
\newcommand{\thistitle}{Lecture 9: The Electricity Grid}

\input{title.tex}


\section{Introduction to Grid Congestion}




\begin{frame}
  \frametitle{Lecture 3: Benefits of Trade}

  Thus far we have looked at electricity markets in \alert{isolation} from each other, while also \alert{ignoring grid physics}.

  Recall: Trade between 2 regions always leads to a \alert{welfare gain} (WFG) in each country, but can have a strong influence on the distribution between the consumer and producer surpluses.

  \centering
\begin{tikzpicture}[
    scale=1.7,
    demand/.style={blue, thick},
    supply/.style={red, thick},
    axis/.style={very thick, ->, >=stealth', line join=miter},
    important line/.style={thick}, dashed line/.style={dashed, thin},
    every node/.style={color=black},
    dot/.style={circle,fill=black,minimum size=4pt,inner sep=0pt,
      outer sep=-1pt},
  ]
  % axis
  \draw[axis,<->] (2.5,0) node(xline)[right] {quantity $Q$} -|
  (0,2.5) node(yline)[above] {price $p$};
  % demand-supply diagram
  \draw[supply] (0,0.1) coordinate (supply_1) -- (2,2.1)
  coordinate (supply_2) node[right] {};
  \draw[demand] (0,2.3) coordinate (demand_1) --
           (2,0.3) coordinate (demand_2) node[right] {};
  \draw[dashed line]
  (0.6,1.7) node[dot]{} -- (0.6,0) node[below]{$Q_D$};
  \draw[dashed line]
  (1.6,1.7) node[dot]{} -- (1.6,0) node[below]{$Q_S$};
  \draw[dashed line]
  (0,1.7) node[left]{$p_{\textrm{world},1}$}  -- (2.3,1.7);

  \draw[fill=red, fill opacity=0.3]
  (0,0.1) -- (1.6,1.7) -- (0,1.7);

  \draw[fill=blue, fill opacity=0.3]
  (0,2.3) -- (0.6,1.7) -- (0,1.7);

  \draw[pattern=north west lines, pattern color=brown] (1.1,1.2) -- (0.6,1.7) -- (1.6,1.7);

  \draw[decorate,decoration={brace},thick] (0.6,1.75) -- (1.6,1.75);
  \node[above] at (1.1,1.85) {export};

    \node[blue,right] at (0,1.85) {CS};
    \node[red,right] at (0,1.3) {PS};

    \node[brown,above] at (1.1,1.4) {WFG};

  %\fill[red] (0,1) -- (1,1) -- (0,0);


  \begin{scope}[xshift=4cm]

  % axis
  \draw[axis,<->] (2.5,0) node(xline)[right] {quantity $Q$} -|
  (0,2.5) node(yline)[above] {price $p$};
  % demand-supply diagram
  \draw[supply] (0,0.1) coordinate (supply_1) -- (2,2.1)
  coordinate (supply_2) node[right] {};
  \draw[demand] (0,2.3) coordinate (demand_1) --
           (2,0.3) coordinate (demand_2) node[right] {};
  \draw[dashed line]
  (0.6,0.7) node[dot]{} -- (0.6,0) node[below]{$Q_S$};
  \draw[dashed line]
  (1.6,0.7) node[dot]{} -- (1.6,0) node[below]{$Q_D$};
  \draw[dashed line]
  (0,0.7) node[left]{$p_{\textrm{world},2}$}  -- (2.3,0.7);

  \draw[fill=red, fill opacity=0.3]
  (0,0.1) -- (0.6,0.7) -- (0,0.7);

  \draw[fill=blue, fill opacity=0.3]
  (0,2.3) -- (1.6,0.7) -- (0,0.7);

  \draw[pattern=north west lines, pattern color=brown] (1.6,0.7) -- (0.6,0.7) -- (1.1,1.2);

  \draw[decorate,decoration={brace},thick] (1.6,0.65) -- (0.6,0.65);
  \node[below] at (1.1,0.65) {import};

    \node[blue,right] at (0,1.3) {CS};
    \node[red,right] at (0,0.5) {PS};

    \node[brown,above] at (1.1,0.75) {WFG};

  %\fill[red] (0,1) -- (1,1) -- (0,0);

  \end{scope}
\end{tikzpicture}


\end{frame}




\begin{frame}
  \frametitle{Lecture 4: Electricity grids: technical overview}

%https://upload.wikimedia.org/wikipedia/commons/thumb/4/41/Electricity_grid_simple-_North_America.svg/640px-Electricity_grid_simple-_North_America.svg.png

  Grid takes electricity from generators to consumers.  Long distance
  transport: \alert{transmission network} at high voltages ($>$ 110
  kV). Shorter distance transport: \alert{distribution network} at
  lower voltages ($\leq$ 110 kV). In houses usually $230~V$.

  \vspace{.5cm}

  \centering
  \includegraphics[width=14cm]{Electricity_grid_simple-_North_America}


  \source{Wikipedia}
\end{frame}




\begin{frame}
  \frametitle{Lecture 4: Electricity grids: technical overview}

  The European transmission network is mostly at 220~kV (green) and 380~kV (red). Purple lines are undersea high voltage direct current (HVDC) cables.

  The capacity of each transmission line is \alert{constrained} because of thermal and voltage limits.

\centering
\includegraphics[width=8cm]{europe-transmission}
\source{ENTSO-E}


\end{frame}



\begin{frame}
  \frametitle{Lecture 4: What happens when things go wrong}

  In November 2006, the continental European system split into three parts. Since before the split 10~GW was being transfered from East to West, in the West there was a generation deficit, which caused a frequency drop, while in the East there was an oversupply, causing a frequency spike.

