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\title{\vspace{-1.7cm}
 The cost-benefit of transmission expansion in a sector-coupled,
  highly-renewable European energy scenario
}
%\subtitle{---}
\author{
  Jonas H\"orsch, Veit Hagenmeyer, {\bf Tom Brown}; \href{mailto:tom.brown@kit.edu}{tom.brown@kit.edu}, \url{https://nworbmot.org/} \\
  \emph{Karlsruhe Institute of Technology (KIT), Institute for Automation and Applied Informatics (IAI)}}

%\institute{}

\date{\vspace{0.3cm}2nd International Symposium on Energy System Optimization, Karlsruhe, 11th October 2018}


\titlegraphic{%
  \vspace{5.8cm}
  % left bottom right top
  \includegraphics[trim=0 0cm 0 0cm,height=1.8cm,clip=true]{kit.png}
  \hspace{5cm}
\includegraphics[trim=0 0cm 0 0cm,height=1.8cm,clip=true]{helmholtz.png}
}

\begin{document}

\maketitle


\begin{frame}

  \frametitle{Table of Contents}
  \setbeamertemplate{section in toc}[sections numbered]
  \tableofcontents[hideallsubsections]
\end{frame}

\section{The Challenge}

\begin{frame}
  \frametitle{The Global Carbon Dioxide Challenge: Net-Zero Emissions by 2050}

  \begin{columns}[T]
\begin{column}{7.5cm}

  \includegraphics[width=8cm]{ipcc-sr15}


\end{column}
\begin{column}{6cm}
  \vspace{.8cm}
\begin{itemize}
\item   Line widths represent 5-95th percentile of scenarios
\item Level of use of negative emission technologies (NET) depends on rate of progress
\item 2C target without NET also needs
  rapid fall by 2050
\item Common theme: \alert{net-zero by 2050}
\end{itemize}
\end{column}
  \end{columns}

    \source{\href{http://ipcc.ch/report/sr15/}{IPCC SR15 on 1.5C, 2018}}
\end{frame}


\begin{frame}
  \frametitle{It's not just about electricity demand...}

  %GHG are 4~Gt, CO2 is only 3.188~Gt
  EU28 \co2{} emissions in 2015 (total 3.2~Gt \co2, 8\% of global):

  \centering
    % left bottom right top
  \includegraphics[trim=0 0.7cm 0 0.5cm,width=12cm]{EU28-emissions_pie-2015-CO2.pdf}

%  ...\alert{but} wind and solar will dominate primary energy in all sectors, so electrification is critical.

  \source{Brown, data from \href{https://www.eea.europa.eu/data-and-maps/data/national-emissions-reported-to-the-unfccc-and-to-the-eu-greenhouse-gas-monitoring-mechanism-13}{EEA}}
\end{frame}



\begin{frame}
  \frametitle{...but electrification of other sectors is critical for decarbonisation}

\alert{Electrification is essential} to decarbonise sectors such as
transport and heating.

Some scenarios show a \alert{doubling or more of electricity demand}.

  \vspace{.7cm}

  \begin{columns}[T]
\begin{column}{6cm}
  \includegraphics[trim=0 0cm 0 0cm,width=6cm,clip=true]{tesla.jpg}
\end{column}
\begin{column}{6cm}

  \includegraphics[trim=0 0cm 0 0cm,width=6cm,clip=true]{640px-Heat_Pump.jpg}
\end{column}
\end{columns}



\source{Tesla; heat pump: \href{https://commons.wikimedia.org/w/index.php?curid=10795550}{Kristoferb at English Wikipedia}}

\end{frame}






\begin{frame}[fragile]
  \frametitle{Take account of social and political constraints}



\begin{columns}[T]

  \begin{column}{5cm}


\centering
\includegraphics[width=5cm]{nein_zur_monstertrasse}

  \end{column}


  \begin{column}{6.7cm}

    \vspace{1cm}

    However, there are \alert{social and political constraints},
    particularly for transmission grid and onshore wind
    development. Fortunately:

    \begin{itemize}
    \item Other sectors can offer \alert{flexibility} back to the grid (e.g. battery electric vehicles, power-to-gas, thermal storage)
    \item \alert{New technologies} can minimise the landscape impact of transmission
  \end{itemize}

  \end{column}

\end{columns}

\end{frame}



\begin{frame}
  \frametitle{Sectoral coupling with spatial resolution, European scope}

  \alert{The Problem}: Most cross-sectoral studies are at the
  country level, but don't have the spatial resolution to resolve
  transmission grid bottlenecks or spatio-temporal resolution for renewables

  \vspace{.7cm}

  \alert{Our Goal}: Model full energy system over Europe with enough
  resolution to understand the need and cost-benefits of transmission
  reinforcement


