diff --git a/electrolyzer/cell.py b/electrolyzer/cell.py
index 3897183..8ba75d4 100644
--- a/electrolyzer/cell.py
+++ b/electrolyzer/cell.py
@@ -60,7 +60,7 @@ def calc_open_circuit_voltage(self, temperature):
         """Calculates open circuit voltage using the Nernst equation."""
         T_K = convert_temperature([temperature], "C", "K")[0]
         E_rev_0 = self.calc_reversible_voltage()
-        p_anode = P_ATMO  # (Pa) assumed atmo
+        p_anode = 30 * P_ATMO  # (Pa) assumed atmo
         p_cathode = P_ATMO
 
         # noqa: E501
diff --git a/examples/example_06_conversion_efficiency/example_run.ipynb b/examples/example_06_conversion_efficiency/example_run.ipynb
index 3da0c54..9e42799 100644
--- a/examples/example_06_conversion_efficiency/example_run.ipynb
+++ b/examples/example_06_conversion_efficiency/example_run.ipynb
@@ -1,314 +1,308 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Example Conversion Efficiency\n",
-    "\n",
-    "This example simulates a single electrolyzer stack with a linear ramping power signal. The electrolyzer is initialized as ON. The full structure for an electrolyzer model is defined in the source code, in `modeling_schema.yaml`.\n",
-    "\n",
-    "* Conversion is calculated based on the energy consumed per kg of hydrogen. Units are kWh/kg\n",
-    "\n",
-    "* Conversion efficiency is calculated by dividing the low-heating value of hydrogen (33.33 kWh/kg) by the actual conversion."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "from electrolyzer import run_electrolyzer\n",
-    "from electrolyzer.inputs.validation import load_modeling_yaml\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load Electrolyzer configuration from YAML file\n",
-    "\n",
-    "This .yaml file initializes a 500kW electrolyzer stack as `ON` with the `BaselineDeg` controller. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
+  "cells": [
     {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>power_signal</th>\n",
-       "      <th>curtailment</th>\n",
-       "      <th>kg_rate</th>\n",
-       "      <th>stack_1_deg</th>\n",
-       "      <th>stack_1_fatigue</th>\n",
-       "      <th>stack_1_cycles</th>\n",
-       "      <th>stack_1_uptime</th>\n",
-       "      <th>stack_1_kg_rate</th>\n",
-       "      <th>stack_1_curr_density</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>195</th>\n",
-       "      <td>589949.748744</td>\n",
-       "      <td>0.089950</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>6.041372e-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>196.0</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>2.08729</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>196</th>\n",
-       "      <td>592462.311558</td>\n",
-       "      <td>0.092462</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>6.074780e-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>197.0</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>2.08729</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>197</th>\n",
-       "      <td>594974.874372</td>\n",
-       "      <td>0.094975</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>6.108189e-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>198.0</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>2.08729</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>198</th>\n",
-       "      <td>597487.437186</td>\n",
-       "      <td>0.097487</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>6.141598e-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>199.0</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>2.08729</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>199</th>\n",
-       "      <td>600000.000000</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>6.175006e-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>0.002031</td>\n",
-       "      <td>2.08729</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Example Conversion Efficiency\n",
+        "\n",
+        "This example simulates a single electrolyzer stack with a linear ramping power signal. The electrolyzer is initialized as ON. The full structure for an electrolyzer model is defined in the source code, in `modeling_schema.yaml`.\n",
+        "\n",
+        "* Conversion is calculated based on the energy consumed per kg of hydrogen. Units are kWh/kg\n",
+        "\n",
+        "* Conversion efficiency is calculated by dividing the low-heating value of hydrogen (33.33 kWh/kg) by the actual conversion."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 53,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "\n",
+        "from electrolyzer import run_electrolyzer\n",
+        "from electrolyzer.inputs.validation import load_modeling_yaml\n",
+        "\n",
+        "import matplotlib.pyplot as plt\n",
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Load Electrolyzer configuration from YAML file\n",
+        "\n",
+        "This .yaml file initializes a 500kW electrolyzer stack as `ON` with the `BaselineDeg` controller. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 54,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>power_signal</th>\n",
+              "      <th>curtailment</th>\n",
+              "      <th>kg_rate</th>\n",
+              "      <th>stack_1_deg</th>\n",
+              "      <th>stack_1_fatigue</th>\n",
+              "      <th>stack_1_cycles</th>\n",
+              "      <th>stack_1_uptime</th>\n",
