Forecast¶
This example have 2 identical and parallel reservoirs with plants with different inflow series.
[1]:
import os
import numpy as np
from pyltmapi import LtmSession, LtmPlot, LtmDot
import logging
logging.basicConfig(level=logging.INFO)
from pathlib import Path
ltm_core_path = os.environ.get("LTM_CORE_PATH", str(Path("~").expanduser().joinpath("ltm/release/bin/")))
license_file = os.environ.get("LTM_CORE_LICENSE_FILE", str(Path("~").expanduser().joinpath("ltm/ltm-license.dat")))
[2]:
from IPython.display import HTML, Image, display, display_markdown
ltmapi_version = LtmSession.version()
display(f"pyltm version {ltmapi_version}")
'pyltm version PyLTM version: 0.21.0'
[3]:
def usercallback(program_info: dict, userdata: any):
print(userdata)
print(program_info)
return True
def generate_plots(ltm):
# Water values and price series
for busbar in ltm.model.busbars():
display_markdown(f"# Busbar: {busbar}", raw=True)
# Water values
if busbar.have_water_value_results():
LtmPlot.make_water_value_plot(busbar.water_value_results(), busbar.name)
# Market results
LtmPlot.make_market_results_plot(busbar.market_result_price(), busbar.name)
# Detailed hydro results from
for busbar in ltm.model.busbars():
display_markdown(f"## {busbar}", raw=True)
# Busbar reservoirs
for rsv in busbar.reservoirs():
display("Reservoir")
LtmPlot.make_generic_plot(rsv.reservoir(), f"Reservoir '{rsv.name}'")
# LtmPlot.make_generic_plot(rsv.discharge(), f"Discharge '{rsv.name}'")
LtmPlot.make_generic_plot(rsv.inflow(), f"Inflow '{rsv.name}'")
# LtmPlot.make_generic_plot(rsv.production(), f"Production '{rsv.name}'")
# LtmPlot.make_generic_plot(rsv.bypass(), f"Bypass '{rsv.name}'")
# LtmPlot.make_generic_plot(rsv.spill(), f"Spill '{rsv.name}'")
[4]:
def open_and_write_model(filename: str):
session = LtmSession("ikernel", ltm_core_path=ltm_core_path, overwrite_session=True)
# Explicitly set license file
session.model.global_settings.ltm_license_file_path = license_file
with session:
try:
# Load model from file.
session.load(filename=filename)
print(vars(session.model.global_settings))
# Write model to disk, and automatically generate an output directory.
session.write_model()
# return
# Display model graph
LtmDot.display_dot_image(session.build_connection_tree())
# LtmDot.display_dot_image(session.build_busbar_graph())
# return
# Execute/run LTM/EMPS on the model
last_rc, results = session.execute_model()
# If last return code is not 0, then there was an error.
if last_rc != 0:
err = results[0]["log_file_contents"]
LtmDot.print(err)
else:
# Make plots from the results
generate_plots(session)
except Exception as e:
print(e)
raise (e)
[5]:
open_and_write_model("forecast.json")
INFO:LtmApiModel:(ikernel) Loading model from file: forecast.json
INFO:LtmApiModel:(ikernel) LtmApiModel::maybe_generate_output_dir: output_path: /builds/energy/ltm/pyltmapi/docs/ltm-api/guides/forecast/testout_forecast/2026-03-24-134129.003-EMPS-parallell
INFO:LtmApiModel:(ikernel) Using license file '/builds/energy/ltm/pyltmapi.tmp/CI_LTM_LICENSE_FILE'
INFO:LtmApiModel:(ikernel) Using license file '/builds/energy/ltm/pyltmapi.tmp/CI_LTM_LICENSE_FILE'
INFO:Validator:(ikernel) Model validation succeeded
INFO:LtmApiModel:(ikernel) Writing model to path /builds/energy/ltm/pyltmapi/docs/ltm-api/guides/forecast/testout_forecast/2026-03-24-134129.003-EMPS-parallell
INFO:Validator:(ikernel) Model validation succeeded
{}
INFO:LtmApiModel:(ikernel) Model executed successfully
Busbar: busbar/forecast¶
Busbar: busbar/tev¶
busbar/forecast¶
'Reservoir'
'Reservoir'
busbar/tev¶
INFO:LtmApiModel:(ikernel) Not deleting output dir (/builds/energy/ltm/pyltmapi/docs/ltm-api/guides/forecast/testout_forecast/2026-03-24-134129.003-EMPS-parallell), as delete_output_dir: false, and has_generated_output_dir: true
INFO:LtmApiModel:(ikernel) Not deleting output dir (/builds/energy/ltm/pyltmapi/docs/ltm-api/guides/forecast/testout_forecast/2026-03-24-134129.003-EMPS-parallell), as delete_output_dir: false, and has_generated_output_dir: true