  \vspace{.7cm}

  \alert{Today}: Some preliminary results

\end{frame}


\section{Variability of Renewables, Demand and Flexibility}


\begin{frame}
  \frametitle{Daily variations: challenges and solutions}

  \begin{columns}[T]
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{DE-solar-day.pdf}
      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{DE-transport-day.pdf}
    \end{column}
    \begin{column}{4cm}
      Daily variations in supply and demand can be balanced by
      \begin{itemize}
      \item \alert{short-term storage} (e.g. batteries, pumped-hydro, small thermal storage)
      \item \alert{demand-side management} (e.g. battery electric vehicles,
        industry)
      \item \alert{east-west grids over multiple time zones}
      \end{itemize}

    \end{column}
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{pumped-storage-diagram-best1.jpg}

      \vspace{.5cm}

      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{tesla-charging.jpg}
    \end{column}
  \end{columns}

\end{frame}




\begin{frame}
  \frametitle{Synoptic variations: challenges and solutions}

  \begin{columns}[T]
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=5.3cm,clip=true]{DE-wind-month.pdf}

      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{2015-11-30-0300.png}

    \end{column}
    \begin{column}{4cm}
      \href{https://www.youtube.com/watch?v=ttfuEnMz2UM}{Synoptic variations} in supply and demand can be balanced by
      \begin{itemize}
      \item \alert{medium-term storage} (e.g. compressed air, chemically with hydrogen or methane, thermally, hydro reservoirs)
      \item \alert{continent-wide grids}
      \end{itemize}

    \end{column}
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=4.5cm,clip=true]{1024px-Gasometer_in_East_London.jpg}

      \includegraphics[trim=0 0cm 0 0cm,width=4.5cm,clip=true]{europe_map.pdf}
    \end{column}
  \end{columns}

\end{frame}




\begin{frame}
  \frametitle{Seasonal variations: challenges and solutions}

  \begin{columns}[T]
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{DE-wind-solar-year.pdf}
      \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{DE-heat-year.pdf}
    \end{column}
    \begin{column}{4cm}
      Seasonal variations in supply and demand can be balanced by
      \begin{itemize}
      \item \alert{long-term storage} (e.g. chemically with hydrogen or methane storage, long-term thermal energy storage, hydro reservoirs)
      \item \alert{north-south grids over multiple latitudes}
      \end{itemize}

    \end{column}
    \begin{column}{5cm}
      \includegraphics[trim=0 0cm 0 0cm,width=4.7cm,clip=true]{1024px-Gasometer_in_East_London.jpg}

      \vspace{.2cm}

      \includegraphics[trim=0 0cm 0 0cm,width=4.7cm,clip=true]{pit-zoom.png}
    \end{column}
  \end{columns}

\end{frame}



\section{The model}


\begin{frame}[fragile]
  \frametitle{Linear optimisation of annual system costs}

Find the long-term cost-optimal energy system, including investments and short-term costs:
\begin{equation*}
  \textrm{Minimise} \left(\parbox{6em}{\centering\alert{Yearly\\system costs}}\right) = \sum_n \left(\parbox{6em}{\centering\alert{Annualised capital costs}}\right) + \sum_{n,t} \left(\parbox{5em}{\centering\alert{Marginal costs}}\right)
\end{equation*}
subject to
\begin{itemize}
\item meeting \alert{energy demand} at each node $n$ (e.g. region) and time $t$ (e.g. hour of year)
\item wind, solar, hydro (variable renewables) \alert{availability time series} $\forall\: n,t$
\item \alert{transmission constraints} between nodes, \alert{linearised power flow}
\item (installed capacity) $\leq$ (\alert{geographical potentials} for renewables)
\item \alert{CO${}_2$ constraint} (e.g. 95\% reduction compared to 1990)
\end{itemize}

In short: mostly-greenfield investment optimisation, multi-period with linear power flow.

Optimise transmission, generation and storage \alert{jointly}, since they're strongly interacting.
\end{frame}



\begin{frame}
  \frametitle{Notable constraints 1/2: Linear power flow}

  The linearised \alert{power flows} $f_\ell$ for each line $\ell \in
  \{1,\dots L\}$ in an AC network are determined by the nodal power
  injections $p_i$, the \alert{reactances} $x_\ell$ of the transmission
  lines by enforcing Kirchhoff's Current Law (energy conservation),
  then Voltage Law (angle differences around closed cycles)
  \alert{directly on cycles} $C_{\ell c}$ rather than using auxilliary
  angle variables $\theta_i$:
  \begin{equation*}
    \sum_{\ell} C_{\ell c} K_{i\ell} \theta_i =  \sum_{\ell} C_{\ell c} x_\ell f_\ell = 0
  \end{equation*}
  This solves faster and more stably than the angle formulation using commercial LP solvers.