+              "      <th>stack_1_kg_rate</th>\n",
+              "      <th>stack_1_curr_density</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>195</th>\n",
+              "      <td>1.472362e+06</td>\n",
+              "      <td>0.222362</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>5.914409e-08</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>196.0</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>1.790017</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>196</th>\n",
+              "      <td>1.479271e+06</td>\n",
+              "      <td>0.229271</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>5.947382e-08</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>197.0</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>1.790017</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>197</th>\n",
+              "      <td>1.486181e+06</td>\n",
+              "      <td>0.236181</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>5.980355e-08</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>198.0</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>1.790017</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>198</th>\n",
+              "      <td>1.493090e+06</td>\n",
+              "      <td>0.243090</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>6.013327e-08</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>199.0</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>1.790017</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>199</th>\n",
+              "      <td>1.500000e+06</td>\n",
+              "      <td>0.250000</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>6.046300e-08</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>200.0</td>\n",
+              "      <td>0.005224</td>\n",
+              "      <td>1.790017</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     power_signal  curtailment   kg_rate   stack_1_deg  stack_1_fatigue  \\\n",
+              "195  1.472362e+06     0.222362  0.005224  5.914409e-08                0   \n",
+              "196  1.479271e+06     0.229271  0.005224  5.947382e-08                0   \n",
+              "197  1.486181e+06     0.236181  0.005224  5.980355e-08                0   \n",
+              "198  1.493090e+06     0.243090  0.005224  6.013327e-08                0   \n",
+              "199  1.500000e+06     0.250000  0.005224  6.046300e-08                0   \n",
+              "\n",
+              "     stack_1_cycles  stack_1_uptime  stack_1_kg_rate  stack_1_curr_density  \n",
+              "195             0.0           196.0         0.005224              1.790017  \n",
+              "196             0.0           197.0         0.005224              1.790017  \n",
+              "197             0.0           198.0         0.005224              1.790017  \n",
+              "198             0.0           199.0         0.005224              1.790017  \n",
+              "199             0.0           200.0         0.005224              1.790017  "
+            ]
+          },
+          "execution_count": 54,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
       ],
-      "text/plain": [
-       "      power_signal  curtailment   kg_rate   stack_1_deg  stack_1_fatigue  \\\n",
-       "195  589949.748744     0.089950  0.002031  6.041372e-08                0   \n",
-       "196  592462.311558     0.092462  0.002031  6.074780e-08                0   \n",
-       "197  594974.874372     0.094975  0.002031  6.108189e-08                0   \n",
-       "198  597487.437186     0.097487  0.002031  6.141598e-08                0   \n",
-       "199  600000.000000     0.100000  0.002031  6.175006e-08                0   \n",
-       "\n",
-       "     stack_1_cycles  stack_1_uptime  stack_1_kg_rate  stack_1_curr_density  \n",
-       "195             0.0           196.0         0.002031               2.08729  \n",
-       "196             0.0           197.0         0.002031               2.08729  \n",
-       "197             0.0           198.0         0.002031               2.08729  \n",
-       "198             0.0           199.0         0.002031               2.08729  \n",
-       "199             0.0           200.0         0.002031               2.08729  "
+      "source": [
+        "fname_input_modeling = \"./modeling_options.yaml\"\n",
+        "model_input = load_modeling_yaml(fname_input_modeling)\n",
+        "\n",
+        "rated_power = model_input['electrolyzer']['stack']['stack_rating_kW']\n",
+        "\n",
+        "# Linear ramping power signal [W]\n",
+        "power_signal_input = np.linspace(0.1e3 * rated_power, 1.2e3 * rated_power, 200)\n",
+        "\n",
+        "elec_sys, results_df = run_electrolyzer(model_input, power_signal_input)\n",
+        "\n",
+        "results_df.tail()"
       ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "fname_input_modeling = \"./modeling_options.yaml\"\n",
-    "model_input = load_modeling_yaml(fname_input_modeling)\n",
-    "\n",
-    "rated_power = model_input['electrolyzer']['stack']['stack_rating_kW']\n",
-    "\n",
-    "# Linear ramping power signal [W]\n",
-    "power_signal_input = np.linspace(1e5, 1.2e3 * rated_power, 200)\n",
-    "\n",
-    "elec_sys, results_df = run_electrolyzer(model_input, power_signal_input)\n",
-    "\n",
-    "results_df.tail()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Power Signal\n",
-    "* Linear ramp power signal \n",
