# -*- coding: utf-8 -*-

# Copyright (c) 2016-2026 by University of Kassel and Fraunhofer Institute for Energy Economics
# and Energy System Technology (IEE), Kassel. All rights reserved.

from __future__ import annotations

import logging
from typing import Iterable, Sequence

from numpy import nan, bool_
import numpy.typing as npt

from pandapower.auxiliary import pandapowerNet
from pandapower.pp_types import Int, UnderOverExcitedType, WyeDeltaType
from pandapower.create._utils import (
    _add_to_entries_if_not_nan,
    _check_element,
    _check_multiple_elements,
    _get_index_with_check,
    _get_multiple_index_with_check,
    _set_const_percent_values,
    _set_entries,
    _set_multiple_entries,
    _set_value_if_not_nan,
)

logger = logging.getLogger(__name__)


def create_load(
    net: pandapowerNet,
    bus: Int,
    p_mw: float,
    q_mvar: float = 0,
    const_z_p_percent: float = 0,
    const_i_p_percent: float = 0,
    const_z_q_percent: float = 0,
    const_i_q_percent: float = 0,
    sn_mva: float = nan,
    name: str | None = None,
    scaling: float = 1.0,
    index: Int | None = None,
    in_service: bool = True,
    type: WyeDeltaType = "wye",
    max_p_mw: float = nan,
    min_p_mw: float = nan,
    max_q_mvar: float = nan,
    min_q_mvar: float = nan,
    controllable: bool | float = nan,
    **kwargs,
) -> Int:
    """
    Adds one load in table net["load"].

    All loads are modelled in the consumer system, meaning load is positive and generation is
    negative active power. Please pay attention to the correct signing of the reactive power as
    well.

    Parameters:
        net: The net within this load should be created
        bus: The bus id to which the load is connected
        p_mw: The active power of the load

            - positive value -> load
            - negative value -> generation

        q_mvar: The reactive power of the load
        const_z_p_percent: percentage of p_mw that will be associated to constant impedance load at rated voltage
        const_i_p_percent: percentage of p_mw that will be associated to constant current load at rated voltage
        const_z_q_percent: percentage of q_mvar that will be associated to constant impedance load at rated voltage
        const_i_q_percent: percentage of q_mvar that will be associated to constant current load at rated voltage
        sn_mva: Nominal power of the load
        name: The name for this load
        scaling: An OPTIONAL scaling factor. Multiplies with p_mw and q_mvar.
        type: type variable to classify the load: wye/delta
        index: Force a specified ID if it is available. If None, the index one higher than the highest already existing
            index is selected.
        in_service: True for in_service or False for out of service
        max_p_mw: Maximum active power load - necessary for controllable loads in for OPF
        min_p_mw: Minimum active power load - necessary for controllable loads in for OPF
        max_q_mvar: Maximum reactive power load - necessary for controllable loads in for OPF
        min_q_mvar: Minimum reactive power load - necessary for controllable loads in OPF
        controllable: States, whether a load is controllable or not. Only respected for OPF; defaults to False if
            "controllable" column exists in DataFrame

    Return:
        The ID of the created load

    Example:
        >>> create_load(net, bus=0, p_mw=10., q_mvar=2.)
    """
    _check_element(net, bus)

    index = _get_index_with_check(net, "load", index)

    if ("const_z_percent" in kwargs) or ("const_i_percent" in kwargs):
        const_percent_values_list = [const_z_p_percent, const_i_p_percent, const_z_q_percent, const_i_q_percent]
        const_z_p_percent, const_i_p_percent, const_z_q_percent, const_i_q_percent, kwargs = _set_const_percent_values(
            const_percent_values_list, kwargs_input=kwargs
        )

    entries = {
        "name": name,
        "bus": bus,
        "p_mw": p_mw,
        "const_z_p_percent": const_z_p_percent,
        "const_i_p_percent": const_i_p_percent,
        "const_z_q_percent": const_z_q_percent,
        "const_i_q_percent": const_i_q_percent,
        "scaling": scaling,
        "q_mvar": q_mvar,
        "sn_mva": sn_mva,
        "in_service": in_service,
        "type": type,
        **kwargs,
    }
    _set_entries(net, "load", index, True, entries=entries)