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

  \includegraphics[width=7cm]{grid_split}
  \end{column}

  \begin{column}{7cm}

  \includegraphics[width=7cm]{frequency_after_grid_split}

  \end{column}
\end{columns}

\source{\hrefc{https://www.entsoe.eu/fileadmin/user_upload/_library/publications/ce/otherreports/Final-Report-20070130.pdf}{UCTE 2006 Report}}

\end{frame}



\begin{frame}
  \frametitle{Questions we want to answer}
  \begin{itemize}
  \item How can we take account of trade between regions in electricity markets?
  \item How do we deal with grid constraints between regions?
  \item How do we deal with grid constraints within regions?
  \item What incentives are there for grid operators to expand their networks?
  \item How do we incentivise the provision of grid services (frequency regulation, voltage stability, black start capability, covering resistive losses)?
  \end{itemize}

\end{frame}



\section{Trading Between Regions}


\begin{frame}
  \frametitle{Existing bidding zones}

\begin{columns}[T]
  \begin{column}{5cm}

    \includegraphics[width=5.8cm]{european_bidding_zones.png}
  \end{column}

  \begin{column}{8cm}

    \begin{itemize}
    \item Bids for German electricity take place in a \alert{bidding zone} encompassing both Germany and Luxembourg (Austria was separated from the German bidding zone in October 2018)
    \item Other countries have their own bidding zones or are \alert{split} into several bidding zones (see Nordic countries and Italy)
    \item This means that transmission constraints are only visible to the market at the \alert{borders} between the bidding zones
    \item Internal transmission constraints are \alert{ignored} - market bids are handled as if they do not exist (see next section on congestion management)
    \end{itemize}

\end{column}
\end{columns}


\end{frame}


\begin{frame}
  \frametitle{European single market for electricity}

    \alert{Goal:} Creation of a single market for electricity in Europe.

    \alert{Benefits are numerous:}
    \begin{itemize}
    \item \alert{Increase in overall welfare} since low-cost regions can export to high-cost regions
    \item \alert{Level out price differences} between bidding zones
    \item \alert{Strengthen competition} between suppliers
        \item \alert{Economies of scale} for power plants
        \item Improve \alert{system integration} of variable RES (balance variable feed-in over larger area, allow integration of best wind and solar sites)
    \item Improve \alert{network security} by sharing system service resources (e.g. control power)
    \item \alert{Backup generation} available in case of a power plant failure
    \item More \alert{uniform aggregated load} leads to more regular power
      plant operation
    \end{itemize}
\end{frame}

\begin{frame}
  \frametitle{European single market for electricity}
    \alert{But:} Technical constraints lead to \alert{congestion}.

    Congestion occurs when a market transaction between two regions is limited by the technical exchange capacity between the regions.


    Adequate allocation of the scarce resource of transmission capacity is called \alert{congestion management}.

    \alert{Pre-emptive measures}:
    \begin{itemize}
    \item \alert{Explicit auctions} of capacity between bidding zones
    \item \alert{Implicit auctions} of capacity between bidding zones
    \end{itemize}
    \alert{Curative measures}:
    \begin{itemize}
    \item \alert{Redispatch} of power plants within the bidding zones
    \end{itemize}
\end{frame}



\begin{frame}
  \frametitle{Capacity constraints between bidding zones}

  \begin{columns}[T]
  \begin{column}{7.5cm}
    \includegraphics[height=7.5cm]{interconnection_lines.png}
  \end{column}
  \begin{column}{6.5cm}
    \begin{itemize}
    \item \alert{Capacity constraints} between bidding zones are determined for each border depending on capacities at the border and any other limiting transmission lines inside each bidding zone
    \item Capacities can be \alert{different} in different directions (exports versus imports)
    \item Some borders have alternating current (AC) and some direct current (DC)
    \item Central and Western Europe has more advanced \alert{flow-based market coupling}
    \end{itemize}
  \end{column}
  \end{columns}

  \source{ENTSO-E, 2017}

\end{frame}
\begin{frame}
  \frametitle{Trade among different bidding zones}
  \begin{itemize}
  \item If the price between two or more bidding zones is not the same, \alert{arbitrage} is possible (buying power in the lower-cost zone and selling it in the higher-cost zone)
  \item If there is no limit on trade, prices will \alert{equalise}
  \item However, trade is typically \alert{limited by interconnection capacity}
    \item If the interconnection capacity is limited, prices may not equalise, giving rise to \alert{congestion rent}, which is the price difference multiplied by the flow of electricity between the regions
  \end{itemize}
\end{frame}


\begin{frame}
  \frametitle{Trading without congestion caused by transmission constraints}

  Before trading, the price in Market A, $PA$, is lower than that in Market B, $PB$.

  After trading, Market A exports to B and the prices equalise $PA^* = PB^*$.

  \centering
  \includegraphics[height=6.5cm]{trading-no_congestion.png}

\end{frame}


\begin{frame}
  \frametitle{Trading with congestion caused by transmission constraints}

  If a transmission line causes a capacity constraint that limits price arbitrage, prices converge but do not equalise. We have \alert{congestion}. The product of the flow and the price difference is the \alert{congestion rent}, $\Delta P \cdot F$. (ATC is the \alert{Available Transmission Capacity}.)

  \centering
  \includegraphics[height=6.5cm]{trading-congestion.png}
\end{frame}



\begin{frame}
  \frametitle{Prices over time}

  Trading will cause prices to converge over time.

  \centering
  \includegraphics[height=6.5cm]{price_before_after_trade.png}

\end{frame}

\begin{frame}
  \frametitle{Example: two nodes with completely inelastic demand}

  Now consider the connection of two nodes $i$ with their own electricity supply
  curves $P_i(Q_i)$ and \alert{completely inelastic demand} (i.e. a vertical
  demand curve) $Q_i^B$, with a line with capacity $K$.



