Multi-Weather-Year Input Generation

The weatheryear module converts outputs from external models (CorRES, demand, hydro, and COP models) into Balmorel-compatible .inc files for a chosen historical weather year (1980–2021). This allows you to run Balmorel with multiple weather-year scenarios to capture annual variability of renewable energy sources and demand.

Installation

pyyaml and xlsxwriter are required by this module but are not installed by default with pybalmorel. Install them via the weatheryear extra:

pip install pybalmorel[weatheryear]

Overview

The module produces Balmorel .inc files for the following data types:

Data type	Method	Key outputs
VRE time series (wind & solar)	`get_vre_data()`	Excel review files + `_VAR_T_.inc` files
VRE-related investment data	`get_vre_related_files()`	`AAA`, `GGG`, `GDATA`, `GKFX`, `ANNUITYCG`, `INVDATA` `.inc` files
Electricity & heat demand	`get_demand_data()`	`DE_VAR_T_.inc`, `DH_VAR_T_.inc`
Hydro inflow	`get_hydro_data()`	`HYDRO_ROR_VAR_T_.inc`, `HYDRO_RES_VAR_T_.inc`, `FLHO_*.inc`
Heat-pump COP factors	`get_cop_data()`	`SEASONALCOP_COP_VAR_T_*.inc`

Each method generates both Day-Ahead and CapDev time series.

Configuration File

All methods are driven by a single YAML configuration file. Below is an annotated template:

# Optional convenience key: weather-year input root folder.
# If provided, defaults are inferred for:
# corres_results, VRE_tech_costs, Existing_wind_cap, Existing_solar_cap,
# VRE_potentials, demand_model_results, hydro_model_results, cop_model_results.
weatheryear_inputs_folder: path/to/weatheryear_inputs

# Backward-compatible alternative key:
# multiweather_other_inputs_folder: path/to/weatheryear_inputs/multiweather_other_inputs

# Wind turbine models (future installations only)
turbine_to_keep:
  - SP335-HH100
  - SP277-HH150
  - SP199-HH150

# Resource grades to include per technology (RGA/B/C → RG1/2/3 in Balmorel)
RGs_to_keep:
  Future_Onshore: [RGA, RGB, RGC]
  Future_Offshore_bottom_fixed: [RGB]
  PV_Rooftop: [RGA, RGB, RGC]

# Geographic regions to include
Regions_to_keep:
  onshore: [DK1, DK2, FIN, DE4-E, DE4-N, ...]
  offshore: [DK1_OFF, DK2_OFF, FIN_OFF, DE4-N_OFF, ...]

# --- VRE investment 
ANNUITYCG_calculation:
  DEBT_SHARE: 0
  INTEREST_RATE: 0.04
  DISCOUNTRATE: 0.04

# --- Demand data ---
spaceHeat_to_hotWater_ratio: 0.7   # fraction of heat demand attributed to space heating
ann_corr_fac_ref_year: 2012        # reference year for annual correction factors


# --- CapDev time-series aggregation ---
# Representative seasons (S) and hours (T) used for the aggregated resolution
CapDev_timesteps_to_keep:
  S: [S02, S08, S15, S21, S28, S34, S41, S47]
  T: [T073, T076, T079, T082, T085, T088, T091, T094,
      T097, T100, T103, T106, T109, T112, T115, T118,
      T121, T124, T127, T130, T133, T136, T139, T142]

When weatheryear_inputs_folder is set, the module assumes this structure:

weatheryear_inputs/
├── Corres_runs/
├── demand_data/
├── hydro_data/
├── cop_data/
└── multiweather_other_inputs/

Defaults are resolved as follows:

corres_results from Corres_runs (or CorRES_runs if present)
VRE_tech_costs, VRE_potentials, Existing_wind_cap, Existing_solar_cap from multiweather_other_inputs
demand_model_results from demand_data (falls back to multiweather_other_inputs/Demand_model_Bal_ready_csv*)
hydro_model_results from hydro_data
cop_model_results from cop_data

Basic Usage

from pybalmorel import WEATHERYEAR

# Instantiate for a specific weather year
mly = WEATHERYEAR(
    year=2013,
    config_fn="config.yml",
    output_folder="results/",
)

# 1. Export VRE time series from CorRES to Excel and .inc files
mly.get_vre_data()

# 2. Generate VRE-related investment .inc files
mly.get_vre_related_files()

# 3. Generate electricity and heat demand .inc files
mly.get_demand_data()

# 4. Generate hydro inflow .inc files
mly.get_hydro_data()

# 5. Generate heat-pump COP .inc files
mly.get_cop_data()

After running, the output folder will have the structure:

results/
└── 2013/
    ├── Future_Onshore/               ← Excel stats files for review
    ├── Future_Offshore_bottom_fixed/
    ├── Existing_ERA5_GWA2/
    ├── PV_Rooftop/
    ├── ...
    └── to_balmorel/                  ← .inc files ready for Balmorel
        ├── WND_VAR_T_Future_Onshore_2013.inc
        ├── SOL_VAR_T_PV_Rooftop_2013.inc
        ├── AAA_renewable.inc
        ├── GDATA_renewable.inc
        ├── DE_VAR_T_DK1_2013.inc
        ├── DH_VAR_T_DK1_2013.inc
        ├── HYDRO_ROR_VAR_T_2013.inc
        ├── SEASONALCOP_COP_VAR_T_2013.inc
        └── ...

Processing Multiple Years

Loop over years to build a full multi-weather-year dataset:

from pybalmorel import WEATHERYEAR

for year in range(1980, 2022):
    mly = WEATHERYEAR(year=year, config_fn="config.yml", output_folder="results/")
    mly.get_vre_data()
    mly.get_vre_related_files()
    mly.get_demand_data()
    mly.get_hydro_data()
    mly.get_cop_data()

API Reference

See the auto-generated API docs under Reference → pybalmorel.weatheryear for the full list of classes and functions exposed by this module.