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\title{\vspace{-1.7cm}
Synergies of sector coupling and transmission extension in a \\cost-optimised, highly renewable European energy system
}
%\subtitle{---}
\author{
  {\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)}
}


\date{\vspace{0.3cm}DIW Berlin, 5th July 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{Energy System Challenges}


\begin{frame}
  \frametitle{The Global Carbon Dioxide Challenge: Budgets from 2016}

  600 Gt budget gives 33\% chance of $1.5^\circ$C (Paris: `pursue efforts to limit [warming] to $1.5^\circ$C')\\
  800 Gt budget gives 66\% chance of $2^\circ$C (Paris: hold `the increase...to well below $2^\circ$C')

  \vspace{.05cm}
  \centering
  \includegraphics[width=14.6cm]{carbon_crunch-cropped}

  \source{`Three years to safeguard our climate,' Nature, 2017}

\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 electification of other sectors is critical for decarbonisation}

  Wind and solar dominate the expandable potentials for low-carbon
  energy provision, so \alert{electrification is essential} to decarbonise
  sectors such as transport and heating.

  \vspace{0.5cm}

  \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}

    \vspace{0.7cm}
  Fortunately, these sectors can also offer crucial \alert{flexibility} back to the electricity system.


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

\end{frame}






\begin{frame}[fragile]
  \frametitle{Energy System Design: Research Questions}

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

    \vspace{.2cm}
  \begin{itemize}
  \item What \alert{infrastructure} does a highly renewable energy system
    require?
  \item \alert{Where} should it go? And \alert{when}?
  \item Given a desired \co2 reduction, how much will it \alert{cost}?
    \item How to deal with the \alert{variability}  of wind and solar?
  \end{itemize}

  \hspace{0.15cm}

  The answers to these questions affect \alert{hundreds of billions}
  of euros of spending per year.

  \hspace{0.15cm}

  Researchers deal with these questions by solving large \alert{optimisation} problems.
  \end{column}
  \begin{column}{4.5cm}
    \vspace{.2cm}
  \includegraphics[width=4.7cm]{goat-clean}
  \end{column}
\end{columns}
\end{frame}



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



\begin{columns}[T]

  \begin{column}{4.5cm}


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

  \end{column}


  \begin{column}{7.6cm}


  \vspace{.7cm}

  The Energy Transition is not just a case of ``cost optimisation
  under CO${}_2$ constraints''.  There are also \alert{social and political constraints}.

  We need to assess:
  \begin{itemize}
    \item Reducing need for transmission using \alert{storage / sector coupling} (e.g. battery electric vehicles, thermal storage)
    \item \alert{New technologies} that can minimise the landscape impact of transmission
    \item \alert{Efficiency} and \alert{sufficiency} to reduce demand
  \end{itemize}

  \vspace{0.2cm}

  \alert{Transparency is critical} for public acceptance.
  \end{column}

\end{columns}

\end{frame}



\section{Variability of Wind, Solar \& Demand}


\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. chemically with hydrogen or methane storage, thermal energy storage, 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{Warm-Up Electricity Only}

\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}{Yearly system costs}\right) = \sum_n \left(\parbox{6em}{Annualised capital costs}\right) + \sum_{n,t} \left(\parbox{6em}{Marginal costs}\right)
\end{equation*}
subject to
\begin{itemize}
\item meeting energy demand at each node $n$ (e.g. region) and time $t$ (e.g. hour of year)
\item wind, solar, hydro (variable renewables) availability $\forall\: n,t$
\item transmission constraints between nodes
\item (installed capacity) $\leq$ (geographical potential for renewables)
\item CO${}_2$ constraint (95\% reduction compared to 1990)
\end{itemize}

  \vspace{.3cm}

  Generation, storage and transmission optimised \alert{jointly}
  because they are \alert{strongly interacting}.
\end{frame}





\begin{frame}
  \frametitle{Warm-up: Determine optimal electricity system}


\begin{columns}[T]
\begin{column}{7cm}
  \begin{itemize}
  \item Meet all electricity demand.
  \item Reduce \co2{} by 95\% compared to 1990.
  \item \alert{Generation} (where potentials allow): onshore and offshore
    wind, solar, hydroelectricity, backup from natural gas.
  \item \alert{Storage}: batteries for short term, electrolyse hydrogen gas for long term.
  \item \alert{Grid expansion}: simulate everything from no grid expansion (like a \alert{decentralised solution}) to optimal grid expansion (with significant \alert{cross-border trade}).
  \end{itemize}
\end{column}
\begin{column}{6.5cm}