  \vspace{0.5cm}

  \centering
  \begin{tikzpicture}

    \fill[black] (0,2) circle (0.5);
    \draw[thick,->] (0.5,2) -- (6.5,2);
    \fill[black] (7,2) circle (0.5);
    \node[text width=4.5cm] at (1,0.3)
        {Node 1 \\demand: $Q_1^B$ = 500 MW \\supply: $P_1(Q_1) = 10 + 0.01 \cdot Q_1$};
    \node[text width=4.5cm] at (8,0.3)
        {Node 2 \\demand: $Q_2^B$ = 1500 MW \\supply: $P_2(Q_2) = 13 + 0.02 \cdot Q_2$};
    \node[text width=3cm] at (3,2.3)
        {$|F| \leq K$};
  \end{tikzpicture}

  \vspace{0.5cm}

  \raggedright
  Note that electricity is cheaper at node 1 than node 2.

  We can determine the flow exported from node 1 and imported to node 2:
  \begin{equation*}
    F = Q_1 - Q_1^B = Q_2^B - Q_2
  \end{equation*}

  \source{Strbac \& Kirschen}

\end{frame}

\begin{frame}
  \frametitle{Case 1: no transmission capacity $K=0$}

  First suppose there is no transmission capacity between the nodes, $K=0$. This is the same as having separate markets.

  For each node $i$ we have demand equal to supply
  \begin{equation*}
    Q_i = Q_i^B
  \end{equation*}

  The price at each node is set by the intersection of the (vertical) demand curve and the supply curve.

  For the first node $Q_1^B = 500$ so the price is
  \begin{equation*}
    P_1(Q_1^B) = P_1(500) = 10 + 0.01 \cdot 500 = 15
  \end{equation*}

  For the second node $Q_2^B = 1500$ so the price is
  \begin{equation*}
    P_2(Q_2^B) = P_2(1500) = 13 + 0.02 \cdot 1500 = 43
  \end{equation*}

  \source{Strbac \& Kirschen}

\end{frame}

\begin{frame}
  \frametitle{Case 1: no transmission capacity $K=0$}

  We can draw this on a single graph by plotting the supply curve for node 1 from the left axis, and the supply curve from node 2 from the right axis. We will always have (regardless of transmission)
  \begin{equation*}
    Q_1^B + Q_2^B = Q_1 + Q_2 = 2000
  \end{equation*}

  \centering
  \includegraphics[width=8cm]{strbac_separate_markets-ee.pdf}

  \source{Strbac \& Kirschen}
\end{frame}


\begin{frame}
  \frametitle{Case 2: unlimited transmission capacity $K=\infty$}

  Now suppose there is unlimited transmission, so that the two markets merge. Now there is a single demand $Q_1 + Q_2 = 2000$ and a single clearing price. The generators adjust their output until the prices equalise:
  \begin{equation*}
    P_1(Q_1) = P_2(Q_2) = P_2(2000 - Q_1)
  \end{equation*}
  We solve this to find $Q_1$:
  \begin{equation*}
    10 + 0.01 \cdot Q_1 = 13 + 0.02 \cdot (2000 - Q_1)
  \end{equation*}
  $\Rightarrow$ $0.03\cdot Q_1 = 43$ $\Rightarrow$ $Q_1 = 1433$~MW, $Q_2 = 2000 - Q_1 = 567$~MW and the common clearing price is $P = P_1(Q_1) = P_2(Q_2) = 24.33$~\euro/MWh.
  \source{Strbac \& Kirschen}
\end{frame}


\begin{frame}
  \frametitle{Case 2: unlimited transmission capacity $K=\infty$}

  We can draw this on our graph, but now the transmission means $Q_i \neq Q_i^B$ since node 1 exports electricity to node 2. The power flow $F$ from node 1 to 2 is
  \begin{align*}
  F &= \left(Q_{1}-Q_{1}^B\right) = - \left(Q_{2}-Q_{2}^{B}\right) = \left(1433 - 500\right) = - \left(567 - 1500\right) = 933
\end{align*}

  \centering
  \includegraphics[width=8cm]{strbac_single_market-ee.pdf}

  \source{Strbac \& Kirschen}
\end{frame}


\begin{frame}
  \frametitle{Case 2: constrained transmission capacity $K=400$~MW}

  Now suppose the transmission capacity is less than the power flow occuring for a single market with unconstrained transmission. The (cheaper) generators at node 1 export power until the line is \alert{congested}. The (more expensive) generators then cover the remaining load at node 2.

  We find two separate prices:
\begin{align*}
P_1(Q_1^B+K) = P_1(500+400) = 10 + 0.01\cdot 900 = 19\\
P_2(Q_2^B-K) = P_2(1500-400) = 13 + 0.02\cdot 1100 = 35
\end{align*}
This leads to $Q_1 = 900$~MW, $P_1 = 19$~\euro/MWh, $Q_2=1100$~MW, $P_2 = 35$~\euro/MWh and flow equal to capacity $F = K = 400$~MW.

\end{frame}

\begin{frame}
  \frametitle{Case 2: constrained transmission capacity $K=400$~MW}

  The \alert{congestion rent} is now visible in the middle (flow times price difference), since there is welfare which is neither generator nor consumer surplus.

  This money goes to the network operator for providing the arbitrage opportunity via the network.


  \centering
  \includegraphics[width=8cm]{strbac_constrained_market-ee.pdf}

\end{frame}


\begin{frame}{Outcomes for different values of transmission capacity $K$}


\begin{columns}[T]
  \begin{column}{5cm}

    \centering
    $K=0, F = 0,$\\
    $Q_1^* = 500, Q_2^* = 1500$

   \includegraphics[width=4.3cm]{strbac_separate_markets-ee.pdf}
  \end{column}
  \begin{column}{5cm}