    _set_value_if_not_nan(net, index, min_p_mw, "min_p_mw", "load")
    _set_value_if_not_nan(net, index, max_p_mw, "max_p_mw", "load")
    _set_value_if_not_nan(net, index, min_q_mvar, "min_q_mvar", "load")
    _set_value_if_not_nan(net, index, max_q_mvar, "max_q_mvar", "load")
    _set_value_if_not_nan(net, index, controllable, "controllable", "load", dtype=bool_, default_val=False)

    return index


def create_loads(
    net: pandapowerNet,
    buses: Sequence,
    p_mw: float | Iterable[float],
    q_mvar: float | Iterable[float] = 0,
    const_z_p_percent: float | Iterable[float] = 0,
    const_i_p_percent: float | Iterable[float] = 0,
    const_z_q_percent: float | Iterable[float] = 0,
    const_i_q_percent: float | Iterable[float] = 0,
    sn_mva: float | Iterable[float] = nan,
    name: Iterable[str] | None = None,
    scaling: float | Iterable[float] = 1.0,
    index: Int | Iterable[Int] | None = None,
    in_service: bool | Iterable[bool] = True,
    type: WyeDeltaType = "wye",
    max_p_mw: float | Iterable[float] = nan,
    min_p_mw: float | Iterable[float] = nan,
    max_q_mvar: float | Iterable[float] = nan,
    min_q_mvar: float | Iterable[float] = nan,
    controllable: bool | Iterable[bool] | float = nan,
    **kwargs,
) -> npt.NDArray[Int]:
    """
    Adds a number of loads in table net["load"].

    All loads are modelled in the consumer system, meaning load is positive and generation is
    negative active power. Please pay attention to the correct signing of the reactive power as
    well.

    Parameters:
        net: The net within this load should be created
        buses: A list of bus ids to which the loads are connected
        p_mw: The active power of the loads

            - positive value   -> load
            - negative value  -> generation

        q_mvar: The reactive power of the loads
        const_z_p_percent: percentage of p_mw that will be associated to constant impedance loads at rated voltage
        const_i_p_percent: percentage of p_mw that will be associated to constant current load at rated voltage
        const_z_q_percent: percentage of q_mvar that will be associated to constant impedance loads at rated voltage
        const_i_q_percent: percentage of q_mvar that will be associated to constant current load at rated voltage
        sn_mva: Nominal power of the loads
        name: The name for this load
        scaling: An OPTIONAL custom scaling factor. Multiplies with p_mw and q_mvar.
        type: type variable to classify the load
        index: Force a specified ID if it is available. If None, the index is set to a range between one higher than the
            highest already existing index and the length of loads that shall be created.
        in_service: True for in_service or False for out of service
        max_p_mw: Maximum active power load - necessary for controllable loads in for OPF
        min_p_mw: Minimum active power load - necessary for controllable loads in for OPF
        max_q_mvar: Maximum reactive power load - necessary for controllable loads in for OPF
        min_q_mvar: Minimum reactive power load - necessary for controllable loads in OPF
        controllable: States, whether a load is controllable or not. Only respected for OPF Defaults to False if
            "controllable" column exists in DataFrame

    Returns:
        The IDs of the created loads

    Example:
        >>> create_loads(net, buses=[0, 2], p_mw=[10., 5.], q_mvar=[2., 0.])
    """
    _check_multiple_elements(net, buses)

    index = _get_multiple_index_with_check(net, "load", index, len(buses))

    if ("const_z_percent" in kwargs) or ("const_i_percent" in kwargs):
        const_percent_values_list = [const_z_p_percent, const_i_p_percent, const_z_q_percent, const_i_q_percent]
        const_z_p_percent, const_i_p_percent, const_z_q_percent, const_i_q_percent, kwargs = _set_const_percent_values(
            const_percent_values_list, kwargs_input=kwargs
        )

    entries = {
        "bus": buses,
        "p_mw": p_mw,
        "q_mvar": q_mvar,
        "sn_mva": sn_mva,
        "const_z_p_percent": const_z_p_percent,
        "const_i_p_percent": const_i_p_percent,
        "const_z_q_percent": const_z_q_percent,
        "const_i_q_percent": const_i_q_percent,
        "scaling": scaling,
        "in_service": in_service,
        "name": name,
        "type": type,
        **kwargs,
    }

