adapt standalone nb to match updates

docs/content/examples/example_electric_vehicle_premise.ipynb

@@ -16,16 +16,6 @@
     "> **Note:** This is the \"premise\" version of this notebook that works with ecoinvent and premise data. If you don't have access to that, please check out the [\"standalone\" version](https://github.com/brightway-lca/bw_timex/blob/main/notebooks/example_electric_vehicle_standalone.ipynb) of this notebook.\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# import bw2io as bi\n",
-    "# bi.restore_project_directory(\"/Users/timodiepers/brightway2-project-timex-backup16-August-2024-01-41PM.tar.gz\", \"timex\", True)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 18,
@@ -41,7 +31,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Prospective databases\n",
+    "## Prospective background databases\n",
     "\n",
     "The `bw_timex` package itself does not provide any data - specifying prospective and dynamic information is up to the user. In this example, we use data from [ecoinvent v3.10](https://ecoinvent.org/), and create a set of prospective databases with [`premise`](https://github.com/polca/premise). We applied projections for the future electricity sectors using the SSP2-RCP19 pathway from the IAM IMAGE. We selected this pathway to simply demonstrate some future development in this case study, and many other models and pathways are available. \n",
     "In the [premise documentation](https://premise.readthedocs.io/en/latest/) you can find instructions for the creation of prospective background databases. \n"
@@ -683,8 +673,6 @@
     }
    ],
    "source": [
-    "from bw_timex import TimexLCA\n",
-    "\n",
     "tlca = TimexLCA({driving: 1}, method, database_date_dict)"
    ]
   },