    \centering
    $K=\infty, F = 933$\\
    $Q_1^* = 1433, Q_2^* = 567$

  \includegraphics[width=4.3cm]{strbac_single_market-ee.pdf}
  \end{column}

\end{columns}
  \centering

  $K=400, F = 400$\\
  $Q_1^* = 900, Q_2^* = 1100$

  \includegraphics[width=4.3cm]{strbac_constrained_market-ee.pdf}

\end{frame}


\begin{frame}{Example: Summary}
  \ra{1.1}
  \begin{table}[!t]
    \begin{tabular}{lrrr}
      \toprule
        & 1: Separate markets &  2: Single market & 3: Constrained market \\
      \midrule
      $Q_1^B$ [MW] & 500 & 500 & 500 \\
      $Q_1$ [MW] & 500 & 1433 & 900 \\
      $P_1$ [\euro/MWh] & 15 & 24.33 & 19 \\
$Q_2^B$ [MW] & 1500 & 1500 & 1500 \\
     $ Q_2$ [MW] & 1500 & 567 & 1100\\
      $P_2$ [\euro/MWh] & 43 & 24.33 &  35 \\
      $F_{1\to 2}$ [MW] & 0 & 933 & 400\\
      $\sum_{i}P_{i}\times Q_i$ [\euro/h] & 72000 & 48660 &  55600  \\
      $\sum_{i}P_{i}\times Q_i^B$ [\euro/h] & 72000 & 48660 & 62000 \\
      $(P_2-P_1)*F_{1\to 2}$ [\euro/h] & 0 & 0 & 6400 \\
      \bottomrule
    \end{tabular}
  \end{table}

  \end{frame}


\begin{frame}{Congestion rent}
Due to the congestion of the transmission line, the marginal cost of producing electricity is different at node 1 and node 2. The competitive price at node 2 is higher than at node 1.

Since consumers pay and generators get paid the price in their local market, in case of congestion there is a difference between the total payment of consumers and the total revenue of producers -- this is the \alert{merchandising surplus} or \alert{congestion rent}, collected by the transmission system operator. For each line it is given by the price difference in both regions times the amount of power flow between them:
\begin{align*}
\text{Congestion rent =}\:\Delta P\times F
\end{align*}


\end{frame}


\begin{frame}{Example: Congestion rent for different values of $K$}

  The congestion rent for the two-node example is given by
  \begin{equation*}
    \textrm{Congestion rent} = | P_1 - P_2 | \times |F|
  \end{equation*}

  It is also the difference between consumer payments and generator revenues.

  As a function of $K$ it reaches a maximum between the two extremes of no capacity and unlimited capacity:

  \centering
  \includegraphics[width=7cm]{kirschen-congestion-K.png}
\end{frame}



\begin{frame}
  \frametitle{Crossborder transmission capacity trading in practice}

\alert{Goal:} efficient allocation of cross-border transmission capacities in
order to optimise social welfare.

\alert{Explicit auction:} transmission rights are auctioned separately and
independently from the electricity market.
    \begin{itemize}
    \item annual, monthly and daily auctions
    \item bilaterally or via exchange
    \end{itemize}

\alert{Implicit auction:} transmission rights and energy are coupled and
traded simultaneously (i.e. buyers bid for electricity supplied by
generators from the neighbouring market area). The price per area
reflects both the cost of energy and congestion.
    \begin{itemize}
    \item via exchange
    \end{itemize}
\end{frame}


\begin{frame}
  \frametitle{Explicit auction}

  In explicit auctions, traders sell/buy electricity and capacity separately.

  \vspace{1cm}

  \centering  \includegraphics[width=10cm]{explicit_auction.png}


\end{frame}

\begin{frame}
  \frametitle{Implicit auction}

  In an implicit auction, the market clearing and use of interconnection capacity is determined \alert{simultaneously} in an algorithm which \alert{optimises overall social welfare}. In Europe for the day ahead market this algorithm is called EUPHEMIA.

  \vspace{.5cm}

  \centering
  \includegraphics[width=10cm]{implicit_auction.png}


\end{frame}

\begin{frame}
  \frametitle{Trend from explicit to implicit auction}

\begin{columns}[T]
  \begin{column}{9.8cm}

\includegraphics[width=10.5cm]{coupling_over_time.png}
  \end{column}
  \begin{column}{4.2cm}

    \begin{itemize}
    \item Top left: day-ahead coupling in 2003.
    \item Top right: day-ahead coupling in 2007.
    \item Bottom left: day-ahead coupling in 2021 (borders in yellow not coupled).
    \item Bottom right: intraday coupling over time.
    \end{itemize}
  \end{column}
\end{columns}
\source{\href{https://doi.org/10.3390/en14134051}{Schittekatte et al, 2021}}
\end{frame}

\section{Redispatch}

\begin{frame}
  \frametitle{The Problem: Congestion inside bidding zones}

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

\includegraphics[width=8cm]{europe-transmission}
\source{ENTSO-E}
  \end{column}
  \begin{column}{6.5cm}

    \begin{itemize}
    \item  The country-sized and regional bidding zones ignore congestion \alert{inside} the bidding zones.
     \item The bidding zone is defined by assuming no congestion inside its borders.
     \item    However, the resulting market dispatch can still lead to violations of transmission capacity inside the zone.
       \item Counter-measures: \alert{redispatch} outside the market.
    \end{itemize}
  \end{column}
\end{columns}

\end{frame}

\begin{frame}
  \frametitle{The problem is exacerbated by wind and solar}

  Renewables are not always located near demand centres, as in this example from Germany.



\begin{columns}[T]
  \begin{column}{6cm}
\includegraphics[width=6cm]{scigrid-load}
  \end{column}

  \begin{column}{6cm}
      % left bottom right top
  \includegraphics[trim=0 0cm 0 1cm,width=6.3cm,clip=true]{scigrid-wind}


\end{column}
\end{columns}

\end{frame}



\begin{frame}
  \frametitle{The problem}



\begin{columns}[T]
  \begin{column}{5.5cm}
        \vspace{.5cm}
\includegraphics[width=6cm]{scigrid-loading}
  \end{column}

  \begin{column}{6cm}
    \begin{itemize}
      \item This leads to \alert{overloaded lines} in the middle of Germany, which
   cannot transport all the wind energy from North Germany to the load
   in South Germany

   \item It also overloads lines in neighbouring countries due to
     \alert{loop flows} (unplanned physical flows `according to least
     resistance' which do not correspond to traded flows)

     \item It also \alert{blocks imports and exports} with
       neighbouring countries, e.g. Denmark

    \end{itemize}

\end{column}
\end{columns}

\end{frame}


\begin{frame}
  \frametitle{Scheduled market flows versus physical flows}



\begin{columns}[T]
  \begin{column}{9cm}
\includegraphics[width=9cm]{physical-vs-scheduled-flows.png}
  \end{column}
  \begin{column}{5cm}

   \vspace{1cm}

    Power traded between
  zones (``scheduled flows'', red) does not always correspond to what flows
  according to the network physics (``physical flows'', blue). This
  leads to political tension as wind from Northern Germany flows to Southern Germany via Poland and the Czech Republic as a \alert{loop flow} rather than flowing inside Germany as intended.