  \vspace{0.3cm}
\centering

\ifgoat
\includegraphics[width=7cm]{pypsa-eur-grid}
\fi

\end{column}
\end{columns}


\source{PyPSA-Eur, based on ENTSO-E map}
\end{frame}



\begin{frame}
  \frametitle{Global constraint on transmission volume}


    \vspace{.5cm}

    New transmission is \alert{capped}, given length $d_l$ and capacity $\bar{P}_\ell$ of each line:
    \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).

    The shadow price $\m_{\textrm{trans}}$ [EUR/(aMWkm)] gives us the marginal value of new transmission capacity.

\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/FRESNA/pypsa-eur}
  \end{itemize}
\end{column}
\end{columns}

\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 & 20   \\
Wind offshore  &2506   &kW\el  &3& 20  \\
Solar PV           &600   &kW\el &4 & 20   \\
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{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{Electricity system with no grid expansion}
\begin{columns}[T]
\begin{column}{8cm}
    \includegraphics[width=8cm]{legend-two}
    \ifgoat
    \includegraphics[trim=0 0cm 0 2cm,width=8cm]{euro-pie-pre-7-branch_limit-1-256.png}
    \fi
\end{column}
\begin{column}{6cm}

  \vspace{.2cm}
  \begin{itemize}
  \item Assume \alert{nodal pricing}
  \item Wind built in North where grid capacity allows, solar in South
  \item With \alert{no grid expansion}, lots of storage required to
    balance variability, \alert{costs are high}
  \item Batteries pair with solar in South
  \item Hydrogen storages pairs with longer-term variations of wind in North
  \end{itemize}
\end{column}

\end{columns}

\source{\href{https://doi.org/10.1109/EEM.2017.7982024}{Hörsch et al, 2017}}

\end{frame}



\begin{frame}
  \frametitle{Dispatch with no grid expansion}

  For Great Britain with limited interconnecting transmission, excess wind is either stored as hydrogen or curtailed:

  \centering
  \includegraphics[width=13cm]{GB-0}
\end{frame}


\begin{frame}
  \frametitle{When grid expansion allowed: avoid costly storage}

  \hspace{-1.1cm}
  \includegraphics[width=15cm]{legend-flat}
  \begin{columns}[T]

\begin{column}{8cm}

  \ifgoat
  \includegraphics[trim=0 0cm 0 2cm,width=8cm]{euro-pie-pre-7-branch_limit-1-5-256.png}
  \fi

\end{column}
\begin{column}{8cm}

  \raisebox{-6.6cm}{
\ifgoat
\includegraphics[trim=0 0cm 0 2cm,width=8cm]{euro-pie-pre-7-branch_limit-3-256.png}
\fi
  }

\end{column}

\end{columns}


\end{frame}



\begin{frame}
  \frametitle{Dispatch with cost-optimal interconnecting transmission}

  Almost all excess wind can be now be exported:

  \centering
  \includegraphics[width=13cm]{GB-1}
\end{frame}



\begin{frame}
  \frametitle{Cost behaviour as transmission expansion is allowed}


\begin{columns}[T]
\begin{column}{8.5cm}
\centering
  \includegraphics[width=8.5cm]{costs_per_cluster_181}
  %\includegraphics[width=6cm]{pre-2-costs_de_storage}
\end{column}
\begin{column}{6cm}
  \begin{itemize}
%\item   %Big reduction in curtailment
    \item Big \alert{non-linear cost reduction} as grid is expanded
    \item Most of cost reduction happens with \alert{25\% grid
      expansion} compared to today's grid (25\% corresponds
      to TYNDP)
    \item Costs comparable to today's system (around \euro 200~billion/a)
      \item Investment in solar and batteries decrease significantly as
        grid expanded; with cost-optimal grid, system is dominated by
        wind
  \end{itemize}
\end{column}
\end{columns}
\source{\href{https://doi.org/10.1016/j.energy.2017.06.004}{Schlachtberger et al, 2017}, \href{https://doi.org/10.1109/EEM.2017.7982024}{Hörsch et al, 2017}}
\end{frame}


\begin{frame}
  \frametitle{Locational Marginal Prices CAP=1 versus CAP=3}



  \begin{columns}[T]

\begin{column}{8cm}

  \hspace{1cm}  With today's capacities:

