Merge pull request #481 from agoenergy/develop

v0.9

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.8.2
+current_version = 0.9.0
 commit = True
 tag = True
 
@@ -10,3 +10,5 @@ tag = True
 [bumpversion:file:.github/workflows/publish.yaml]
 
 [bumpversion:file:README.md]
+
+[bumpversion:file:app/tab_info.py]

.github/workflows/publish.yaml

@@ -23,4 +23,4 @@ jobs:
         uses: docker/build-push-action@v5
         with:
           push: true
-          tags: wingechr/ptx-boa:0.8.2
+          tags: wingechr/ptx-boa:0.9.0

.streamlit/config.toml

@@ -9,7 +9,7 @@
     toolbarMode = "minimal"
 
 [logger]
-    level="DEBUG"
+    level="INFO"
 
 [browser]
     gatherUsageStats = false

Dockerfile

@@ -1,5 +1,5 @@
 FROM python:3.10-slim
-LABEL version="0.8.2"
+LABEL version="0.9.0"
 
 RUN apt-get update
 RUN apt-get install -y git

README.md

@@ -68,7 +68,7 @@ scp -r ptxboa2:ptx-boa_offline_optimization/optimization_cache/* .
 # connect to server
 ssh ptxboa
 # pull latest image from dockerhub
-VERSION=0.8.2
+VERSION=0.9.0
 docker pull wingechr/ptx-boa:$VERSION
 # stop and delete the currently running container "app"
 docker stop app

app/layout_elements.py

@@ -168,11 +168,10 @@ def display_footer():
             st.markdown(
                 """
                 ##### On behalf of
-                Agora Energiewende<br/>
+                Agora Industry<br/>
                 Anna-Louisa-Karsch-Str. 2<br/>
                 D-10178 Berlin<br/>
-                www.agora-industry.org<br/>
-                www.agora-energiewende.org
+                www.agora-industry.org
                 """,
                 unsafe_allow_html=True,
             )
@@ -192,13 +191,16 @@ def display_footer():
             )
 
         # TODO: fix uneven height and vertical alignment of logos
-        c1, c2, c3, c4 = st.columns(4, gap="medium")
+        c0, c1, c2, c3, c4, c5 = st.columns(
+            [1, 2, 2, 2, 2, 1],
+            gap="large",
+        )
         with c1:
-            st.image("img/oeko_logo_612x306.png")
+            st.image("img/Agora_Industry_logo_612x306.png")
         with c2:
             st.image("img/agora-energiewende_logo_612x306.png")
         with c3:
-            st.image("img/Agora_Industry_logo_612x306.png")
+            st.image("img/oeko_logo_612x306.png")
         with c4:
             st.image("img/PtX-Hub_Logo_international_612x306.png")
 

app/plot_functions.py

@@ -582,11 +582,11 @@ def add_trace_to_figure(
     df_plot = df[(df["Component"] == component)]
     df_plot = df_plot[(df_plot["Parameter"] == parameter)]
     if fill:
-        if df_plot["MW (MWh for SOC)"].sum() > 0:
+        if df_plot["MW"].sum() > 0:
             fig.add_trace(
                 go.Scatter(
                     x=df_plot["time"],
-                    y=df_plot["MW (MWh for SOC)"],
+                    y=df_plot["MW"],
                     mode="lines",
                     name=component,
                     line_color=color,
@@ -597,7 +597,7 @@ def add_trace_to_figure(
         fig.add_trace(
             go.Scatter(
                 x=df_plot["time"],
-                y=df_plot["MW (MWh for SOC)"],
+                y=df_plot["MW"],
                 mode="lines",
                 name=component,
                 line_color=color,
@@ -612,7 +612,7 @@ def transform_time_series(
         res = df.reset_index().melt(
             id_vars=["timestep", "period"],
             var_name="Component",
-            value_name="MW (MWh for SOC)",
+            value_name="MW",
         )
         res["Parameter"] = parameter
         return res
@@ -623,9 +623,9 @@ def transform_time_series(
     df_gen = transform_time_series(df_gen)
     df_links = -n.links_t["p1"]
     df_links = transform_time_series(df_links)
-    df_store = n.stores_t["e"]
+    df_store = n.stores_t["p"]
     df_store = transform_time_series(df_store)
-    df_storageunit = n.storage_units_t["state_of_charge"]
+    df_storageunit = n.storage_units_t["p"]
     df_storageunit = transform_time_series(df_storageunit)
 