  \end{column}

\end{columns}

\source{\hrefc{https://blog.energybrainpool.com/en/physical-flows-vs-commercial-schedules-in-cross-border-power-trading/}{Energy Brainpool, 2017}}
\end{frame}

\begin{frame}
  \frametitle{Solution 1: Redispatch after energy market clearing}

  These problems are \alert{not visible} in the day-ahead electricity
  market, which treats the whole of Germany as a single
  bidding zone. It dispatches wind in North Germany as if there was no
  internal congestion...

  To ensure that the physical limits of transmission are not exceeded,
  the network operator must \alert{`re-dispatch'} power stations and
  \alert{curtail} (Einspeisemanagement) renewables to restore order.
  This is \alert{costly} (0.8 redispatch + 0.6 RE-compensation = 1.4 billion
  EUR in 2017 - although exceptional circumstances in 1st quarter) and
  results in \alert{lost CO$_2$-free generation} (5.5 TWh curtailment of RE
  and CHP in 2017).

  \alert{International redispatch} is sometimes also required
  (Multilateral Remedial Actions = MRA).

  Furthermore, there are \alert{no market incentives} to reinforce the North-South
  grid, to locate more power stations in South Germany or to
  build storage / P2X in North Germany.

\end{frame}

\begin{frame}
  \frametitle{Redispatch}
  \centering
  \includegraphics[width=14cm]{redispatch.png}

  \source{Next Kraftwerke}
\end{frame}

\begin{frame}
  \frametitle{Redispatch in Germany: Trend}

  \centering
\includegraphics[width=11cm]{Volume-and-expenditures-for-redispatch-and-curtailment-from-2015-to-2019-in-Germany_W640.jpg}

\source{\hrefc{https://doi.org/10.1016/j.apenergy.2020.116201}{Xiong et al (2021)}}
\end{frame}



\begin{frame}
  \frametitle{Redispatch 2.0}

  From October 2021 redispatch was reformed in Germany in NABEG 2.0. Before it was distinguished between redispatch (for conventional power stations) and curtailment (for renewables and CHP).

  The goal of the new legislation is:
  \begin{itemize}
  \item To put conventionals and renewables on same footing (both can participate in redispatch)
    \item Also involve units attached to the distribution grid (units above 100~kW or those already that can be controlled)
  \end{itemize}

\end{frame}

\begin{frame}
  \frametitle{Solution 1b: Measures involving multiple bidding zones}

  Sometimes redispatch actions within the bidding zone are not sufficient.

  Here there are two options (much rarer than redispatch):
  \begin{itemize}
  \item \alert{Counter-trading}: Transmission system operators buy power in one bidding zone and sell in another on the power exchanges to reduce a bottleneck either on the border or inside the bidding zone.
  \item \alert{Multilateral Remedial Action (MRA)}: Post-market redispatch involving multiple bidding zones.
  \end{itemize}


\end{frame}

\begin{frame}
  \frametitle{Solution 2: Grid expansion within bidding zones}

\begin{columns}[T]
  \begin{column}{7cm}
\includegraphics[height=7.5cm]{grid-extensions.png}
  \end{column}
  \begin{column}{7cm}
    \begin{itemize}
      \item Relieve congestion by expanding capacities inside the bidding zone
      \item Investment increases money TSOs can claim via network fee on consumers
      \item Regulator (Bundesnetzagentur) must approve the grid expansion plans
    \end{itemize}
  \end{column}

\end{columns}

\source{BNetzA, 2019}

\end{frame}

\begin{frame}
  \frametitle{Solution 3: Smaller bidding zones to ``see'' congested boundaries}


\begin{columns}[T]
  \begin{column}{5cm}
\includegraphics[width=6cm]{nordel.png}
  \end{column}
  \begin{column}{5cm}
    \begin{itemize}
      \item In Scandinavia they have solved this by introducing \alert{smaller bidding zones}
      \item Now congestion at the boundaries between zones is taken
        into account in the \alert{implicit auctions} of the market
      \item This is also done in Italy (again, a long country),
          where prices for small consumers are \alert{uniformised} for fairness
    \end{itemize}

\end{column}
\end{columns}


\end{frame}



\begin{frame}
  \frametitle{Solution 4: Nodal pricing}


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

    \vspace{.5cm}
\includegraphics[width=7cm]{lmp.png}
  \end{column}
  \begin{column}{5cm}
    \begin{itemize}
    \item The ultimate solution, as used in the US and other markets,
      is \alert{nodal pricing}, which exposes all transmission congestion
    \item Considered too complex and subject to market power to be
      used in Europe, but this is questionable...
      \item Here we see clearly why many argue for a North-South
        German split
    \end{itemize}

\end{column}
\end{columns}



\end{frame}




\begin{frame}
  \frametitle{First step: Split Germany North-South}


\begin{columns}[T]
  \begin{column}{5cm}
    \vspace{.5cm}
\includegraphics[width=5.2cm]{DE_split.png}
  \end{column}
  \begin{column}{6cm}

    \vspace{.7cm}
    \begin{itemize}

    \item Initial price difference could average up to 12 EUR/MWh
    \item Prices would converge with more network expansion
    \item Redispatch costs reduced by 39\% in 2025, 58\% in 2035 (assuming NEP 2030 transmission projects get built)
    \item Politically difficult, may require, like Italy, uniformised
      price on consumer side
    \end{itemize}
  \end{column}
\end{columns}

\source{\href{https://www.strommarkttreffen.org/2018-02_Fraunholz&Hladik_Zwei_Preiszonen_in_D.pdf}{Fraunholz \& Hladik, 2018}}
\end{frame}



\begin{frame}
  \frametitle{Solution 1.5: Flow-based market coupling}

  Flow-based market coupling can be used in zonal markets to see
  precise individual line constraints, instead of ``boxing'' the feasible space
  like ATC/NTC schemes do.