  \includegraphics[width=8cm]{lmp-1-256.pdf}

\end{column}
\begin{column}{8cm}

  \hspace{1cm}With three times today's grid:

  \includegraphics[width=8cm]{lmp-3-256.pdf}

\end{column}

\end{columns}


\end{frame}



\begin{frame}
  \frametitle{Grid expansion cap shadow price as cap is relaxed}


\begin{columns}[T]
\begin{column}{10cm}
\centering
  \includegraphics[width=11cm]{shadows-branch_limit}
  %\includegraphics[width=6cm]{pre-2-costs_de_storage}
\end{column}
\begin{column}{4cm}
  \begin{itemize}
%\item   %Big reduction in curtailment
  \item With overhead lines the optimal system has around 3 times today's transmission volume
  \item With underground cables (5-8 times more expensive) the optimal system has around 1.3 to 1.6 times today's transmission volume
  \end{itemize}
\end{column}
\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Different flexibility options have difference temporal scales}

\begin{columns}[T]
  \begin{column}{10.5cm}

    \vspace{0.5cm}
  \includegraphics[width=11cm]{soc_series_LV0-25_H2_hydro_diw2030_solar1_7-eps-converted-to.pdf}

  \end{column}

  \begin{column}{3cm}
    \vspace{1cm}
    \begin{itemize}
    \item Hydro reservoirs are \alert{seasonal}
    \item Hydrogen storage is \alert{synoptic}
    \end{itemize}

  \end{column}

\end{columns}
\end{frame}



\begin{frame}
  \frametitle{Different flexibility options have difference temporal scales}

\begin{columns}[T]
  \begin{column}{10.5cm}

    \vspace{0.5cm}
  \includegraphics[width=11cm]{soc_series_LV0-25_all_2011-08_diw2030_solar1_7-eps-converted-to.pdf}

  \end{column}

  \begin{column}{3cm}
        \vspace{2cm}
    \begin{itemize}
    \item Pumped hydro and battery storage are \alert{daily}
    \end{itemize}

  \end{column}

\end{columns}
\end{frame}

\section{Electricity, Heat and Transport}


\begin{frame}
  \frametitle{Include other sectors: heating and land transport}

  Electricity,  (low-temperature) heating and land transport cover 77\% of 2015 CO$_2$ emissions:

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


  \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}{Efficiency of renewables and sector coupling}


  \includegraphics[width=\linewidth,trim=2.7cm 20cm 3.2cm 1.8cm,clip=true]{./graphics/bmwi-whitepaper-figure_18.pdf}

  \source{\href{https://www.bmwi.de/Redaktion/EN/Publikationen/whitepaper-electricity-market.html}{BMWi White Paper 2015}}
\end{frame}


\begin{frame}[fragile]
  \frametitle{Challenge: Heating and transport demand highly 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}[fragile]
  \frametitle{Sector Coupling}

  \alert{Idea}: Couple the electricity sector to heating and mobility.

  This enables decarbonisation of these sectors \alert{and} offers more flexibility to the power system.

  \vspace{0.2cm}

  \begin{columns}[T]
\begin{column}{6cm}
  \alert{Battery electric vehicles} can change their charging pattern to benefit the
  system and even feed back into the grid if necessary

  \includegraphics[trim=0 0cm 0 0cm,width=6cm,clip=true]{tesla.jpg}
\end{column}
\begin{column}{6cm}
  \alert{Heat} and \alert{synthetic fuels} are easier and cheaper to store than electricity, even over many months

  \vspace{0.5cm}

        \includegraphics[trim=0 0cm 0 0cm,width=6cm,clip=true]{pit-zoom}
\end{column}
\end{columns}


\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}

\vspace{1cm}

  [NB: Computational restrictions mean restricting to
    one-node-per-country for Europe.]