    Transmission flows cannot exceed the capacities $\bar{P}_\ell$ of the
    transmission lines (with buffer $s_{N-1} = 0.7$ to approximate
    $N-1$ security):
    \begin{equation*}
      | f_{\ell,t} | \leq  s_{N-1} \cdot \bar{P}_\ell
    \end{equation*}

  Since the impedances $x_\ell$ change as capacity $\bar{P}_\ell$ is
  added, we do multiple runs and iteratively update the $x_\ell$ after
  each run, rather than risking a non-linear (or MILP) optimisation.


\end{frame}



\begin{frame}
  \frametitle{Notable constraints 2/2: Global constraints on \co2 and transmission volumes}
  CO${}_2$ limits are respected, given emissions $e_{n,s}$ for each fuel source $s$:
    \begin{equation*}
      \sum_{n,s,t}  g_{n,s,t} e_{n,s} \leq \textrm{CAP}_{\textrm{CO}_2} \hspace{1cm} \leftrightarrow \hspace{1cm} \m_{\textrm{CO}_2}
    \end{equation*}
    We enforce a reduction of \co2 emissions by some fraction of 1990
    levels.

    \vspace{.3cm}
    Optimal transmission capacities $\bar{P}_\ell$ cannot be reduced compared to today's capacities $\bar{P}_\ell^{\textrm{today}}$:
    \begin{equation*}
      \bar{P}_\ell \geq  \bar{P}_\ell^{\textrm{today}}
    \end{equation*}

    But we can also limit total new transmission volume in MWkm ($d_\ell$ is line length in km):
    \begin{equation*}
      \sum_{\ell} d_\ell   \bar{P}_\ell \leq \textrm{CAP}_{\textrm{trans}} \hspace{1cm} \leftrightarrow \hspace{1cm} \m_{\textrm{trans}}
    \end{equation*}
    We  successively change the transmission limit, to assess the costs of balancing power in time (i.e. storage) versus space (i.e. transmission networks).

\end{frame}



\begin{frame}
  \frametitle{PyPSA-Eur: Open Model of European Transmission System}
\begin{columns}[T]
\begin{column}{6cm}


  \vspace{0.4cm}
\centering

%\includegraphics[width=4cm]{line-loading}
\includegraphics[width=7cm]{pypsa-eur-grid}
\end{column}
\begin{column}{7.5cm}

  \begin{itemize}
    \item Grid data based on \alert{GridKit} extraction of ENTSO-E interactive map
    \item \alert{powerplantmatching} tool combines open databases using matching algorithm \href{https://github.com/larsga/Duke}{DUKE}
    \item Renewable energy time series from open \alert{atlite}, based
      on Aarhus University REatlas
    \item Geographic \alert{potentials} for RE from land use
    \item Basic \alert{validation} described in Hörsch et al \href{https://arxiv.org/abs/1806.01613}{`PyPSA-Eur: An Open Optimisation Model of the
      European Transmission System'}
    \item \url{https://github.com/PyPSA/pypsa-eur}
  \end{itemize}
\end{column}
\end{columns}

\end{frame}



\begin{frame}
  \frametitle{Reduce spatial resolution with clustering}

\begin{columns}[T]
\begin{column}{7cm}
We need spatial resolution to:
\begin{itemize}
\item capture the \alert{geographical variation} of renewables resources and the load
\item capture \alert{spatio-temporal effects} (e.g. size of wind correlations across the continent)
\item represent important \alert{transmission constraints}
\end{itemize}

BUT we do not want to have to model all 5,000 network nodes of the European system.
\end{column}
\begin{column}{6cm}
  \vspace{.5cm}

    \centering
    \includegraphics[width=6.5cm]{clustering}
\end{column}
\end{columns}
\end{frame}


\begin{frame}
  \frametitle{Solution: $k$-means clustering}

\centering
 \includegraphics[width=13cm]{networks-clustered-crop}

\end{frame}






\begin{frame}
  \frametitle{Sector coupling: A new source of flexibility}

  Couple the electricity sector (electric demand, generators,
  electricity storage, grid) to electrified
  transport and low-T heating demand (model covers 75\% of final energy consumption in 2014).
  Also allow production of synthetic hydrogen and methane.
% graphic generated in
\begin{figure}[!t]
\begin{adjustbox}{scale=0.70,trim=5 8.8cm 0 1cm}


  \begin{circuitikz}
  \draw (1.5,14.5) to [short,i^=grid connection] (1.5,13);
  \draw [ultra thick] (-5,13) node[anchor=south]{electric bus} -- (6,13);
  \draw(2.5,13) |- +(0,0.5) to [short,i^=$$] +(2,0.5);
  \draw (0,-0.5) ;
  \draw (0.5,13) -- +(0,-0.5) node[sground]{};
  \draw (2.5,12) node[vsourcesinshape, rotate=270](V2){}
  (V2.left) -- +(0,0.6);
  \draw (2.5,11.2) node{generators};
    \node[draw,minimum width=1cm,minimum height=0.6cm,anchor=south west] at (3.4,11.9){storage};
    \draw (4,13) to (4,12.5);


