Source code for pandaprosumer.controller.models.electric_boiler

"""
Module containing the ElectricBoilerController class.
"""

import numpy as np
from math import log
import pandas as pd
from numba import njit

from pandapipes import create_fluid_from_lib, call_lib
from pandaprosumer.mapping.fluid_mix import FluidMixMapping
from pandaprosumer.constants import CELSIUS_TO_K
from pandaprosumer.controller.base import BasicProsumerController


def _calculate_electric_boiler_temp(mdot_kg_per_s, t_out_c, t_in_c, cp_fluid_kj_per_kgk, efficiency_percent, max_p_kw):
    # 1. Calculate power of condenser
    q_fluid_kw = mdot_kg_per_s * cp_fluid_kj_per_kgk * (t_out_c - t_in_c)

    p_el_consumed_kw = q_fluid_kw / (efficiency_percent / 100)

    # 8. Check parameters
    if max_p_kw and p_el_consumed_kw > max_p_kw + 1e-3:  # ToDo: Check numba if max_p_kw Nan
        # If the consumed electrical power is too high, recalculate the output temperature
        p_el_consumed_kw = max_p_kw
        q_fluid_kw = max_p_kw * (efficiency_percent / 100)
        # FixMe: Should update the output temperature or the mass flow rate ?
        t_out_c = t_in_c + q_fluid_kw / (mdot_kg_per_s * cp_fluid_kj_per_kgk)

    return q_fluid_kw, mdot_kg_per_s, t_in_c, t_out_c, p_el_consumed_kw


[docs] class ElectricBoilerController(BasicProsumerController): """ Controller for electric boilers. :param prosumer: The prosumer object :param electric_boiler_object: The electric boiler object :param order: The order of the controller :param level: The level of the controller :param in_service: The in-service status of the controller :param index: The index of the controller :param kwargs: Additional keyword arguments """ @classmethod def name(cls): return "electric_boiler" def __init__(self, prosumer, electric_boiler_object, order, level, in_service=True, index=None, name=None, **kwargs): """ Initializes the ElectricBoilerController. """ super().__init__(prosumer, electric_boiler_object, order=order, level=level, in_service=in_service, index=index, name=name, **kwargs) self.fluid = prosumer.fluid def _calculate_electric_boiler(self, prosumer, mdot_kg_per_s, t_out_c, t_in_c): """ Main method for Electric Boiler physical calculation during one time step :param mdot_kg_per_s: Mass flow rate in kg/s :param t_out_c: Output provided temperature to the feed pipe in °C :param t_in_c: Input temperature from return pipe in °C """ cp_fluid_kj_per_kgk = self.fluid.get_heat_capacity(CELSIUS_TO_K + (t_out_c + t_in_c) / 2) / 1000 efficiency_percent = self._get_element_param(prosumer, 'efficiency_percent') max_p_kw = self._get_element_param(prosumer, 'max_p_kw') q_fluid_kw = mdot_kg_per_s * cp_fluid_kj_per_kgk * (t_out_c - t_in_c) p_el_consumed_kw = q_fluid_kw / (efficiency_percent / 100) q_fluid_kw, mdot_kg_per_s, t_in_c, t_out_c, p_el_consumed_kw = _calculate_electric_boiler_temp(mdot_kg_per_s, t_out_c, t_in_c, cp_fluid_kj_per_kgk, efficiency_percent, max_p_kw) return q_fluid_kw, mdot_kg_per_s, t_in_c, t_out_c, p_el_consumed_kw
[docs] def control_step(self, prosumer): """ Executes the control step for the controller. :param prosumer: The prosumer object """ super().control_step(prosumer) t_out_required_c, t_in_required_c, mdot_tab_required_kg_per_s = self.t_m_to_deliver(prosumer) mdot_required_kg_per_s = np.sum(mdot_tab_required_kg_per_s) assert not np.isnan(t_out_required_c), f"Electric Boiler {self.name} t_out_required_c is NaN for timestep {self.time} in prosumer {prosumer.name}" assert not np.isnan(t_in_required_c), f"Electric Boiler {self.name} t_in_required_c is NaN for timestep {self.time} in prosumer {prosumer.name}" assert not np.isnan(mdot_required_kg_per_s).any(), f"Electric Boiler {self.name} mdot_required_kg_per_s is NaN for timestep {self.time} in prosumer {prosumer.name}" assert t_out_required_c >= t_in_required_c, f"Electric Boiler {self.name} t_out_required_c is lower than t_in_required_c for timestep {self.time} in prosumer {prosumer.name}" rerun = True nb_runs = 0 while rerun: nb_runs += 1 if nb_runs > 20: raise Exception("Heat Exchanger calculation did not converge after 100 iterations", self.name, self.time, prosumer.name) q_kw, mdot_delivered_kg_per_s, t_in_c, t_out_c, p_kw = self._calculate_electric_boiler(prosumer, mdot_required_kg_per_s, t_out_required_c, t_in_required_c) result_mdot_tab_kg_per_s = self._merit_order_mass_flow(prosumer, mdot_delivered_kg_per_s, mdot_tab_required_kg_per_s) rerun = False if len(self._get_mapped_responders(prosumer)) > 1 and mdot_delivered_kg_per_s < mdot_required_kg_per_s: # If the electric boiler is not able to deliver the required mass flow, # recalculate the input temperature, considering that all the downstream elements will be # still return the same temperature, even if the mass flow delivered to them by the Boiler is lower t_return_tab_c = self.get_treturn_tab_c(prosumer) if abs(mdot_delivered_kg_per_s) > 1e-8: t_in_new_c = np.sum(result_mdot_tab_kg_per_s * t_return_tab_c) / mdot_delivered_kg_per_s else: t_in_new_c = t_in_required_c if abs(t_in_new_c - t_in_required_c) > 1: # If this recalculation changes the input temperature, rerun the calculation # with the new temperature t_in_required_c = t_in_new_c rerun = True assert q_kw >= 0, f"Electric Boiler {self.name} q_kw is negative ({q_kw}) for timestep {self.time} in prosumer {prosumer.name}" assert p_kw >= 0, f"Electric Boiler {self.name} p_kw is negative ({p_kw}) for timestep {self.time} in prosumer {prosumer.name}" result_fluid_mix = [] for mdot_kg_per_s in result_mdot_tab_kg_per_s: result_fluid_mix.append({FluidMixMapping.TEMPERATURE_KEY: t_out_c, FluidMixMapping.MASS_FLOW_KEY: mdot_kg_per_s}) result = np.array([[q_kw, mdot_delivered_kg_per_s, t_in_c, t_out_c, p_kw]]) self.finalize(prosumer, result, result_fluid_mix) self.applied = True