Add Nodal Pricing with OPF

.github/pull_request_template.md

@@ -1,4 +1,9 @@
-<!-- SPDX-FileCopyrightText: ASSUME Developers -->
+<!--
+SPDX-FileCopyrightText: ASSUME Developers
+
+SPDX-License-Identifier: AGPL-3.0-or-later
+-->
+
 <!-- SPDX-License-Identifier: AGPL-3.0-or-later -->
 ## Related Issue
 Closes #<issue‑number>

README.md

@@ -72,7 +72,7 @@ pip install 'assume-framework[learning]'
 Please keep in mind, that the above installation method will install pytorch package without CUDA support.
 If you want to make use of your GPU with CUDA cores, please install pytorch with GPU support separately as described [here](https://pytorch.org/get-started/locally/).
 
-We also include **network-based market clearing algorithms** such as for the re-dispatch or nodal market clearing, which requires the PyPSA library.
+We also include **network-based market clearing algorithms** such as for the re-dispatch, zonal clearing with NTCs and nodal market clearing, which all require the PyPSA library.
 To install the package with these capabilities, use:
 
 ```bash

assume/markets/clearing_algorithms/__init__.py

@@ -21,7 +21,8 @@
 # try importing pypsa if it is installed
 try:
     from .redispatch import RedispatchMarketRole
-
+    from .nodal_clearing import NodalClearingRole
     clearing_mechanisms["redispatch"] = RedispatchMarketRole
+    clearing_mechanisms["nodal_clearing"] = NodalClearingRole
 except ImportError:
     pass

assume/markets/clearing_algorithms/complex_clearing.py

@@ -177,10 +177,18 @@ def energy_balance_rule(model, node, t):
     )
 
     if incidence_matrix is not None:
+        # add NTCs
         model.transmission_constr = pyo.ConstraintList()
         for t in model.T:
             for line in model.lines:
-                capacity = lines.at[line, "s_nom"]
+                # s_max_pu might also be time variant. but for now we assume it is static
+                s_max_pu = (
+                    lines.at[line, "s_max_pu"]
+                    if "s_max_pu" in lines.columns
+                    and not pd.isna(lines.at[line, "s_max_pu"])
+                    else 1.0
+                )
+                capacity = lines.at[line, "s_nom"] * s_max_pu
                 # Limit the flow on each line
                 model.transmission_constr.add(model.flows[t, line] <= capacity)
                 model.transmission_constr.add(model.flows[t, line] >= -capacity)
@@ -290,8 +298,8 @@ class ComplexClearingRole(MarketRole):
     """
     This class defines an optimization-based market clearing algorithm with support for complex bid types,
     including block bids, linked bids, minimum acceptance ratios, and profiled volumes. It supports network
-    representations with either zonal or nodal configurations, enabling the modeling of complex markets with
-    multiple zones and power flow constraints.
+    representations (through Net Transfer Capacities) with either zonal or nodal configurations, enabling the modeling of complex markets with
+    multiple zones based on a transport model.
 
     The market clearing algorithm accepts additional arguments via the ``param_dict`` in the market configuration.
 
@@ -344,6 +352,11 @@ def __init__(self, marketconfig: MarketConfig):
             self.lines = self.grid_data["lines"]
             buses = self.grid_data["buses"]
 
+            if "x" in self.lines.columns:
+                logger.warning(
+                    "Warning: 'lines.csv' contains reactances 'x' but this clearing is based on Net Transfer Capacities only (Transport model). Use 'nodal_clearing' to include a linear OPF."
+                )
+
             self.zones_id = self.marketconfig.param_dict.get("zones_identifier")
             self.node_to_zone = None
 
@@ -779,7 +792,6 @@ def extract_results(
         if hasattr(model, "flows"):
             flows = model.flows
 
-            # filter flows and only use positive flows to half the size of the dict
             flows_filtered = {
                 index: flow.value for index, flow in flows.items() if not flow.stale
             }