     df = pd.concat([df_p_max_pu, df_gen, df_links, df_store, df_storageunit])
@@ -711,12 +711,24 @@ def create_profile_figure_generation(df_sel: pd.DataFrame) -> go.Figure:
         parameter="Power",
         color="#408B2E",
     )
+    add_trace_to_figure(
+        df_sel,
+        fig,
+        component="Electricity storage",
+        parameter="Power",
+        color="#D05094",
+    )
+
+    add_trace_to_figure(
+        df_sel, fig, component="H2 storage", parameter="Power", color="#733E88"
+    )
 
     add_vertical_lines(fig)
 
     fig.update_layout(
         xaxis={"title": "time (h)"},
         yaxis={"title": "output (MW)"},
+        legend={"traceorder": "normal"},
     )
 
     return fig
@@ -757,6 +769,7 @@ def create_profile_figure_soc(df_sel: pd.DataFrame) -> go.Figure:
     fig.update_layout(
         xaxis={"title": "time (h)"},
         yaxis={"title": "state of charge (MWh)"},
+        legend={"traceorder": "normal"},
     )
 
     return fig

app/sidebar.py

@@ -9,13 +9,13 @@
 
 @st.cache_resource()
 def sidebar_logo():
-    st.image("img/agora-energiewende_logo_612x306.png")
+    st.image("img/Agora_Industry_logo_612x306.png")
 
 
 def make_sidebar(api: PtxboaAPI):
     st.logo(
         image="img/transparent_10x10.png",  # placeholder when sidebar is expanded
-        icon_image="img/agora-energiewende_logo_612x306.png",
+        icon_image="img/Agora_Industry_logo_612x306.png",
     )
 
     with st.sidebar:

app/tab_info.py

@@ -4,6 +4,8 @@
 
 from app.ptxboa_functions import read_markdown_file
 
+__version__ = "0.8.3"
+
 
 def content_info():
     with st.container(border=True):
@@ -42,3 +44,16 @@ def content_info():
 
     with st.container(border=True):
         st.markdown(read_markdown_file("md/info_disclaimer.md"))
+        st.markdown(
+            (
+                "#### Licensing and quotation\n"
+                "This tool is licensed under the Creative Commons CC-BY 4.0 license"
+                " (<https://creativecommons.org/licenses/by/4.0/>).\n\n"
+                "The use of the methods and results are only authorised"
+                " in case the tool and its authors are properly cited.\n\n"
+                "Please cite it as:"
+                " Oeko-Institut, Agora Industry & Agora Energiewende  (2024):"
+                f" PTX Business Opportunity Analyser {__version__}"
+                " <https://ptxboa.agora-thinktanks.org/>)"
+            )
+        )

md/info_disclaimer.md

@@ -1,22 +1,3 @@
-#### Disclaimer
-
-The PTX BOA uses technical reports published by third parties.
-The authors of the tool and Agora Energiewende trust but do not guarantee
-the accuracy and completeness of the information provided by them.
-
-All rights reserved to Öko-Institut and Agora Energiewende.
-The use of the methods and results are only authorised
-in case Öko-institut and Agora Energiewende is properly cited.
-
-#### Licensing and quotation
-
-This tool is licensed under the Creative Commons CC-BY-SA license
-(<https://creativecommons.org/licenses/by-sa/4.0/>).
-
-Please cite it as: Oeko-Institut, Agora Energiewende & Agora Industry (2023):
-PTX Business Opportunity Analyser
-<https://ptx-boa.streamlit.app/>
-
 #### Source code and contribution
 
 We strongly welcome anyone interested in contributing to this project.
@@ -28,3 +9,9 @@ or make a contribution, please check out our Github repository:
 
 Visit our website for data documentation, additional resources and updates:
 <https://www.agora-energiewende.de/en/publications/business-opportunity-analyser-boa>
+
+#### Disclaimer
+
+The PTX BOA uses technical reports published by third parties.
+The authors of the tool and Agora Energiewende trust but do not guarantee
+the accuracy and completeness of the information provided by them.

offline_optimization_script.py

@@ -65,13 +65,7 @@ def generate_param_sets(api: PtxboaAPI):
 