  \draw [ultra thick] (-6,10) node[anchor=south]{transport} -- (-3,10);
  \draw (-5.5,10) -- +(0,-0.5) node[sground]{};
  \draw (-3.5,10) to [short,i_=${}$] (-3.5,13);
  \draw (-3.2,11.5)  node[rotate=90]{discharge};
  \draw (-4.5,13) to [short,i^=${}$] (-4.5,10);
  \draw (-4.2,11.5)  node[rotate=90]{charge};
  \node[draw,minimum width=1cm,minimum height=0.6cm,anchor=south west] at (-4.5,8.9){battery};
  \draw (-4,10) to (-4,9.5);

    \draw [ultra thick] (2,10) -- (6.5,10)  node[anchor=south]{heat};
  \draw (3.5,10) -- +(0,-0.5) node[sground]{};
  % esource (empty source) is a dipole, so remove the legs by making it connect a distance of its own width
  % follows: http://tex.stackexchange.com/questions/87275/use-circuitikz-voltage-source-icon-as-a-node
  \draw (4.5,9.35) to [esource] (4.5,8.5);
  \draw (4.5,10) -- (4.5,9.35);
  \draw (4.5,8.3) node{solar thermal};
  \draw (5,13) to [short,i^=heat pump;] (5,10);
  \draw (6.2,11) node{resistive heater};
  \node[draw,minimum width=1cm,minimum height=0.6cm,anchor=south west] at (5.5,8.9){hot water tank};
  \draw (6,10) to (6,9.5);


  \draw [ultra thick] (-2,10)  -- (0.5,10) node[anchor=south]{hydrogen};
  \draw (-1.5,13) to [short,i_=${}$] (-1.5,10);
    \draw (-1.2,11.5)  node[rotate=90]{electrolysis};
  \draw (-0.5,10) to [short,i^=${}$] (-0.5,13);
  \draw (-0.2,11.5)  node[rotate=90]{fuel cell};
  \draw (-1,10) to (-1,9.5);
  \node[draw,minimum width=1cm,minimum height=0.6cm,anchor=south west] at (-1.5,8.9){store};

  \draw (0,10) to [short,i_=${}$] (0,8);
  \draw [ultra thick] (-1,8) node[anchor=south]{methane} -- (3,8);
  \draw (1.5,8) to [short,i_=${}$] (1.5,13);
  \draw (2.5,8) to [short,i_=${}$] (2.5,10);
  \node[draw,minimum width=1cm,minimum height=0.6cm,anchor=south west] at (0.5,6.9){store};
  \draw (1,8) to (1,7.5);
  \draw (0.3,9)  node[rotate=90]{methanation};
  \draw (1.8,9.2)  node[rotate=90]{generator/CHP};
  \draw (2.8,9)  node[rotate=90]{boiler/CHP};
  \end{circuitikz}

\end{adjustbox}
\end{figure}

\end{frame}




\begin{frame}[fragile]
  \frametitle{Challenge: Heating and transport demand strongly peaked}


  \begin{columns}[T]
\begin{column}{6cm}
  Compared to electricity, heating and transport are \alert{strongly peaked}.
  \begin{itemize}
  \item   Heating is strongly seasonal, but also with synoptic variations.
    \item   Transport has strong daily periodicity.
  \end{itemize}

  \vspace{.3cm}

  \includegraphics[trim=0 0cm 0 0cm,width=6cm,clip=true]{elec_demand.pdf}

\end{column}
\begin{column}{6cm}
  \includegraphics[trim=0 0cm 0 0cm,width=5.7cm,clip=true]{heat_demand.pdf}
  \includegraphics[trim=0 0cm 0 0cm,width=5.7cm,clip=true]{transport_profiles.pdf}
\end{column}
\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Transport sector: Electrification of Transport}
\begin{columns}[T]
\begin{column}{7cm}
    \includegraphics[trim=0 0cm 0 0cm,width=8cm,clip=true]{transport_profiles.pdf}

    Weekly profile for the transport demand based on statistics gathered by the German Federal Highway Research Institute (BASt).

\end{column}
\begin{column}{7cm}
  \begin{itemize}
  \item Road and rail transport  is fully electrified (vehicle costs are not considered)
    \item Because of higher efficiency of electric motors, final
      energy consumption 3.5 times lower than today at 1100~TWh\el/a for Europe
            \item In model can replace Battery Electric Vehicles (BEVs) with Fuel Cell Electric Vehicles (FCEVs) consuming hydrogen. Advantage: hydrogen cheap to store. Disadvantage: efficiency of fuel cell only 60\%, compared to 90\% for battery discharging.
  \end{itemize}
\end{column}
\end{columns}

\end{frame}





\begin{frame}
  \frametitle{Heating sector: Many Options with Thermal Energy Storage (TES)}
\begin{columns}[T]
\begin{column}{7cm}

    \includegraphics[trim=0 0cm 0 0cm,width=8cm,clip=true]{heat_demand.pdf}

    Heat demand profile from 2011 in each region using population-weighted average daily T in each region, degree-day approx. and scaled to Eurostat total heating demand.