-    "* Confirm that the stack is initialized at time = 0.0 seconds"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "<AxesSubplot:title={'center':'Stack Up time'}, xlabel='Time (s)', ylabel='Time (s)'>"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### Power Signal\n",
+        "* Linear ramp power signal \n",
+        "* Confirm that the stack is initialized at time = 0.0 seconds"
       ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+      "cell_type": "code",
+      "execution_count": 55,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: title={'center': 'Stack Up time'}, xlabel='Time (s)', ylabel='Time (s)'>"
+            ]
+          },
+          "execution_count": 55,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "# Power input signal from DataFrame\n",
+        "results_df[\"power_signal\"].plot(title=\"Power Signal\", xlabel=\"Time (s)\", ylabel=\"Power (W)\")\n",
+        "\n",
+        "# Plot stack up-time to show start up delays \n",
+        "stack_uptime = results_df[[col for col in results_df.columns if \"_uptime\" in col]]\n",
+        "stack_uptime.plot(title=\"Stack Up time\", xlabel=\"Time (s)\", ylabel=\"Time (s)\")"
       ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### Co-Plot H2 rate and Conversion Efficiency\n",
+        "\n",
+        "* Converts DataFrame data to kW and kg/hr\n",
+        "* low-heating value (LHV) = 33.33 kWh/kg\n",
+        "* Rated power = 500kW "
       ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Power input signal from DataFrame\n",
-    "results_df[\"power_signal\"].plot(title=\"Power Signal\", xlabel=\"Time (s)\", ylabel=\"Power (W)\")\n",
-    "\n",
-    "# Plot stack up-time to show start up delays \n",
-    "stack_uptime = results_df[[col for col in results_df.columns if \"_uptime\" in col]]\n",
-    "stack_uptime.plot(title=\"Stack Up time\", xlabel=\"Time (s)\", ylabel=\"Time (s)\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Co-Plot H2 rate and Conversion Efficiency\n",
-    "\n",
-    "* Converts DataFrame data to kW and kg/hr\n",
-    "* low-heating value (LHV) = 33.33 kWh/kg\n",
-    "* Rated power = 500kW "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 56,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "power_kW = results_df['power_signal'] / 1e3\n",
+        "h2rate_kg_hr = results_df['kg_rate'] * 3600 \n",
+        "\n",
+        "lhv = 33.33 \n",
+        "eff_conv = lhv * h2rate_kg_hr / power_kW \n",
+        "\n",
+        "fig, ax = plt.subplots()\n",
+        "ax.set_title('H2 Production and Conversion Efficiency')\n",
+        "ax.plot(power_kW, h2rate_kg_hr, label='H2 Production', color='green')\n",
+        "ax.set_xlabel(\"Total Power [kW]\")\n",
+        "ax.set_ylabel(\"Mass Flow-Rate [kg/hr]\")\n",
+        "ax.vlines(x=rated_power, ymin=0, ymax=1.2*h2rate_kg_hr.max(), linestyle='dashed', color='black', label='Rated-Power')\n",
+        "plt.legend(loc='lower right')\n",
+        "\n",
+        "ax2 = ax.twinx()\n",
+        "ax2.plot(power_kW, eff_conv, color='orange', label='Efficiency')\n",
+        "ax2.set_ylabel(\"Effiency\")\n",
+        "plt.legend()\n",
+        "plt.grid()"
       ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
     }
-   ],
-   "source": [
-    "power_kW = results_df['power_signal'] / 1e3\n",
-    "h2rate_kg_hr = results_df['kg_rate'] * 3600 \n",
-    "\n",
-    "lhv = 33.33 \n",
-    "eff_conv = lhv * h2rate_kg_hr / power_kW \n",
-    "\n",
-    "fig, ax = plt.subplots()\n",
-    "ax.set_title('H2 Production and Conversion Efficiency')\n",
-    "ax.plot(power_kW, h2rate_kg_hr, label='H2 Production', color='green')\n",
-    "ax.set_xlabel(\"Total Power [kW]\")\n",
-    "ax.set_ylabel(\"Mass Flow-Rate [kg/hr]\")\n",
-    "ax.vlines(x=rated_power, ymin=0, ymax=1.2*h2rate_kg_hr.max(), linestyle='dashed', color='black', label='Rated-Power')\n",
-    "plt.legend(loc='lower right')\n",
-    "\n",
-    "ax2 = ax.twinx()\n",
-    "ax2.plot(power_kW, eff_conv, color='orange', label='Efficiency')\n",
-    "ax2.set_ylabel(\"Effiency\")\n",
-    "plt.legend()\n",
-    "plt.grid()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3.8.13 ('hopp')",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3.8.13 ('hopp')",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.8.17"
+    },
+    "orig_nbformat": 4,
+    "vscode": {
+      "interpreter": {
+        "hash": "9a04511d318809dd12c12e36f25289adaaf050c85c4c458841c399d183c75e5d"
+      }
+    }
   },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "9a04511d318809dd12c12e36f25289adaaf050c85c4c458841c399d183c75e5d"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
+  "nbformat": 4,
+  "nbformat_minor": 2
 }
diff --git a/examples/example_06_conversion_efficiency/modeling_options.yaml b/examples/example_06_conversion_efficiency/modeling_options.yaml
index ec221c5..ab9a923 100644
--- a/examples/example_06_conversion_efficiency/modeling_options.yaml
+++ b/examples/example_06_conversion_efficiency/modeling_options.yaml
@@ -4,13 +4,13 @@ general:
 electrolyzer:
     dt: 1 # default
     initialize: True #
-    initial_power_kW: 500.
+    initial_power_kW: 1250.
     stack:
-        cell_area: 1000.0
-        max_current: 2000
+        cell_area: 1500.0
+        max_current: 3000
         temperature: 60
-        n_cells: 100
-        stack_rating_kW: 500.
+        n_cells: 200
+        stack_rating_kW: 1250.
     control:
         n_stacks: 1
         control_type: BaselineDeg # default