewable energy and access to electricity. This finding supports hypothesis \(H_1\) which proposed the existence of such a correlation.
 Data analysis revealed that the correlation coefficient between access to electricity and renewable energy share is 0.834, indicating a strong positive correlation. The regression coefficient for access to electricity is 0.561 and is statistically significant with a p-value of less than 0.0001. 
 
-The paper further indicates that there is a weak correlation between access to electricity and GDP growth (correlation coefficient of 0.048) and also a weak correlation between GDP growth and the share of renewable energy (correlation coefficient of 0.125). The regression coefficient for GDP growth is 0.177 and is not statistically significant with a p-value of 0.505.
+The paper further indicates that there is a weak correlation between access to electricity and GDP growth (correlation coefficient of 0.048) and also a weak correlation between GDP growth and the share of renewable energy (correlation coefficient of 0.125). The regression coefficient for GDP growth is 0.177 and is not statistically significant with a p-value of 0.505. Confirming the previous findings in the theoretical part, that the problem with electricity access is it's productive use, or lack thereof.
 
-Thus, the conclusion of the paper suggests that the share of renewable energy plays a significant role in expanding access to electricity in Kenya.
+Thus, the conclusion of the paper suggests that the share of renewable energy plays a significant role in expanding access to electricity in Kenya. While access to electricity represents a crucial initial step, understanding the underlying barriers to productive use remains a critical area for further research.
 
-Thanks to it's current low reliance on fossil fuels, Kenya is expected to benefit from existing and expanding cheap renewable energy as its source of growth.
+Thanks to it's current low reliance on fossil fuels, Kenya is expected to benefit from existing and expanding cheap renewable energy as its source of growth in it's productive areas.
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