\end{column}
\begin{column}{7cm}
  \begin{itemize}
  \item All space and water heating in the residential and services
    sectors is considered, with no additional efficiency measures
    (conservative) - total heating demand is  3585~TWh\th/a.
  \item Heating demand can be met by heat pumps, resistive heaters, gas boilers, solar thermal, Combined-Heat-and-Power (CHP) units. No industrial waste heat.
    \item Thermal Energy Storage (TES) is available to the system as hot water tanks.
  \end{itemize}
\end{column}
\end{columns}

\end{frame}






\begin{frame}
  \frametitle{Centralised District Heating versus Decentralised Heating}

  We model both fully decentralised heating and cases where up to 45\%
  of heat demand is met with district heating in northern countries.

\begin{columns}[T]
\begin{column}{5cm}
  \alert{Decentral individual heating} can be supplied by:
  \begin{itemize}
    \item Air- or Ground-sourced heat pumps
  \item Resistive heaters
  \item Gas boilers
    \item Small solar thermal
  \item Water tanks with short time constant $\tau = 3$ days
  \end{itemize}
\end{column}
\begin{column}{5cm}
  \alert{Central heating} can be supplied via district heating networks by:
  \begin{itemize}
    \item Air-sourced heat pumps
\item Resistive heaters
\item Gas boilers
        \item Large solar thermal
  \item Water tanks with long time constant $\tau = 180$ days
\item CHPs
  \end{itemize}
\end{column}

\begin{column}{5cm}
  CHP feasible dispatch:
    \includegraphics[trim=0 0cm 0 0cm,width=5cm,clip=true]{chp_feasible.pdf}
\end{column}

\end{columns}


\end{frame}



\section{Results}

\begin{frame}
  \frametitle{Introduction to results}

  In the first few slides we'll sequentially turn on different demand
  sectors and flexibility options to assess their effects on total
  system costs and balancing in the \alert{temporal dimension}.

  This was done in a one-node-per-country model for Europe in
  \href{https://arxiv.org/abs/1801.05290}{{\bf Brown et al 2018}} for a 95\%
  CO$_2$ reduction target (compared to 1990).

  Then we'll upgrade to a 128-node model and explore the effects of
  transmission expansion and different CO$_2$ targets, and how they
  interact - the \alert{spatial dimension}.

\end{frame}



\begin{frame}
  \frametitle{Coupling Heating and Transport to Electricity: Limited Use of Flexibility}
  \begin{columns}[T]
    \begin{column}{9cm}
      \includegraphics[width=9cm]{RGI-h-0.pdf}

    \end{column}
    \begin{column}{5cm}
      \begin{itemize}
      \item Costs jump by 117\% to cover new energy supply and heating infrastructure
      \item 95\% \co2{} reduction means most heat is generated by heat pumps using renewable electricity
      \item Cold winter weeks with high demand, low wind, low solar and low heat pump COP mean backup gas boilers required
      \end{itemize}
    \end{column}
  \end{columns}
\end{frame}



\begin{frame}
  \frametitle{Cold week in winter}

    \begin{columns}[T]
    \begin{column}{6cm}

  \centering
\includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-base-0-DE}

\includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-base-0_urban_heat-DE}
    \end{column}
    \begin{column}{7cm}
      \vspace{1.5cm}
        There are difficult periods in winter with:
        \begin{itemize}
        \item \alert{Low} wind and solar generation
        \item \alert{High} space heating demand
        \item \alert{Low} air temperatures, which are bad for air-sourced heat pump performance
        \end{itemize}

        Solution: \alert{backup gas boilers} burning either natural gas, or
        synthetic methane.
    \end{column}
    \end{columns}
\end{frame}



\begin{frame}
  \frametitle{Using heating flexibility}
  \begin{columns}[T]
    \begin{column}{8.3cm}
      \includegraphics[width=9cm]{RGI-heating-0.pdf}
    \end{column}
    \begin{column}{6cm}

      \vspace{.5cm}
        Successively activating couplings and flexibility \alert{reduces costs} by 28\%.
        These options include:
        \begin{itemize}
          \item  production of \alert{synthetic methane}
          \item  centralised \alert{district heating} in areas with dense heat demand
          \item long-term \alert{thermal energy storage} (TES)  in district heating networks
          \item \alert{demand-side management} and vehicle-to-grid for 50\% of battery electric vehicles (BEV)
        \end{itemize}
    \end{column}
  \end{columns}
\end{frame}



\begin{frame}
  \frametitle{Cold week in winter: inflexible (left); smart (right)}

  \begin{columns}[T]
    \begin{column}{6.5cm}
  \centering
\includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-base-0-DE}

\includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-base-0_urban_heat-DE}
    \end{column}
    \begin{column}{6.5cm}
  \centering

  \includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-central-tes-0-DE}

  \includegraphics[trim=0 0cm 0 0cm,width=5.5cm,clip=true]{cold_week-central-tes-0_urban_heat-DE}
    \end{column}
  \end{columns}
\end{frame}


\begin{frame}
  \frametitle{Storage energy levels: different time scales}

\begin{columns}[T]
  \begin{column}{9cm}

    \vspace{0.5cm}
  \includegraphics[width=9cm]{scales.pdf}

  \end{column}

  \begin{column}{6cm}
    \begin{itemize}
    \item Methane storage is depleted in winter, then replenished
      throughout the summer with synthetic methane
    \item Hydrogen storage fluctuates every 2–3 weeks, dictated by
      wind variations
    \item Long-Term Thermal Energy Storage (LTES) has a dominant
      seasonal pattern, with synoptic-scale fluctuations are
      super-imposed
    \item Battery Electric Vehicles (BEV) and battery storage
      vary daily
    \end{itemize}

  \end{column}

\end{columns}
\end{frame}




\begin{frame}
  \frametitle{Application to 128-node transmission model}


\begin{columns}[T]
  \begin{column}{6cm}

    \vspace{1cm}
    The previous sector coupling results come from a model with one
    node power country described in
    \href{https://arxiv.org/abs/1801.05290}{Brown et al 2018}, for the
    case with no interconnecting transmission.

    \vspace{1cm}

    Now we apply the smart flexibility model to a 128-node
    model of Europe.

  \end{column}


  \begin{column}{9cm}

    \vspace{0.1cm}
  \includegraphics[width=8.5cm]{today.pdf}

  \end{column}

\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Benefit of grid expansion for sector-coupled system}



\begin{columns}[T]
  \begin{column}{9cm}

    \vspace{0.1cm}
  \includegraphics[width=9cm]{lv_sweep-co20.pdf}

  \end{column}

  \begin{column}{6cm}

    \begin{itemize}
    \item The optimal volume (in MWkm) of transmission is around factor 3 bigger than today's grid
    \item Costs reduce from solar and power-to-gas; more offshore wind
    \item Costlier than today's system (380~billion \euro/a with same assumptions)
    \item Total cost benefit of extra grid: $\sim$~80~billion \euro/a
    \item \alert{Over half of benefit available at 25\% expansion} (like TYNDP)
    \end{itemize}

  \end{column}

\end{columns}


%  Benefit of cross-border transmission is weaker with full sector flexibility (right) than with inflexible sector coupling (left); comes close to today's costs of around \euro~377~billion per year

\end{frame}








\begin{frame}
  \frametitle{Distribution of technologies: No grid expansion}


\begin{columns}[T]
  \begin{column}{9cm}

    \vspace{0.1cm}
  \includegraphics[width=8.5cm]{lv1p0-CO0-spatial-costs-all.pdf}

  \end{column}

  \begin{column}{6cm}
    \vspace{1cm}
    \begin{itemize}
    \item Mix of solar and wind at almost all locations
    \item Capacities of offshore wind limited by grid restrictions
    \item Large share of power-to-gas paired with on- and offshore
      wind, particularly at periphery of network
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Distribution of technologies: 25\% more grid volume}


\begin{columns}[T]
  \begin{column}{9cm}

    \vspace{0.1cm}
  \includegraphics[width=8.5cm]{lv1p25-CO0-spatial-costs-all.pdf}

  \end{column}

  \begin{column}{6cm}
    \vspace{1cm}
    \begin{itemize}
    \item Wind predominates in North
    \item Solar predominates in South
    \item P2G near wind and at periphery of network
    \item Grid expansion mostly around North Sea, to bring offshore to load centres, and East-West to smooth weather coming from Atlantic
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Distribution of technologies: 100\% more grid volume}


\begin{columns}[T]
  \begin{column}{9cm}

    \vspace{0.1cm}
  \includegraphics[width=8.5cm]{lv2p0-CO0-spatial-costs-all.pdf}

  \end{column}

  \begin{column}{6cm}
    \vspace{1cm}
    \begin{itemize}
    \item Further expansion of off- and onshore wind in North
    \item Grid expansion focuses again on North and East-West axis
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}



\begin{frame}{Pathway down to zero emissions in electricity, heating and transport}
\begin{columns}[T]
  \begin{column}{9cm}

