diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 2ba11297f..b22224b5b 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -37,6 +37,8 @@ Change Log
 - [FIXED] :code:`convert_format.py`: update the attributes of the characteristic objects to match the new characteristic
 - [FIXED] additional arguments from mpc saved to net._options: create "_options" if it does not exist
 - [CHANGED] cim2pp: extracted getting default classes, added generic setting datatypes from CGMES XMI schema
+- [ADDED] function :code:`getOTDF` to obtain Outage Transfer Distribution Factors, that can be used to analyse outages using the DC approximation of the power system
+- [ADDED] function :code:`outage_results_OTDF` to obtain the matrix of results for all outage scenarios, with rows as outage scenarios and columns as branch power flows in that scenario
 
 
 [2.13.1] - 2023-05-12
diff --git a/pandapower/pypower/makeLODF.py b/pandapower/pypower/makeLODF.py
index 65d960b9c..97b5fc93e 100644
--- a/pandapower/pypower/makeLODF.py
+++ b/pandapower/pypower/makeLODF.py
@@ -66,3 +66,118 @@ def makeLODF(branch, PTDF):
     update_LODF_diag(LODF)
 
     return LODF
+
+
+def makeOTDF(PTDF, LODF, outage_branches):
+    """
+    Compute the Outage Transfer Distribution Factors (OTDF) matrix.
+
+    This function creates the OTDF matrix that relates bus power injections
+    to branch flows for specified outage scenarios. It's essential that
+    outage branches do not lead to isolated nodes or disconnected islands
+    in the grid.
+
+    The grid cannot have isolated nodes or disconnected islands. Use the
+    pandapower.topology module to identify branches that, if outaged, would
+    lead to isolated nodes (determine_stubs) or islands (find_graph_characteristics).
+
+    The resulting matrix has a width equal to the number of nodes and a length
+    equal to the number of outage branches multiplied by the total number of branches.
+    The dot product of OTDF and the bus power vector in generation reference frame
+    (positive for generation, negative for consumption - the opposite of res_bus.p_mw)
+    yields an array with outage branch power flows for every outage scenario,
+    facilitating the analysis of all outage scenarios under a DC
+    power flow approximation.
+
+    Parameters
+    ----------
+    PTDF : numpy.ndarray
+        The Power Transfer Distribution Factor matrix, defining the sensitivity
+        of branch flows to bus power injections.
+    LODF : numpy.ndarray
+        The Line Outage Distribution Factor matrix, describing how branch flows
+        are affected by outages of other branches.
+    outage_branches : list or numpy.ndarray
+        Indices of branches for which outage scenarios are to be considered.
+
+    Returns
+    -------
+    OTDF : numpy.ndarray
+        The Outage Transfer Distribution Factor matrix. Rows correspond to
+        outage scenarios, and columns correspond to branch flows.
+
+    Examples
+    --------
+    >>> H = makePTDF(baseMVA, bus, branch)
+    >>> LODF = makeLODF(branch, H)
+    >>> outage_branches = [0, 2]  # Example branch indices for outage scenarios
+    >>> OTDF = makeOTDF(H, LODF, outage_branches)
+    >>> # To obtain a 2D array with the outage results:
+    >>> outage_results = (OTDF @ Pbus).reshape(len(outage_branches), -1)
+
+    Notes
+    -----
+    - The function assumes a DC power flow model.
+    - Ensure that the specified outage branches do not lead to grid
+      disconnection or isolated nodes.
+    """
+    OTDF = np.vstack([PTDF + LODF[:, [i]] @ PTDF[[i], :] for i in outage_branches])
+    return OTDF
+
+
+def outage_results_OTDF(OTDF, Pbus, outage_branches):
+    """
+    Calculate the branch power flows for each outage scenario based on the given
+    Outage Transfer Distribution Factors (OTDF), bus power injections (Pbus), and
+    specified outage branches.
+
+    This function computes how branch flows are affected under N-1 contingency
+    scenarios (i.e., for each branch outage specified). It uses the OTDF matrix and
+    the bus power vector (Pbus) to determine the branch flows in each outage scenario.
+
+    Pbus should represent the net power at each bus in the generation reference case.
+
+    Parameters
+    ----------
+    OTDF : numpy.ndarray
+        The Outage Transfer Distribution Factor matrix, which relates bus power
+        injections to branch flows under specific outage scenarios. Its shape
+        should be (num_outage_scenarios * num_branches, num_buses).
+    Pbus : numpy.ndarray
+        A vector representing the net power injections at each bus. Positive values 
+        for generation, negative for consumption. Its length should be equal to 
+        the total number of buses.
+    outage_branches : numpy.ndarray
+        An array of indices representing the branches that are outaged in each
+        scenario. Its length should be equal to the number of outage scenarios.
+
+    Returns
+    -------
+    numpy.ndarray
+        A 2D array where each row corresponds to an outage scenario and each column
+        represents the resulting power flow in a branch. The number of rows is equal
+        to the number of outage scenarios, and the number of columns is equal to the
+        number of branches.
+
+    Examples
+    --------
+    >>> OTDF = np.array([...])  # example OTDF matrix
+    >>> Pbus = np.array([...])  # example bus power vector
+    >>> outage_branches = np.array([...])  # example outage branches
+    >>> branch_flows = outage_results_OTDF(OTDF,Pbus,outage_branches)
+
+    Notes
+    -----
+    The function assumes a linear relationship between bus power injections and
+    branch flows, which is typical in DC power flow models.
+    """
+    # get branch flows as an array first:
+    nminus1_otdf = (OTDF @ Pbus.reshape(-1, 1))
+    # reshape to a 2D array with rows relating to outage scenarios and columns to
+    # the resulting branch power flows
+    nminus1_otdf = nminus1_otdf.reshape(outage_branches.shape[0], -1)
+    return nminus1_otdf
+
+
+
+
diff --git a/pandapower/test/loadflow/test_PTDF_LODF.py b/pandapower/test/loadflow/test_PTDF_LODF.py
index f0ac6e58f..7e42fa507 100644
--- a/pandapower/test/loadflow/test_PTDF_LODF.py
+++ b/pandapower/test/loadflow/test_PTDF_LODF.py
@@ -11,7 +11,7 @@
 import pandapower.networks as nw
 from pandapower.pd2ppc import _pd2ppc
 from pandapower.pypower.makePTDF import makePTDF
-from pandapower.pypower.makeLODF import makeLODF
+from pandapower.pypower.makeLODF import makeLODF, makeOTDF, outage_results_OTDF
 
