Fix bug in yields table

README.md

@@ -25,7 +25,7 @@ It uses the power of ([mixed integer]) [linear programming] optimization, [`pand
     - Electricity prices via [`elmada`]
     - Carbon emission factors via [`elmada`]
     - Standard load profiles from [BDEW]
-    - PV profiles via [`gsee`] (In Germany, using weather data from [DWD])
+    - PV profiles via [`GSEE`] (In Germany, using weather data from [DWD])
   - [`DataBase`](draf/prep/data_base.py) - for scientific data such as cost or efficiency factors.
 - **Scenario generation tools:** Easily build individual scenarios or sensitivity analyses.
 - **Multi-objective mathematical optimization** with support of different model languages and solvers:
@@ -100,35 +100,39 @@ Copyright (c) 2022 Markus Fleschutz
 License: [LGPL v3]
 
 The development of `draf` was initiated by [Markus Fleschutz] in 2017 and continued in a cooperative PhD between the [MeSSO Research Group] of the [Munster Technological University], Ireland and the [Energy System Analysis Research Group] of the [Karlsruhe University of Applied Sciences], Germany.
-Thank you [Markus Bohlayer], [Adrian Bürger], and [Andre Leippi] for your valuable feedback.
+This Project was supported by the Federal Ministry for Economic Affairs and Climate Action (BMWK) on the basis of a decision by the German Bundestag and by the MTU Risam scholarship scheme.
+
+Thank you [Dr. Markus Bohlayer], [Dr. Ing. Adrian Bürger], [Andre Leippi], [Dr. Ing. Marco Braun], and [Dr. Michael D. Murphy] for your valuable feedback.
 
 <img src="doc/images/MTU_HKA_Logo.svg" width="500" alt="MTU_HKA_Logo">
 
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
 <!-- SOURCES -->
 [`elmada`]: https://github.com/DrafProject/elmada
-[`gsee`]: https://github.com/renewables-ninja/gsee
+[`GSEE`]: https://github.com/renewables-ninja/gsee
 [`GurobiPy`]: https://pypi.org/project/gurobipy
 [`matplotlib`]: https://matplotlib.org
 [`pandas`]: https://pandas.pydata.org
 [`plotly`]: https://plotly.com
 [`Pyomo`]: https://github.com/Pyomo/pyomo
 [`seaborn`]: https://seaborn.pydata.org
-[Adrian Bürger]: https://scholar.google.de/citations?user=UcLkLlEAAAAJ
 [anaconda]: https://www.anaconda.com/products/individual
 [Andre Leippi]: https://www.linkedin.com/in/andre-leippi-3187a81a7
 [BDEW]: https://www.bdew.de
+[Dr. Ing. Adrian Bürger]: https://www.linkedin.com/in/adrian-b%C3%BCrger-251205236/
+[Dr. Ing. Marco Braun]: https://www.h-ka.de/en/about-hka/organization-people/staff-search/person/marco-braun
+[Dr. Markus Bohlayer]: https://www.linkedin.com/in/markus-bohlayer
+[Dr. Michael D. Murphy]: https://www.linkedin.com/in/michael-d-murphy-16134118
 [DWD]: https://www.dwd.de
 [Energy System Analysis Research Group]: https://www.h-ka.de/en/ikku/energy-system-analysis
 [Karlsruhe University of Applied Sciences]: https://www.h-ka.de/en
 [LGPL v3]: https://www.gnu.org/licenses/lgpl-3.0.de.html
 [linear programming]: https://en.wikipedia.org/wiki/Linear_programming
-[Markus Bohlayer]: https://scholar.google.com/citations?user=hH1FQVsAAAAJ
 [Markus Fleschutz]: https://mfleschutz.github.io
 [MeSSO Research Group]: https://messo.cit.ie
 [miniconda]: https://docs.conda.io/en/latest/miniconda.html
 [Mittelmann benchmark]: http://plato.asu.edu/ftp/milp.html
 [mixed integer]: https://en.wikipedia.org/wiki/Integer_programming
 [Munster Technological University]: https://www.mtu.ie
-[xarray]: http://xarray.pydata.org/en/stable
+[xarray]: http://xarray.pydata.org/en/stable

draf/components/component_templates.py

@@ -474,7 +474,9 @@ def get_C():
             data=0.5,
             doc="Ratio of reaching the ideal COP (exergy efficiency)",
             src="@Arat_2017",
-        )  # Cox_2022 used 0.45 (https://doi.org/10.1016/j.apenergy.2021.118499)
+            # Cox_2022 used 0.45: https://doi.org/10.1016/j.apenergy.2021.118499
+            # but roughly 0.5 in recent real operation of high temperature HP: https://www.waermepumpe.de/fileadmin/user_upload/waermepumpe/01_Verband/Webinare/Vortrag_Wilk_AIT_02062020.pdf
+        )
         sc.param("dQ_HP_CAPx_", data=self.dQ_CAPx, doc="Existing heating capacity", unit="kW_th")
         sc.param(
             "dQ_HP_max_", data=1e5, doc="Big-M number (upper bound for CAPn + CAPx)", unit="kW_th"

draf/core/case_study.py

@@ -218,7 +218,7 @@ def add_scen(
         based_on: Optional[str] = "REF",
         based_on_last: bool = False,
         components: Optional[List[Component]] = None,
-        custom_model: Optional[Callable] = None
+        custom_model: Optional[Callable] = None,
     ) -> Scenario:
         """Add a Scenario with a name, a describing doc-string and a link to a model.
 
