Feature/bert basic

docs/alkaline_ref.md

@@ -0,0 +1,73 @@
+1. [Oystein Ulleberg, 2003](https://www.sciencedirect.com/science/article/pii/S0360319902000332?via%3Dihub)
+    "Modeling of advanced alkaline electrolyzers: a system simulation approach"
+
+
+2. [Gambou, Guilbert,et al 2022](https://www.mdpi.com/1996-1073/15/9/3452)
+    "A Comprehensive Survey of Alkaline Electrolyzer Modeling: Electrical
+    Domain and Specific Electrolyte Conductivity"
+
+
+3. [Haug ,Kreitz, 2017](https://www.sciencedirect.com/science/article/pii/S0360319917318633)
+    "Process modelling of an alkaline water electrolyzer"
+
+
+4. [Henou, Agbossou, 2014](https://www.sciencedirect.com/science/article/pii/S0378775313017527)
+    - "Simulation tool based on a physics model and an electrical
+    analogy for an alkaline electrolyser"
+    - Notes:
+        - cited by [Gambou, Guilbert,et al 2022]
+        - HAS ALL THE VALUES FOR VARIABLES USED IN [Gambou, Guilbert,et al 2022]
+
+5. [Hammoudi,Henao, 2012](https://www.sciencedirect.com/science/article/pii/S036031991201590X)
+    - "New multi-physics approach for modelling andn design of
+    alkaline electrolyzers"
+    - Notes:
+        - Referenced by [Henou, Agbossou, 2014] for theta calculation
+            (electrode coverage)
+        - Eqn 44 for bubble stuff
+        - j_lim=300 kA/m^2
+        - includes other efficiency losses
+        - cites: https://www.sciencedirect.com/science/article/pii/S0360128509000598
+
+6. [Brauns,2021](https://iopscience.iop.org/article/10.1149/1945-7111/abda57/pdf)
+    - bibtex label:
+    - "Evaluation of Diaphragms and Membranes as Separators for Alkaline Water Electrolysis" by Jorn Brauns et all 2021. J. Electrochem Soc 168 014510
+    - Notes:
+        - good numbers
+        - electrolyte flow rate of 350 mL/min
+        - total electrolyte volume of 10L
+        - has supplementary material (need to checkout)
+        - in "material stability" it mentions stuff about DEGRADATION
+
+7. [NEL Report](https://www.energy.gov/sites/default/files/2022-02/2-Intro-Liquid%20Alkaline%20Workshop.pdf)
+    - bibtex label:
+
+
+8. [Brauns, Turek 2020](https://www.mdpi.com/2227-9717/8/2/248)
+    - bibtex label:
+    - "Alkaline Water Electrolysis Powered by Renewable Energy: A Review"
+
+
+9. [Eigeldinger, Vogt 2000](https://www.sciencedirect.com/science/article/pii/S0013468600005132)
+    - bibtex label: Eigeldinger_2000
+    - "The bubble coverage of gas evolving electrodes in a flowing electrolyte"
+    - Notes:
+        - Ref 15 of Henou 2014 for current density and theta stuff
+        - has current density equation with theta included
+
+10. [Haug, Koj, Turek 2017](https://www.sciencedirect.com/science/article/pii/S0360319916336588)
+"Influence of process conditions on gas purity in alkaline water electrolysis"
+by Phillip Haug, Motthias Koj, Thomas Turek [2017]
+
+
+11. [Niroula, Chaudhary, Subedi, Thapa 2003](https://iopscience.iop.org/article/10.1088/1757-899X/1279/1/012005/pdf)
+
+    "Parametric Modelling and Optimization of Alkaline Electrolyzer for the Production
+    of Green Hydrogen" by S. Niroula, C Chaudhary, A Subedi, and B S Thapa
+    [2003] doi:10.1088/1757-899X/1279/1/012005
+
+
+12. [Vogt,Balzer 2005](https://www.sciencedirect.com/science/article/pii/S001346860400948X?via%3Dihub)
+"The bubble coverage of gas-evolving electrodes in stagnant electrolytes"
+by H. Vogt and R.J. Balzer
+Volume 50, Issue 10, 15 March 2005, Pages 2073-2079

electrolyzer/simulation/base.py

@@ -0,0 +1,34 @@
+from typing import Any, Dict
+
+import attrs
+
+from electrolyzer.tools.type_dec import FromDictMixin
+
+
+class BaseClass(FromDictMixin):
+    """
+    BaseClass object class. This class does the logging and MixIn class inheritance.
+    """
+
+    @classmethod
+    def get_model_defaults(cls) -> Dict[str, Any]:
+        """Produces a dictionary of the keyword arguments and their defaults.
+
+        Returns
+        -------
+        Dict[str, Any]
+            Dictionary of keyword argument: default.
+        """
+        return {el.name: el.default for el in attrs.fields(cls)}
+
+    def _get_model_dict(self) -> dict:
+        """Convenience method that wraps the `attrs.asdict` method. Returns the object's
+        parameters as a dictionary.
+
+        Returns
+        -------
+        dict
+            The provided or default, if no input provided,
+            model settings as a dictionary.
+        """
+        return attrs.asdict(self)

electrolyzer/simulation/bert.py

@@ -105,6 +105,55 @@ def _run_electrolyzer_opt(modeling_options, power_signal):
     return tot_kg, max_curr_density
 
 
+def run_LCA(elec_sys, plant_life_years: int):
+    sys_refurb = pd.DataFrame()
+    sys_aep = pd.DataFrame()
+    sys_ah2 = pd.DataFrame()
+    years = list(np.arange(0, plant_life_years, 1))
+    for i, stack in enumerate(elec_sys.stacks):
+        id = i + 1
+        refturb_schedule, ahp_kg, aep_kWh = stack.estimate_life_performance_from_year(
+            plant_life_years
+        )
+        sys_aep = pd.concat(
+            [
+                sys_aep,
+                pd.DataFrame(
+                    dict(zip(["Stack {}".format(id)], [aep_kWh])), index=years
+                ),
+            ]
+        )
+        sys_ah2 = pd.concat(
+            [
+                sys_ah2,
+                pd.DataFrame(dict(zip(["Stack {}".format(id)], [ahp_kg])), index=years),
+            ]
+        )
+        sys_refurb = pd.concat(
+            [
+                sys_refurb,
+                pd.DataFrame(
+                    dict(zip(["Stack {}".format(id)], [refturb_schedule])), index=years
+                ),
+            ]
+        )
+        # df_index = [
+        #     [f"stack {id}"]*plant_life_years,
+        #     list(np.arange(0,plant_life_years,1))
+        # ]
+        # temp_df = pd.DataFrame(dict(zip(
+        #     ["AEP [kWh/year]","Refurb Schedule","AHP [kg/year]"],
+        #     [aep_kWh,ahp_kg,refturb_schedule])),
+        #     index=df_index
+        # )
+        # stack_LCA = pd.concat([stack_LCA,temp_df])
+    return {
+        "Refurb Schedule": sys_refurb,
+        "AEP [kWh/year]": sys_aep,
+        "AHP [kg/year]": sys_ah2,
+    }
+
+
 def run_electrolyzer(input_modeling, power_signal, optimize=False):
     """
     Runs an electrolyzer simulation based on a YAML configuration file and power