\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 All road and rail transport in each country is electrified, where it is not already electrified
    \item Because of higher efficiency of electric motors, final
      energy consumption 3.5 times lower than today at 1102~TWh\el/a for the 30
      countries
            \item In model can replace Electric Vehicles (EVs) with Fuel Cell Vehicles (FCVs) 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{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{Coupling Transport to Electricity}
  \begin{columns}[T]
    \begin{column}{9cm}
      \includegraphics[width=9cm]{RGI-t-0.pdf}


    \end{column}
    \begin{column}{5cm}
      \begin{itemize}
      \item If all road and rail transport is electrified, electrical demand increases 37\%
      \item Costs increase 41\% because charging profiles are very peaked (NB: distribution grid costs NOT included)
      \item Stronger preference for PV and storage in system mix because of daytime peak
      \item Can now use flexible charging
      \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{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 all 30 countries using population-weighted average daily T in each country, 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}



\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{Coupling Heating to Transport and Electricity: Electricity Demand}
  \begin{columns}[T]
    \begin{column}{9cm}
      \includegraphics[width=9cm]{RGI-supply_energy.pdf}

    \end{column}
    \begin{column}{5cm}
      \begin{itemize}
      \item To 4062~TWh\el/a demand from electricity and transport, 3585~TWh\th/a heating demand is added
      \item Much of the heating demand is met via electricity, but with high efficiency from heat pumps
      \item Electricity demand 80\% higher than current electricity demand
        %5600/3100
      \item Efficiency savings can reduce this \dots
      \end{itemize}
    \end{column}
  \end{columns}
\end{frame}



\begin{frame}
  \frametitle{Coupling Heating to Transport and Electricity: Costs}
  \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 from 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{Sector Coupling with All Extra Flexibility (V2G and TES)}

  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

  \centering
  \includegraphics[width=13cm]{transmission.pdf}
\end{frame}



\begin{frame}
  \frametitle{Spatial distribution of primary energy for All-Flex-Central}

  Including optimal transmission sees a shift of energy production to wind in Northern Europe.

\begin{columns}[T]
  \begin{column}{7cm}

    \vspace{0.5cm}
  \includegraphics[width=7.6cm]{spatial-all_flex-central-0.pdf}

  \end{column}
  \begin{column}{7cm}

    \vspace{0.5cm}
  \includegraphics[width=7.6cm]{spatial-all_flex-central-opt.pdf}

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

    \includegraphics[width=9cm]{RGI-CO2-twin}

  \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 Transmission increasingly important below 30\%
    \item Heating comes next with expansion of heat pumps below 20\%
    \item Below 10\%, power-to-gas solutions replace natural gas
    \end{itemize}

  \end{column}

\end{columns}

\end{frame}



\begin{frame}{Electricity price statistics: zero-price hours gone thanks to P2G}

  \centering
    \includegraphics[width=11.245cm]{price_statistics.pdf}

\end{frame}



\begin{frame}{Curtailment also much reduced}

  \centering
    \includegraphics[width=11.245cm]{curtailment.pdf}

\end{frame}



\begin{frame}{Market values relative to average load-weighted price re-converge}

  \centering
    \includegraphics[width=11.245cm]{market_values.pdf}

\end{frame}




\begin{frame}{Gas production/consumption tightly coupled to price}

  \centering
    \includegraphics[width=11cm]{gas_v_prices.pdf}

\end{frame}




\begin{frame}
  \frametitle{Outlook}

  \begin{itemize}
  \item Develop improvements on  algorithmic side to enable larger problems (clustering, improved optimisation routines)
  \item Apply sector coupling to 200-node European model (instead of
    one-node-per-country) to see real transmission bottlenecks with scope, scale and sectors
  \item Explore pathway from here to 2050 (is P2X cost-effective sooner for local transmission bottlenecks? - these are not seen in the one-node-per-country sector model)
  \item Improve technology palette: bioenergy, waste heat, CCS, DAC, more synthetic electrofuels
 \item Complete sectoral coverage: aviation, shipping, process heat
   in industry
    \item Explore more grid optimisation options: HTC, DLR, PST, SPS with
      storage/DSM
  \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
  \vspace{0.1cm}

  There's an initiative for that! Sign up for the mailing list / come to the next workshop:
  \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 There are \alert{lots of cost-effective solutions} thanks to falling price of renewables

    \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}

    \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}{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}