@@ -256,7 +256,7 @@ def add_scen(
                 consider_invest=self.consider_invest,
                 mdl_language=self.mdl_language,
                 obj_vars=self.obj_vars,
-                custom_model=custom_model
+                custom_model=custom_model,
             )
         else:
             if components is not None:
@@ -485,7 +485,6 @@ def set_model(
     def _optimize_parallel(
         self, scens: Optional[Iterable] = None, optimize_kwargs: Optional[Dict] = None
     ):
-
         @ray.remote
         def optimize_scenario(sc):
             sc.optimize(**optimize_kwargs)

draf/core/scenario.py

@@ -663,8 +663,7 @@ def save_results(self) -> None:
             pickle.dump(self, f, protocol=pickle.HIGHEST_PROTOCOL)
         logger.info(f"Saved scenario results to {fp}")
 
-
-    def save(self, name:Optional[str]=None) -> None:
+    def save(self, name: Optional[str] = None) -> None:
         """Saves the scenario to a pickle-file."""
         date_time = self._get_now_string()
 

draf/plotting/cs_plotting.py

@@ -119,7 +119,8 @@ def yields_table(self, gradient: bool = False, nyears_for_irr: int = 15) -> pdSt
                 ("", "C_invAnn"): cs.get_ent("C_TOT_invAnn_"),
                 ("", "C_op"): cs.get_ent("C_TOT_op_"),
                 ("", "EAC"): -cs.get_diff("C_TOT_") / cs.get_diff("CE_TOT_") * 1e6,
-                ("", "PP"): (cs.get_ent("C_TOT_inv_") / cs.get_diff("C_TOT_op_")).replace(
+                ("", "PP"): cs.get_ent("C_TOT_inv_")
+                / ((cs.get_diff("C_TOT_op_") + cs.get_diff("C_TOT_RMI_"))).replace(
                     np.inf, np.nan  # infinity is not supported by background gradient
                 ),
             }
@@ -943,25 +944,39 @@ def capas(self, include_capx: bool = True, subplot_x_anchors=(0.79, 0.91)) -> go
         unit1 = cs.REF_scen.get_unit("C_TOT_inv_")
         ser, unit1 = hp.auto_fmt(ser, unit1)
         fig.add_trace(
-            go.Bar(y=ser.index.tolist(), x=ser.values, xaxis="x2", yaxis="y2", orientation="h")
+            go.Bar(
+                y=ser.index.tolist(),
+                x=ser.values,
+                xaxis="x2",
+                yaxis="y2",
+                orientation="h",
+                marker_color="grey",
+            )
         )
 
         ser = pd.Series(cs.get_ent("C_TOT_op_"))
         unit2 = cs.REF_scen.get_unit("C_TOT_op_")
         ser, unit2 = hp.auto_fmt(ser, unit2)
         fig.add_trace(
-            go.Bar(y=ser.index.tolist(), x=ser.values, xaxis="x3", yaxis="y3", orientation="h")
+            go.Bar(
+                y=ser.index.tolist(),
+                x=ser.values,
+                xaxis="x3",
+                yaxis="y3",
+                orientation="h",
+                marker_color="grey",
+            )
         )
 
         margin = 0.01
-        domain1 = (0, subplot_x_anchors[0]-margin)
-        domain2 = (subplot_x_anchors[0]+margin, subplot_x_anchors[1] - margin )
+        domain1 = (0, subplot_x_anchors[0] - margin)
+        domain2 = (subplot_x_anchors[0] + margin, subplot_x_anchors[1] - margin)
         domain3 = (subplot_x_anchors[1] + margin, 1)
 
         capx_adder = " (decision variables in <b>bold</b>)" if include_capx else ""
         fig.update_layout(
             margin=dict(t=5, l=5, r=5, b=5),
-            xaxis=dict(domain=domain1, title=f"Capacity (kW or kWh) of component{capx_adder}"),
+            xaxis=dict(domain=domain1, title=f"Capacity of component (kW or kWh){capx_adder}"),
             xaxis2=dict(domain=domain2, anchor="y2", title=f"C_inv ({unit1})", side="top"),
             yaxis2=dict(anchor="x2", showticklabels=False),
             xaxis3=dict(domain=domain3, anchor="y3", title=f"C_op ({unit2})", side="top"),

draf/prep/param_funcs.py

@@ -71,6 +71,9 @@ def c_HP_inv_(estimated_size=100) -> ParDat:
     """
     assert 0 < estimated_size < 200
     value = 1520.7 * estimated_size**-0.363
+
+    # see also Kosmadakis.2020 (https://doi.org/hsn7) for newer data
+
     return ParDat(name="c_HP_inv_", data=value, doc="CAPEX", src="@Wolf_2017", unit="€/kW_el")