Source code for oemof.thermal.solar_thermal_collector

# -*- coding: utf-8

This module is designed to hold functions for calculating a solar thermal collector.

This file is part of project oemof ( It's copyrighted
by the contributors recorded in the version control history of the file,
available from its original location:

SPDX-License-Identifier: MIT

import pvlib
import pandas as pd

[docs]def flat_plate_precalc( lat, long, collector_tilt, collector_azimuth, eta_0, a_1, a_2, temp_collector_inlet, delta_temp_n, irradiance_global, irradiance_diffuse, temp_amb ): r""" Calculates collectors heat, efficiency and irradiance of a flat plate collector. .. flat_plate_precalc_equation: :math:`\dot Q_{coll} = E_{coll} \cdot \eta_C` Parameters ---------- lat: numeric Latitude of the location. long: numeric Longitude of the location. collector_tilt: numeric The tilt of the collector. collector_azimuth: numeric The azimuth of the collector. Azimuth according to pvlib in decimal degrees East of North. eta_0: numeric Optical efficiency of the collector. a_1, a_2: numeric Thermal loss parameters. temp_collector_inlet: numeric or series with length of periods Collectors inlet temperature. delta_temp_n: numeric Temperature difference between collector inlet and mean temperature. irradiance_global: time indexed series Global horizontal irradiance. irradiance_diffuse: time indexed series Diffuse irradiance. temp_amb: time indexed series Ambient temperature. Returns ------- data : pandas.DataFrame DataFrame containing the followiing columns: * col_ira: The irradiance on the tilted collector. * eta_c: The efficiency of the collector. * collector_heat: The heat power output of the collector. """ # Creation of a df with 3 columns data = pd.DataFrame( { 'ghi': irradiance_global, 'dhi': irradiance_diffuse, 'temp_amb': temp_amb } ) # date_time_index = pd.date_range( # df.loc[0, date_col], periods=periods, freq='H', tz=tz # ) # datainput = df.iloc[:periods] # data.set_index('date', inplace=True) # Calculation of geometrical position of collector with the pvlib solposition = pvlib.solarposition.get_solarposition( time=data.index, latitude=lat, longitude=long ) dni = pvlib.irradiance.dni( ghi=data['ghi'], dhi=data['dhi'], zenith=solposition['apparent_zenith'] ) total_irradiation = pvlib.irradiance.get_total_irradiance( surface_tilt=collector_tilt, surface_azimuth=collector_azimuth, solar_zenith=solposition['apparent_zenith'], solar_azimuth=solposition['azimuth'], dni=dni.fillna(0), # fill NaN values with '0' ghi=data['ghi'], dhi=data['dhi'], ) data['col_ira'] = total_irradiation['poa_global'] eta_c = calc_eta_c_flate_plate( eta_0, a_1, a_2, temp_collector_inlet, delta_temp_n, data['temp_amb'], total_irradiation['poa_global'], ) data['eta_c'] = eta_c collectors_heat = eta_c * total_irradiation['poa_global'] data["collectors_heat"] = collectors_heat return data
[docs]def calc_eta_c_flate_plate( eta_0, a_1, a_2, temp_collector_inlet, delta_temp_n, temp_amb, collector_irradiance, ): r""" Calculates collectors efficiency .. calc_eta_c_flate_plate_equation: :math:`\eta_C = \eta_0 - a_1 \cdot \frac{\Delta T}{E_{coll}} - a_2 \cdot \frac{{\Delta T}^2}{E_{coll}}` with :math:`\Delta T = T_{coll,in} + {\Delta T}_n - T_{amb}` Parameters ---------- eta_0: numeric Optical efficiency of the collector. a_1: numeric Thermal loss parameter 1. a_2: numeric Thermal loss parameter 2. temp_collector_inlet: numeric, in °C Collectors inlet temperature. delta_temp_n: numeric Temperature difference between collector inlet and mean temperature. temp_amb: series of numeric, in °C Ambient temperature. collector_irradiance: series of numeric Irradiance on collector after all losses. Returns ------- eta_c: series of numeric collectors efficiency """ delta_t = temp_collector_inlet + delta_temp_n - temp_amb eta_c = pd.Series() for index, value in collector_irradiance.items(): if value > 0: eta = ( eta_0 - a_1 * delta_t[index] / value - a_2 * delta_t[index] ** 2 / value ) if eta > 0: eta_c[index] = eta else: eta_c[index] = 0 else: eta_c[index] = 0 return eta_c