    _add_to_entries_if_not_nan(net, "load", entries, index, "min_p_mw", min_p_mw)
    _add_to_entries_if_not_nan(net, "load", entries, index, "max_p_mw", max_p_mw)
    _add_to_entries_if_not_nan(net, "load", entries, index, "min_q_mvar", min_q_mvar)
    _add_to_entries_if_not_nan(net, "load", entries, index, "max_q_mvar", max_q_mvar)
    _add_to_entries_if_not_nan(
        net, "load", entries, index, "controllable", controllable, dtype=bool_, default_val=False
    )
    defaults_to_fill = [("controllable", False)]

    _set_multiple_entries(net, "load", index, defaults_to_fill=defaults_to_fill, entries=entries)

    return index


def create_asymmetric_load(
    net: pandapowerNet,
    bus: Int,
    p_a_mw: float = 0,
    p_b_mw: float = 0,
    p_c_mw: float = 0,
    q_a_mvar: float = 0,
    q_b_mvar: float = 0,
    q_c_mvar: float = 0,
    sn_a_mva: float=nan,
    sn_b_mva: float=nan,
    sn_c_mva: float=nan,
    sn_mva: float = nan,
    name: str | None = None,
    scaling: float = 1.0,
    index: Int | None = None,
    in_service: bool = True,
    type: WyeDeltaType = "wye",
    **kwargs,
) -> Int:
    """
    Adds one 3 phase load in table net["asymmetric_load"].

    All loads are modelled in the consumer system, meaning load is positive and generation is
    negative active power. Please pay attention to the correct signing of the reactive power as
    well.

    Parameters:
        net: The net within this load should be created
        bus: The bus id to which the load is connected
        p_a_mw: The active power for Phase A load
        p_b_mw: The active power for Phase B load
        p_c_mw: The active power for Phase C load
        q_a_mvar: The reactive power for Phase A load
        q_b_mvar: The reactive power for Phase B load
        q_c_mvar: The reactive power for Phase C load
        sn_a_mva: Nominal power for Phase A load
        sn_b_mva: Nominal power for Phase B load
        sn_c_mva: Nominal power for Phase C load
        sn_mva: Nominal power of the load
        name: The name for this load
        scaling: An OPTIONAL custom scaling factor. Multiplies with p_mw and q_mvar of all phases.
        type:  type variable to classify three ph load: delta/wye
        index: Force a specified ID if it is available. If None, the index one higher than the highest already existing
            index is selected.
        in_service: True for in_service or False for out of service

    Returns:
        The ID of the created asymmetric load

    Example:
        >>> create_asymmetric_load(net, bus=0, p_c_mw=9., q_c_mvar=1.8)
    """
    _check_element(net, bus)

    index = _get_index_with_check(net, "asymmetric_load", index, name="3 phase asymmetric_load")

    entries = {
        "name": name,
        "bus": bus,
        "p_a_mw": p_a_mw,
        "p_b_mw": p_b_mw,
        "p_c_mw": p_c_mw,
        "scaling": scaling,
        "q_a_mvar": q_a_mvar,
        "q_b_mvar": q_b_mvar,
        "q_c_mvar": q_c_mvar,
        "sn_a_mva": sn_a_mva,
        "sn_b_mva": sn_b_mva,
        "sn_c_mva": sn_c_mva,
        "sn_mva": sn_mva,
        "in_service": in_service,
        "type": type,
        **kwargs,
    }
    _set_entries(net, "asymmetric_load", index, True, entries=entries)