    \includegraphics[width=9cm]{co2_sweep-lv1-25.pdf}

  \end{column}


  \begin{column}{6cm}

    \vspace{0.5cm}

    If we look at investments to eradicate \co2{} emissions in
    electricity, heating and transport we see:

    \begin{itemize}
    \item Electricity and transport are decarbonised first
    \item Heating comes next with expansion of heat pumps below 30\%
    \item Below 10\%, power-to-gas solutions replace natural gas
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}





\begin{frame}{Benefit of grid depends on level of carbon dioxide reduction}
\begin{columns}[T]
  \begin{column}{9cm}

    \includegraphics[width=9cm]{total_costs-lv-co2.pdf}

  \end{column}


  \begin{column}{6cm}

    \vspace{0.7cm}
    \begin{itemize}
    \item Optimal grid (rightmost point of each curve) grows successively larger
    \item Benefit of grid expansion grows with depth of CO$_2$ reduction
    \item Can still get away with no transmission reinforcement (if
      the system is operated flexibly)
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}

\begin{frame}{Relative market values drop, but not drastically}

  \centering
    \includegraphics[width=11.245cm]{co2_sweep-mvs-lv1-25.pdf}

\end{frame}

\begin{frame}
  \frametitle{Outlook}

  \begin{itemize}
  \item Develop \alert{improvements on  algorithmic side} to enable larger problems (clustering, improved optimisation routines)
  \item Explore \alert{pathways} from here to 2050 more rigorously
  \item Improve \alert{technology palette}: bioenergy, waste heat, CCS, DAC, more synthetic electrofuels
 \item Complete \alert{sectoral coverage}: aviation, shipping, process heat
   in industry
    \item Explore more \alert{grid optimisation} options: HTC, DLR, PST, SPS with
      storage/DSM
    \item Improve representation of \alert{thermal loads} (e.g. to assess building insulation)
          \item Co-optimise \alert{distribution grids} in a simplified manner
     \item Develop \alert{model simplifications} that reproduce features of bigger model
  \end{itemize}
\end{frame}



\section{Open Energy Modelling}


\begin{frame}
  \frametitle{Idea of Open Energy Modelling}

  The whole chain from raw data to modelling results should be open:

  \vspace{0.2cm}

  \centering
  \includegraphics[width=13cm]{open-model-process}

  \vspace{0.1cm}
  \centering
  \large
  \textbf{Open data + free software $\Rightarrow$ Transparency + Reproducibility}

  \normalsize
  \raggedright
  \vspace{0.1cm}

  There's an initiative for that! Sign up for the mailing list / come to the next workshop at Aarhus University, Denmark, 22-24 May 2019:
  \vspace{0.1cm}

  \centering

  \includegraphics[width=8cm]{openmod-logo-large}

  \large
  \textbf{\href{http://openmod-initiative.org/}{openmod-initiative.org}}

  \normalsize
  \raggedright

  \source{openmod initiative}
\end{frame}




\begin{frame}
  \frametitle{Python for Power System Analysis (PyPSA)}

  Our free software PyPSA is online at \url{https://pypsa.org/} and on
  github. It can do:



\begin{columns}[T]
  \begin{column}{6cm}

  \begin{itemize}
  \item Static \alert{power flow}
  \item \alert{Linear optimal power flow} (LOPF) (multiple periods, unit commitment,
    storage, coupling to other sectors)
    \item \alert{Security-constrained LOPF}
    \item Total electricity system \alert{investment optimisation}
  \end{itemize}

  It has models for storage, meshed AC grids, meshed DC grids, hydro plants, variable renewables and sector coupling.

  \end{column}

\begin{column}{7cm}

  \vspace{0.3cm}
\centering
\includegraphics[width=8cm]{lmp}


\end{column}
\end{columns}

\end{frame}


\section{Conclusions}


\begin{frame}{Conclusions}

  \begin{itemize}
    \item Meeting \alert{Paris targets} is much more urgent than widely recognised

    \item \alert{Electrification of other energy sectors} like heating
      and transport is important, since wind and solar will dominate
      low-carbon primary energy provision

    \item \alert{Grid helps} to make CO2 reduction easier $=$ cheaper

    \item \alert{Cross-sectoral} approaches are important to reduce
      CO2 emissions \alert{and} for flexibility

    \item \alert{Policy prerequisites}: high, increasing and
      transparent \alert{price for \co2{} pollution}; to manage grid
      congestion better: \alert{smaller bidding zones} and \alert{more dynamic pricing}

    \item The energy system is complex and contains some uncertainty
      (e.g. cost developments, scaleability of power-to-gas, consumer behaviour), so
      \alert{openness is critical}