  \centering \includegraphics[width=13cm]{fbmc}

  \source{Van den Bergh, Boury, Delarue}
\end{frame}

\begin{frame}
  \frametitle{Solution 1.5: Flow-based market coupling}

\begin{columns}[T]
  \begin{column}{6cm}
    \vspace{.5cm}
    \includegraphics[height=7cm]{core-fbmc.png}
  \end{column}
  \begin{column}{7cm}
    \begin{itemize}
    \item   From May 2015 to early 2022 flow-based market coupling was only applied in Germany, France, Netherlands, Belgium and Luxembourg
      \item From mid-2022 it has been extended across northern `Core' countries in continental Europe
    \end{itemize}
  \end{column}
\end{columns}
\source{\hrefc{https://www.jao.eu/core-fb-mc}{JAO Core FBMC}}
\end{frame}

\section{Balancing Power}

\begin{frame}
  \frametitle{System services}

  \alert{System services} are provided by the Transmission System Operator to
  maintain the stability of the grid for electricity market transactions.  They include:
  \begin{itemize}
  \item Frequency control
  \item Voltage control
  \item Black-start capacities for grid restoration after black-outs
    \item Compensation for transmission losses
\item Cross-border interconnection management
  \end{itemize}

General modes of provision:
  \begin{itemize}
  \item Compulsory
  \item Bilateral
\item Tendering
\item Wholesale market
  \end{itemize}

\end{frame}

\begin{frame}
  \frametitle{Markets for frequency control power}

  Control power markets provide frequency control.

  Frequency is determined by \alert{balance of supply and demand}.

  Target frequency in Europe: 50 Hz (in other parts of world, like US, it is 60 Hz)

  Excessive demand $\to$ frequency drops $\to$ \alert{positive} balancing energy is procured by TSO

  Excessive generation $\to$ frequency rises $\to$ \alert{negative} balancing energy is procured by TSO

  \centering
  \includegraphics[width=10cm]{scalespicture.jpg}
\end{frame}



\begin{frame}
  \frametitle{Markets for frequency control power}

  Power is scheduled in Germany on a 15-minute basis. For deviations
  from the schedule, \alert{positive} control power is needed for an excess of
  demand, \alert{negative} for an excess of generation.

  \vspace{.5cm}

  \centering
  \includegraphics[width=13.5cm]{csm_ausgangslage_0c61355339.png}

  \source{\hrefc{https://www.a1energysolutions.at/regelenergie-pool/}{A1 Energy Solutions}}

\end{frame}


\begin{frame}
  \frametitle{Different types of control power}

  Control power is distinguished by how fast it acts.

  Old terminology: \alert{primary} for fast-acting, through \alert{tertiary} for slow-acting.

  \centering
  \includegraphics[width=14cm]{primary-secondary.jpg}

    \source{BNetzA}

\end{frame}

\begin{frame}
  \frametitle{Different types of control power}

  Example activation during frequency excursion.  New terminology: \alert{FCR}: Frequency Containment Reserve (primary), \alert{aFRR}: automatic Frequency Restoration Reserve (secondary), \alert{mFRR}: manual Frequency Restoration reserve (tertiary).

  \centering
  \includegraphics[width=11cm]{frr.png}

  \source{ENTSO-E, 2018}
\end{frame}

\begin{frame}
  \frametitle{Utilisation of control power}

    \centering
    \includegraphics[height=7cm]{use_of_control_power.png}

    \source{Georg Erdmann}
\end{frame}

\begin{frame}
  \frametitle{European balancing markets}

  European balancing target model has following goals:
  \begin{itemize}
  \item  Effective competition
    \item Non-discrimination
\item   Transparency
\item  Integration
  \end{itemize}

  European platforms and projects under development:
\begin{itemize}
  \item  IGCC, International Grid Control Cooperation – imbalance netting
  \item PICASSO, Platform for the International Coordination of Automated Frequency Restoration and Stable System Operation – aFRR
\item  MARI, Manually Activated Reserves Initiative – mFRR
\item  TERRE, Trans-European Restoration Reserves Exchange – RR
\end{itemize}
\end{frame}

\begin{frame}
  \frametitle{Markets for control power}

  TSOs procure balancing power from   \alert{Balance Service Providers (BSP)} in balancing markets. Energy cost is charged to balance group.

  \alert{Balance Service Providers (BSP)}: generators, demand response, storage.

  NB: Difference between system imbalance (global) and balance group imbalance (local).

  \centering
  \includegraphics[width=14cm]{markets_for_control_power.png}

  \source{ENTSO-E, 2018}
\end{frame}

\begin{frame}
  \frametitle{Markets for control power}

  Reserves are procured either via \alert{pay-as-clear} (marginal pricing) or \alert{pay-as-bid} auctions (you get paid what you bid). Only capacity is procured for FCR; for FRR both capacity and energy prices are procured in separate markets (since 2020). You don't have to be successful in the capacity market to bid in energy, but if you bid in capacity, you have to bid in energy.

    \begin{table}[!t]
    \begin{tabular}{rp{3.5cm}p{3.5cm}p{3.5cm}}
      \toprule
    &        FCR (primary) &  aFRR (secondary) & mFRR (tertiary / minute) \\
      \midrule
      activation & based on frequency & automatic by TSO & manual by TSO \\
      full power & within 30 seconds & within 5 minutes & within 15 minutes\\
        bids & symmetric & positive or negative & positive or negative \\
        min bid size & 1 MW & 5 MW & 5 MW\\
        auctions & 6*4 hour slices per day & 6*4 hour slices per day & 6*4 hour slices per day\\
        compensation & capacity only & capacity \& energy & capacity \& energy\\
        pay-as- & clear & bid (P), clear (E) & bid (P), clear (E) \\
      \bottomrule
    \end{tabular}
  \end{table}


\end{frame}

\begin{frame}
  \frametitle{Control power pay-as-bid auction}

  Because there are few players and concerns about oligopoly, i.e. market power, some
  control power markets use \alert{pay-as-bid}: you get paid what
  you bid rather than a uniform clearing price.