 from pandapower.test.loadflow.result_test_network_generator import result_test_network_generator_dcpp
 from pandapower.test.helper_functions import add_grid_connection, create_test_line, assert_net_equal
@@ -67,5 +67,69 @@ def test_LODF():
         raise AssertionError("LODF has wrong dimension")
 
 
+def test_OTDF():
+    net = nw.case9()
+    mg = pp.topology.create_nxgraph(net, respect_switches=True)
+    # roots = np.r_[net.ext_grid.bus.values, net.gen.bus.values]
+    # stubs = pp.topology.determine_stubs(net, roots=roots, mg=mg, respect_switches=True)  # no lines are stubs here?
+    # stubs = pp.toolbox.get_connected_elements(net, "line", roots)  # because not n-1 lines here are those
+    c = pp.topology.find_graph_characteristics(g=mg, roots=net.ext_grid.bus.values, characteristics=["bridges"])
+    bridges = np.array([pp.topology.lines_on_path(mg, p) for p in c["bridges"]]).flatten()
+    # outage_lines = [i for i in net.line.index.values if i not in stubs and i not in bridges]
+    outage_lines = np.array([i for i in net.line.index.values if i not in bridges])
+    pp.rundcpp(net)
+    _, ppci = _pd2ppc(net)
+    ptdf = makePTDF(ppci["baseMVA"], ppci["bus"], ppci["branch"])
+    lodf = makeLODF(ppci["branch"], ptdf)
+    OTDF = makeOTDF(ptdf, lodf, outage_lines)
+    Pbus = -net.res_bus.p_mw.values  # must be in generation reference frame
+    nminus1_otdf = (OTDF @ Pbus.reshape(-1, 1)).reshape(outage_lines.shape[0], -1)
+
+    # Test selected outages
+    n_lines = len(net.line)
+    for outage, line in enumerate(outage_lines):
+        otdf_outage_result = (OTDF[outage * n_lines:outage * n_lines + n_lines, :] @ Pbus)
+
+        # Run power flow for the outage scenario
+        net.line.at[line, "in_service"] = False
+        pp.rundcpp(net)
+        pf_outage_result = net.res_line.p_from_mw.values
+        net.line.at[line, "in_service"] = True
+
+        # Compare the results
+        assert np.allclose(otdf_outage_result, pf_outage_result, rtol=0, atol=1e-12)
+
+
+def test_OTDF_outage_results():
+    net = nw.case9()
+    mg = pp.topology.create_nxgraph(net, respect_switches=True)
+    # roots = np.r_[net.ext_grid.bus.values, net.gen.bus.values]
+    # stubs = pp.topology.determine_stubs(net, roots=roots, mg=mg, respect_switches=True)  # no lines are stubs here?
+    # stubs = pp.toolbox.get_connected_elements(net, "line", roots)  # because not n-1 lines here are those
+    c = pp.topology.find_graph_characteristics(g=mg, roots=net.ext_grid.bus.values, characteristics=["bridges"])
+    bridges = np.array([pp.topology.lines_on_path(mg, p) for p in c["bridges"]]).flatten()
+    # outage_lines = [i for i in net.line.index.values if i not in stubs and i not in bridges]
+    outage_lines = np.array([i for i in net.line.index.values if i not in bridges])
+    pp.rundcpp(net)
+    _, ppci = _pd2ppc(net)
+    ptdf = makePTDF(ppci["baseMVA"], ppci["bus"], ppci["branch"])
+    lodf = makeLODF(ppci["branch"], ptdf)
+    OTDF = makeOTDF(ptdf, lodf, outage_lines)
+    Pbus = -net.res_bus.p_mw.values  # must be in generation reference frame
+    nminus1_otdf = outage_results_OTDF(OTDF, Pbus, outage_lines)
+
+    # now obtain the outage results by performing power flow calculations:
+    nminus1_pf = []
+    for i in outage_lines:
+        net.line.at[i, "in_service"] = False
+        pp.rundcpp(net)
+        nminus1_pf.append(net.res_line.p_from_mw.values.copy())
+        net.line.at[i, "in_service"] = True
+
+    nminus1_pf = np.vstack(nminus1_pf)
+
+    assert np.allclose(nminus1_otdf, nminus1_pf, rtol=0, atol=1e-12)
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-xs"])