  \end{itemize}

\end{frame}


\begin{frame}
  \frametitle{Costs and assumptions for the electricity sector (projections for 2030)}

  \begin{table}
\centering
\begin{tabular}{@{}lrlrr@{}}
\toprule
Quantity                &Overnight  Cost [\euro]  &Unit & FOM [\%/a] & Lifetime [a] \\
\midrule
Wind onshore    &1182   &kW\el &3 & 25   \\
Wind offshore  &2506   &kW\el  &3& 25  \\
Solar PV           &600   &kW\el &4 & 25   \\
Gas             &400    &kW\el  &4& 30  \\
%Gas marginal            &75     &\euro{}/MWh$_{\textrm{e}}$    \\
Battery storage         &1275   &kW\el  & 3 & 20 \\
Hydrogen storage        &2070   &kW\el  & 1.7 &20 \\
Transmission line       &400    &MWkm & 2 & 40\\
\bottomrule
\end{tabular}
\end{table}
  Interest rate of 7\%, storage efficiency losses, only gas has \co2 emissions, gas marginal costs.

  Batteries can store for 6 hours at maximal rating (efficiency $0.9\times 0.9$), hydrogen storage for 168 hours (efficiency $0.75\times 0.58$).
\end{frame}





\begin{frame}
  \frametitle{Cost and other assumptions}

  \begin{table}
\centering
\begin{tabular}{@{}lrlrrr@{}}
\toprule
Quantity                & O'night cost [\euro]  &Unit & FOM [\%/a] & Lifetime [a] & Efficiency \\
\midrule
GS Heat pump decentral & 1400 & kW\th  & 3.5& 20 \\
AS Heat pump decentral & 1050 & kW\th  & 3.5& 20 \\
AS Heat pump central & 700 & kW\th  & 3.5& 20 \\
Resistive heater & 100  & kW\th  & 2& 20 & 0.9\\
Gas boiler decentral & 175  & kW\th  & 2& 20 & 0.9 \\
Gas boiler central & 63  & kW\th  & 1& 22 & 0.9 \\
CHP & 650 & kW\el & 3& 25\\
Central water tanks & 30 & m${}^3$  & 1& 40 & $\tau = 180$d\\
District heating & 220 & kW\th & 1 & 40 &  \\
Methanation+DAC & 1000 & kW$_{H_2}$ & 3 & 25  & 0.6\\
%Gas plant efficiency    &30     &\%     \\
%Interest rate           &7      &\%     \\
\bottomrule
\end{tabular}
\end{table}
  Costs oriented towards Henning \& Palzer (2014, Fraunhofer ISE) and Danish Energy Database
\end{frame}


\begin{frame}
  \frametitle{Transport sector: Battery Electric Vehicles}
\begin{columns}[T]
\begin{column}{7cm}
    \includegraphics[trim=0 0cm 0 0cm,width=8cm,clip=true]{bev_availability.pdf}

    Availability (i.e. fraction of vehicles plugged in) of Battery Electric Vehicles (BEV).
\end{column}
\begin{column}{7cm}
  \begin{itemize}
  \item Passenger cars to Battery Electric Vehicles (BEVs), 50~kWh battery available and 11~kW charging power
  \item Can participate in DSM and V2G, depending on scenario (state of charge returns to at least 75\% every morning)
    \item All BEVs have time-dependent availability, averaging 80\%, max 95\% (at night)
    \item No changes in consumer behaviour assumed (e.g. car-sharing/pooling)
    \item BEVs are treated as exogenous (capital costs NOT included in calculation)
  \end{itemize}
\end{column}
\end{columns}

\end{frame}





\begin{frame}
  \frametitle{Using Battery Electric Vehicle Flexibility}
  \begin{columns}[T]
    \begin{column}{9cm}
      \includegraphics[width=9cm]{RGI-transport-0.pdf}


    \end{column}
    \begin{column}{6cm}
      \begin{itemize}
      \item Shifting the charging time can reduce system costs by up to 14\%.
      \item If only 25\% of vehicles participate: already a 10\% benefit.
      \item Allowing battery EVs to feed back into the grid (V2G) reduces costs by a further 10\%.
      \item This removes case for stationary batteries and allows more solar.
      \item If fuel cells replace electric vehicles, hydrogen electrolysis increases costs because of conversion losses.
      \end{itemize}
    \end{column}
  \end{columns}
\end{frame}






\begin{frame}
  \frametitle{LTES and P2G in autarkic (self-sufficient) apartment block}

  LTES and H2 storage enable \alert{complete self-sufficiency} for an
  apartment block in Brütten, Switzerland. All its energy comes from solar panels and a heat pump (no grid connections).

  \centering
  \includegraphics[trim=0 0cm 0 0cm,width=12cm,clip=true]{bruetten-house-system.jpg}
\end{frame}





\begin{frame}{Copyright}


  Unless otherwise stated, the graphics and text are Copyright \copyright Tom Brown, 2018.


  The graphics and text for which no other attribution are given are licensed under a
  \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons
  Attribution 4.0 International Licence}.

  \begin{center}\ccby\end{center}

\end{frame}


\end{document}