  In theory, pay-as-bid should result in lower costs than pay-as-clear (since actors bid close to variable cost), but in practice they raise bids to anticipate the marginal bid.
  FCR moved to pay-as-clear in 2019, in Summer 2022 aFRR and mFRR energy auctions are also pay-as-clear.

  \centering
  \includegraphics[height=5cm]{control_power_auction.png}

  \source{Next Kraftwerke}
\end{frame}

\begin{frame}
  \frametitle{Control power pay-as-bid auction}

  Reducing entry barriers are in focus of market design.

  \includegraphics[width=14cm]{control_power_provision.png}

  \source{Zweifel / Praktiknjo / Erdmann, 2017}
\end{frame}


\begin{frame}
  \frametitle{Control power tendered quantities in Germany}

  \centering
  \includegraphics[width=14cm]{control-reserve-2009-2022.png}

  \source{\hrefc{https://www.next-kraftwerke.com/knowledge/frequency-containment-reserve-fcr}{Next Kraftwerke}}
\end{frame}

\begin{frame}
  \frametitle{Cost allocation of control power}

  Distinguish between \alert{capacity price} for availability and \alert{energy price} for utilisation.

  \centering
  \includegraphics[height=7cm]{control_power_cost_allocation.png}

  \source{Erdmann}

\end{frame}


\begin{frame}
  \frametitle{Capacity spending on control power}

  The total spent on capacity auctions (ignoring energy) has declined significantly.

  \centering
  \includegraphics[width=14cm]{kosten-vorhaltung-regelenergie-NXK026.jpg}

  \source{\hrefc{https://www.next-kraftwerke.de/wissen/regelenergie}{Next Kraftwerke}}

\end{frame}


\section{Distribution Grids}


\begin{frame}
  \frametitle{German distribution grid}

  Definition of \alert{distribution grid} in Germany: everything below 220~kV. The distribution grid distributes electricity to and from the transmission grid, whereas the transmission grid transports it over long distances. Low voltage: $\leq 1$ kV, middle voltage: $3-30$ kV, high voltage: 110 kV. Ultra high voltage transmission: 220-380 kV.

  \centering
  \includegraphics[height=5.5cm]{german_distribution_grid.png}

  \source{\hrefc{https://www.bmwk.de/Redaktion/EN/Infografiken/Energie/verteilernetz.html}{BMWK}}
\end{frame}
\begin{frame}
  \frametitle{Energy transition in distribution grids}

  \centering
  \includegraphics[height=7cm]{distribution_grid_change.png}

  \source{$^2$ 50Hertz, Energiewende Outlook 2035, 2016; E-Bridge, MITNETZ Strom, 2016}
\end{frame}
\begin{frame}
  \frametitle{Energy transition in distribution grids}

  \begin{columns}[T]
  \begin{column}{7cm}
  More complexity for the Distribution System Operator (DSO):
  \begin{itemize}
    \item Congestion management
    \item Voltage control
     \item Smart meters to enable both dynamic tariffs and network-oriented control of assets like heat pumps and electric vehicles
     \item Grid restoration after blackout
      \item (Frequency control – only in isolated systems)
  \end{itemize}

  \end{column}
  \begin{column}{7cm}
      \centering
  \includegraphics[height=7cm]{Electricity_Grid_Schematic_English.svg.png}
  \end{column}
\end{columns}
\end{frame}



\begin{frame}
  \frametitle{Smart meters}

  \begin{columns}[T]
  \begin{column}{9cm}
  \begin{itemize}
    \item Old analogue electricity meters could only cumulate the total consumption (e.g. yearly)
    \item Modern \alert{smart meters} combine the ability to measure
      and store the (sub-)hourly consumption, enabling dynamic
      tariffs, but also allow communication through a gateway, e.g. to
      allow the grid operator to interrupt load
    \item German 2023 law requires all customers to have the option to install
      a smart meter with dynamic tariff from 2025 (``soweit technisch machbar und wirtschaftlich zumutbar'')
    \item By 2032 all customers with demand $>6000$ kWh/a (i.e. those with heat pumps or electric vehicles) are required to have one
  \end{itemize}

  \end{column}
  \begin{column}{5cm}
      \centering
  \includegraphics[height=7cm]{Intelligenter_zaehler-_Smart_meter.jpg}
  \end{column}
  \end{columns}
  \source{\hrefc{https://en.wikipedia.org/wiki/Smart_meter}{Wikipedia}}
\end{frame}



\begin{frame}
  \frametitle{Smart meter rollout in Germany}

  Although $\sim 20$\% of Germany's 50 million metering locations are modern $\Rightarrow$ measure hourly
  demand, in 2021 only 160,000 had smart
  meter gateway for communication.

  \centering
  \includegraphics[height=6cm]{smart_meter_rollout-2021.png}
  
  \source{\hrefc{https://www.ffe.de/en/publications/the-smart-meter-rollout-in-germany-and-europe/}{FfE, 2023}}
\end{frame}

\section{Network Fees}

\begin{frame}
  \frametitle{Grid as monopoly}

  Grid operation is a \alert{natural monopoly}, as network infrastructure is prohibitively costly to replicate.

  As any monopoly, it is prone to eliminating newcomers (potential competition for affiliated generation/retail unit) by overcharging or denying technical feasibility.