     # specify parameter dimensions not relevant for optimization
     # we choose arbritray values for those
-    static_params = {
-        "transport": "Ship",
-        "ship_own_fuel": False,
-        "country": "Germany",
-        "secproc_water": "Specific costs",
-        "secproc_co2": "Specific costs",
-    }
+    static_params = {"transport": "Ship", "ship_own_fuel": False, "country": "Germany"}
 
     # these are the parameter dimensions that are relevant for the optimization
     scenarios = api.get_dimension("scenario").index.tolist()
@@ -81,14 +75,22 @@ def generate_param_sets(api: PtxboaAPI):
         for c in api.get_dimension("chain").index.tolist()
         if not c.endswith("+ reconv. to H2")
     ]
+    secprocs_water = ["Specific costs", "Sea Water desalination"]
+    secprocs_co2 = ["Specific costs", "Direct Air Capture"]
 
     param_sets = []
     for region in regions:
         # only get availabe technologies for this region
         res_gens = api.get_res_technologies(region)
         param_sets += [
             p | static_params | {"region": region}
-            for p in product_dict(scenario=scenarios, chain=chains, res_gen=res_gens)
+            for p in product_dict(
+                scenario=scenarios,
+                chain=chains,
+                res_gen=res_gens,
+                secproc_water=secprocs_water,
+                secproc_co2=secprocs_co2,
+            )
         ]
 
     return param_sets
@@ -100,13 +102,27 @@ def main(
     loglevel: Literal["debug", "info", "warning", "error"] = "info",
     index_from: int = None,
     index_to: int = None,
+    count_only: bool = False,
 ):
     cache_dir = Path(cache_dir)
     cache_dir.mkdir(exist_ok=True)
 
     out_dir = Path(out_dir) if out_dir else cache_dir
     out_dir.mkdir(exist_ok=True)
 
+    api = PtxboaAPI(data_dir=DEFAULT_DATA_DIR, cache_dir=cache_dir)
+
+    param_sets = generate_param_sets(api)
+
+    if count_only:
+        print(f"Number of parameter variations: {len(param_sets)}")
+        return
+
+    # filter for batch
+    index_from = index_from or 0
+    index_to = index_to or len(param_sets)
+    param_sets = param_sets[index_from:index_to]
+
     # set up logging
     fmt = "[%(asctime)s %(levelname)7s] %(message)s"
     datefmt = "%Y-%m-%d %H:%M:%S"
@@ -115,18 +131,12 @@ def main(
         format=fmt,
         datefmt=datefmt,
         handlers=[
-            logging.FileHandler(cache_dir / "offline_optimization_script.log"),
+            logging.FileHandler(
+                cache_dir / f"offline_optimization_script.{index_from}-{index_to}.log"
+            ),
         ],
     )
     logging.info(f"starting offline optimization script with cache_dir: {cache_dir}")
-    api = PtxboaAPI(data_dir=DEFAULT_DATA_DIR, cache_dir=cache_dir)
-
-    param_sets = generate_param_sets(api)
-
-    # filter for batch
-    index_from = index_from or 0
-    index_to = index_to or len(param_sets)
-    param_sets = param_sets[index_from:index_to]
 
     results = []  # save results
     for params in progress.bar.Bar(
@@ -154,7 +164,9 @@ def main(
 
     # save result
     with open(
-        out_dir / "offline_optimization.results.json", "w", encoding="utf-8"
+        out_dir / f"offline_optimization.results.{index_from}-{index_to}.json",
+        "w",
+        encoding="utf-8",
     ) as file:
         json.dump(
             results,
@@ -205,6 +217,12 @@ def main(
         type=int,
         help="final index (exlusive) for prallel runs",
     )
+    parser.add_argument(
+        "-n",
+        "--count_only",
+        action="store_true",
+        help="only print number of parameter variations and quit.",
+    )
 
     args = parser.parse_args()
     main(**vars(args))

ptxboa/api_data.py

@@ -809,16 +809,20 @@ def _get_calculation_data(
             chain, transport_distances
         )
 
+        used_flows = set()
         for process_step in chain_steps_main:
             process_code = chain[process_step]
             res = pg.get_process_params(process_code)
             res["step"] = process_step
             res["process_code"] = process_code
             result["main_process_chain"].append(res)
+            used_flows = used_flows | set(res["CONV"])
 
         for flow_code, process_code in secondary_processes.items():
             if not process_code:
                 continue
+            if flow_code not in used_flows:
+                continue
             res = pg.get_process_params(process_code)
             res["process_code"] = process_code
             result["secondary_process"][flow_code] = res