    return index


# =============================================================================
# def create_impedance_load(net, bus, r_A , r_B , r_C, x_A=0, x_B=0, x_C=0,
#                      sn_mva=nan, name=None, scaling=1.,
#                     index = None, in_service=True, type=None,
#                     ):
#     """
#     Creates a constant impedance load element ABC.
#
#     INPUT:
#         **net** - The net within this constant impedance load should be created
#
#         **bus** (int) - The bus id to which the load is connected
#
#         **sn_mva** (float) - rated power of the load
#
#         **r_A** (float) - Resistance in Phase A
#         **r_B** (float) - Resistance in Phase B
#         **r_C** (float) - Resistance in Phase C
#         **x_A** (float) - Reactance in Phase A
#         **x_B** (float) - Reactance in Phase B
#         **x_C** (float) - Reactance in Phase C
#
#
#         **kwargs are passed on to the create_load function
#
#     OUTPUT:
#         **index** (int) - The unique ID of the created load
#
#     Load elements are modeled from a consumer point of view. Active power will therefore always be
#     positive, reactive power will be positive for under-excited behavior (Q absorption, decreases voltage) and
#     negative for over-excited behavior (Q injection, increases voltage)
#     """
#     if bus not in net["bus"].index.values:
#         raise UserWarning("Cannot attach to bus %s, bus does not exist" % bus)
#
#     if index is None:
#         index = get_free_id(net["asymmetric_load"])
#     if index in net["impedance_load"].index:
#         raise UserWarning("A 3 phase asymmetric_load with the id %s already exists" % index)
#
#     # store dtypes
#     dtypes = net.impedance_load.dtypes
#
#     net.impedance_load.loc[index, ["name", "bus", "r_A","r_B","r_C", "scaling",
#                       "x_A","x_B","x_C","sn_mva", "in_service", "type"]] = \
#     [name, bus, r_A,r_B,r_C, scaling,
#       x_A,x_B,x_C,sn_mva, in_service, type]
#
#     # and preserve dtypes
#     _preserve_dtypes(net.impedance_load, dtypes)
#
#     return index
#
# =============================================================================


def create_load_from_cosphi(  # no index ?
    net: pandapowerNet, bus: Int, sn_mva: float, cos_phi: float, mode: UnderOverExcitedType, **kwargs
) -> Int:
    """
    Creates a load element from rated power and power factor cos(phi).

    Parameters:
        net: The net within this static generator should be created
        bus: The bus id to which the load is connected
        sn_mva: rated power of the load
        cos_phi: power factor cos_phi
        mode:
        
            - "underexcited" (Q absorption, decreases voltage)
            - "overexcited" (Q injection, increases voltage)

        **kwargs: any parameter from create_load, as these get passed to the create_load function

    Returns:
        The ID of the created load

    Load elements are modeled from a consumer point of view. Active power will therefore always be
    positive, reactive power will be positive for underexcited behavior (Q absorption, decreases voltage) and negative
    for overexcited behavior (Q injection, increases voltage).
    """
    from pandapower.toolbox import pq_from_cosphi

    p_mw, q_mvar = pq_from_cosphi(sn_mva, cos_phi, qmode=mode, pmode="load")
    return create_load(net, bus, sn_mva=sn_mva, p_mw=p_mw, q_mvar=q_mvar, **kwargs)


def create_load_dc(
    net: pandapowerNet,
    bus_dc: Int,
    p_dc_mw: float,
    scaling: float = 1.0,
    type: str | None = None,
    index: Int | None = None,
    name: str | None = None,
    in_service: bool = True,
    controllable: bool = False,
    **kwargs,
):
    """
    Creates a dc voltage source in a dc grid with an adjustable set point
    
    Parameters:
        net: The pandapower network in which the element is created
        bus_dc: index of the dc bus the dc load is connected to
        p_dc_mw: The power of the load
        name: element name
        index: Force a specified ID if it is available. If None, the index one higher than the highest already existing index is selected.
        in_service: True for in service or False for out of service.
        scaling: An OPTIONAL scaling factor, is multiplied with p_dc_mw.
        type: A string describing the type.
        controllable: States, whether a load is controllable or not. Only respected for OPF; defaults to False if
            "controllable" column exists in DataFrame

    Returns:
        The ID of the created svc

    """
    _check_element(net, bus_dc, element="bus_dc")

    index = _get_index_with_check(net, "source_dc", index=index)

    entries = {
        "name": name,
        "bus_dc": bus_dc,
        "p_dc_mw": p_dc_mw,
        "in_service": in_service,
        "scaling": scaling,
        "type": type,
        "controllable": controllable,
        **kwargs,
    }
    _set_entries(net, "load_dc", index, True, entries=entries)

    return index