  Good \alert{regulation} should guarantee:
  \begin{itemize}
  \item   \alert{Non-discriminatory third-party access} (i.e. of generators and consumers)
\item    \alert{Transparency}
\item  \alert{Cost recovery} (so network operator doesn't go bankrupt)
\item   \alert{Cost reflectiveness} (clear connection between charges and actual costs)
  \end{itemize}

  \source{Lévêque, 2010}
\end{frame}


\begin{frame}
  \frametitle{Composition of grid tariffs}

  Grid tariffs must cover the following expenses of grid operators:
\begin{itemize}
  \item Operation and Maintenance (O\&M)
\item  Grid extension
\item  Control power (capacity component)
\item  Feed-in management (Einsman)
\item  Redispatch
\item   Grid reserve (capacity held for redispatch in South)
\item  Capacity reserve (for peak capacity, cannot participate in energy market now or ever)
\item  Security reserve (coal/climate reserve)
\item  Reactive power
\item   Grid losses
\item  Other
\end{itemize}
\end{frame}


\begin{frame}
  \frametitle{Most network costs are at the distribution grid level}

  \centering
  \includegraphics[height=7.4cm]{ausgaben-strom-2022.png}

  \source{\hrefc{https://www.bmwk.de/Redaktion/DE/Publikationen/Energie/monitoringbericht-expertenkommission-zum-energiewende-monitoring.html}{Monitoring-Kommission, 2024}}
\end{frame}

\begin{frame}
  \frametitle{Grid tariff regulation: Regulation approaches}

  \centering
  \includegraphics[width=12cm]{grid_regulatory_approach.png}

\end{frame}



\begin{frame}
  \frametitle{Incentive regulation in Germany}

  \begin{itemize}
    \item 5-year regulatory period (current period 2019-2024)
  \item  Revenue that TSO/DSO is allowed to earn is fixed for the regulatory period at a level.
  \item Revenue cap: total cost + depreciation + return on equity
  \item Investment costs into grid extension are allowed above cap.
  \end{itemize}

  Costs:
  \begin{itemize}
    \item permanently non-controllable
\item temporarily non-controllable
\item controllable
\item volatile
  \end{itemize}

  \alert{Efficiency benchmarking} - based on cost examination and structural data validation of individual TSO/DSO.
The most efficient entity serves as benchmark.
\end{frame}


\begin{frame}
  \frametitle{Future of network fees in Germany}

  The energy transition changes the role of network fees.
  
  \begin{itemize}
  \item Network fees need to \alert{incentivise flexible demand} rather than hindering it.
  \item Can consider time-varying network fees, like the time-varying wholesale electricity price. Currently flexibility is often penalised; e.g. large industrial consumers ($\sim 20$\% of German demand) get a discount of up to 90\% if they have a smooth consumption for at least 7000 hours a year.
  \item Unlike other countries where generation also pays, in Germany only loads pay network fees. Distribution grid fees depend on local costs, so consumers in eastern Germany are unfairly burdened with costs for renewable connection. Need redistribution! BNetzA is working on it.
  \item Since costs are very high, there is some discussion about the government paying to reduce the fees. 
  \end{itemize}

\end{frame}
  

\section{Electricity Retail Markets}

\begin{frame}
  \frametitle{Retail competition}

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

    \vspace{.7cm}

    The ultimate rationale of liberalisation/restructuring of the
  electricity sector is the prospect of \alert{lower prices} for electricity
  consumers achievable through \alert{competition}.

    \vspace{.7cm}

  The option for final customer to \alert{switch supplier} creates a
  competitive pressure for market players along the electricity supply
  chain.

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

  \centering
  \includegraphics[height=7.5cm]{lieferantenwechsel-im-strommarkt.png}
  \end{column}
  \end{columns}

  \source{\hrefc{https://www.bdew.de/service/daten-und-grafiken/lieferantenwechsel-im-strommarkt/}{BDEW, 2023}}

\end{frame}

\begin{frame}
  \frametitle{Categories of suppliers in the German market}

  \begin{itemize}
  \item Remnants of large vertically integrated utilities: E.ON, RWE, Vattenfall,
  EnBW
  \item Municipal utilities (Stadtwerke Potsdam/München, etc.)
  \item Retailers with mixed ownership structure
  \item Small independent retailers
  \end{itemize}

  Typically supplier has Balance Responsible Party (BRP) role.

  Electricity retail markets are \alert{regional}: distribution network level.

  Default supplier (Grundversorger) is the designated supplier obliged to supply any
  customer in their supply area (in Germany: the entity supplying the
  largest number of grid connection points; in Berlin: Vattenfall).

  Apart from the baseline contract, the default supplier can offer
  alternative tariffs.
\end{frame}

\begin{frame}
  \frametitle{Categories of final customers}

\begin{itemize}
\item Residential
\item Commercial
\item Industrial
\end{itemize}

Household customers: up to 10,000 kWh yearly consumption
\begin{itemize}
\item residential \& small commercial
\item  standard load profile (SLP) - approximation
\end{itemize}

Non-household customers: all other
\begin{itemize}
\item commercial ($>$ 10,000 kWh yearly consumption) \& industrial
\item registered load profile measurement (RLM): $>$100 GWh p.a.
\end{itemize}
\end{frame}


\begin{frame}
  \frametitle{Retail price composition: household \& industry customers}

  Note the high fraction of regulated (Netzentgelte) and state-induced taxes and levies.

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

  \centering
  \includegraphics[width=7.5cm]{strompreis-f-r-haushalte.png}
  \end{column}
  \begin{column}{7cm}

  \centering
  \includegraphics[width=7.5cm]{strompreis-f-r-die-industrie-inkl.-stromsteuer-.png}
  \end{column}
  \end{columns}

  \source{\hrefc{https://www.bdew.de/service/daten-und-grafiken/bdew-strompreisanalyse/}{BDEW, 2023}}

\end{frame}

\end{document}
