Progress System Data Module

class progress.mod_sysdata.RASystemData

Bases: object

Manages and processes the core system data needed for resource adequacy (RA) assessments.

This class provides methods to read and extract power system information from CSV files:

  • Branch data (e.g., line capacities, MTTF/MTTR)

  • Bus data (bus names, bus numbers)

  • Generator data (pmax, pmin, forced outage rates, maintenance times, costs)

  • Storage data (ESS ratings, SOC constraints, costs, reliability parameters)

  • Load data (regional load profiles)

These methods facilitate easy import and organization of data so that reliability or adequacy simulations can be conducted downstream (e.g., Monte Carlo simulations).

branch(data_branch)

Loads branch (transmission line) data and extracts key attributes for RA analysis.

Parameters:

data_branch (str) – Path to the CSV file containing branch data, typically including columns like “From Bus”, “To Bus”, “Rating”, “MTTF”, “MTTR”, etc.

Returns:

A tuple containing:

  • nl (int): Number of transmission lines (rows in the CSV).

  • fb (np.ndarray): 1D array of “From Bus” indices for each line.

  • tb (np.ndarray): 1D array of “To Bus” indices for each line.

  • cap_trans (np.ndarray): 1D array of transmission line ratings (MW).

  • MTTF_trans (np.ndarray): Mean time to failure for each line (hours).

  • MTTR_trans (np.ndarray): Mean time to repair for each line (hours).

Return type:

tuple

Raises:

  • FileNotFoundError – If data_branch does not point to a valid file.

  • pd.errors.EmptyDataError – If the CSV file is empty or badly formatted.

bus(data_bus)

Loads bus data and extracts bus names and numbers.

Parameters:

data_bus (str) – Path to the CSV file containing bus data, often with columns “Bus Name” and “Bus No.”.

Returns:

A tuple containing:

  • bus_name (pd.Series): Series of bus names.

  • bus_no (np.ndarray): 1D array of bus indices.

  • nz (int): Number of buses (length of bus_no).

Return type:

tuple

Raises:

  • FileNotFoundError – If data_bus is not found.

  • pd.errors.EmptyDataError – If the CSV is empty or invalid.

gen(data_gen)

Loads conventional generator data, including capacities and reliability parameters.

Parameters:

data_gen (str) – Path to the CSV file containing generator info (e.g., “Bus No.”, “Max Cap”, “Min Cap”, “FOR”, “MTTF”, “MTTR”, “Cost”).

Returns:

A tuple containing:

  • genbus (np.ndarray): Bus indices (1D) for each generator.

  • ng (int): Number of generators in the system.

  • pmax (np.ndarray): Max capacity (MW) of each generator.

  • pmin (np.ndarray): Min capacity (MW) of each generator.

  • FOR_gen (np.ndarray): Forced outage rate of each generator.

  • MTTF_gen (np.ndarray): Mean time to failure (hours).

  • MTTR_gen (np.ndarray): Mean time to repair (hours).

  • gencost (np.ndarray): Generation cost for each generator.

Return type:

tuple

Raises:

  • FileNotFoundError – If data_gen file is not found.

  • pd.errors.EmptyDataError – If the CSV is empty or malformed.

load(bus_name, data_load)

Loads and returns time-series load data (demand) for specified bus(es).

Parameters:

  • bus_name (str or list[str]) – Column label(s) in the load CSV corresponding to each region’s load. Can be a string for a single bus or a list of strings for multiple buses.

  • data_load (str) – Path to the CSV file containing hourly or sub-hourly load data.

Returns:

A NumPy array containing load values. Its shape depends on whether bus_name references one or multiple columns.

Return type:

np.ndarray

Raises:

  • FileNotFoundError – If data_load is not found.

  • pd.errors.EmptyDataError – If the CSV is empty or invalid.

storage(data_storage)

Loads and returns data on energy storage systems (ESS), including power ratings and SOC limits.

Parameters:

data_storage (str) – Path to the CSV file containing ESS data (e.g., “Pmax”, “Pmin”, “Duration”, “max_SOC”, “min_SOC”, “MTTF”, “MTTR”, etc.).

Returns:

A tuple containing:

  • essname (pd.Series): Names/IDs for each ESS unit.

  • essbus (np.ndarray): Bus indices corresponding to each ESS.

  • ness (int): Number of ESS units.

  • ess_pmax (np.ndarray): Maximum power output (MW) for each ESS.

  • ess_pmin (np.ndarray): Minimum power output (MW) for each ESS.

  • ess_duration (np.ndarray): Duration (hours) of each ESS at rated power.

  • ess_socmax (np.ndarray): Max SOC fraction for each ESS (0-1).

  • ess_socmin (np.ndarray): Min SOC fraction for each ESS (0-1).

  • ess_eff (np.ndarray): Round-trip efficiency of each ESS.

  • disch_cost (np.ndarray): Discharge cost for each ESS.

  • ch_cost (np.ndarray): Charge cost for each ESS.

  • MTTF_ess (np.ndarray): Mean time to failure (hours) for each ESS.

  • MTTR_ess (np.ndarray): Mean time to repair (hours) for each ESS.

  • ess_units (np.ndarray): Multiplicities or number of identical ESS units.

Return type:

tuple

Raises:

  • FileNotFoundError – If data_storage file does not exist.

  • pd.errors.EmptyDataError – If the CSV is empty or malformed.