pv_forecasting/tools.py

# -*-utf8-*-
import numpy as np
import json
import math
from logzero import logger

def load_config(path):
    with open(path, 'r', encoding='utf-8') as fr:
        config = json.load(fr)
    return config

def cal_angle(prov:str, city:str, angle_config:dict):
    """_summary_

    Args:
        prov (str): _ 省、直辖市、自治区、特别行政区
        city (str): _ 地级市、地区、自治州、盟
        angle_config (dict): _

    Returns:
        _type_: _description_
    """
    prov_values = angle_config.get(prov)
    if not prov_values:
        return False
    city_values = prov_values.get(city)
    if not prov_values:
        values = np.mean(list(prov_values.values), axis=0)
    else:
        values = city_values
    return values

def cal_generation(cap:float, angle, best_angle, dhi_list):
    """_summary_
    G = Y * cos(|x - y|)* 0.9 * GHI
    """
    dhi_list = np.asarray(dhi_list)
    logger.info(dhi_list)
    index = math.cos(math.radians(abs(angle - best_angle)))
    return list(cap * index * 0.9 * dhi_list / 1000)


def cal_complex_gen(cap:float, angle:float, best_angle:float, 
                    dhi_list:list, t_list:list, materials:str, sigma:float=None, 
                    t_noct:[float, int]=45)->list:
    """复杂的计算出力的方式

    Args:
        cap (float): _装机容量(KW).
        angle (float): _光伏安装倾角(°).
        best_angle (float): _当地最佳安装倾角  
        dhi_list (list): _未来120h辐照预测值，W/m2  
        t_list (list): _未来120h气温预测值,℃  
        materials (str): _晶体材料  
        sigma (float, optional): _温度系数（%/℃）取值一般为[-0.45 ~ -0.33]，当该值不为None时，不通过晶体材料计算sigma. Defaults to None.
        t_noct (int, optional): _电池片结温. Defaults to 45.

    Returns:
        power_list(list[float]): 未来120h的小时出力，KW
    """
    t_a_noct = 20
    g_noct = 800
    ita = 0.083 / 0.9
    sigma_dict = {
        "N型单晶": -0.38,
        "P型单晶": -0.42,
        "P型多晶": -0.42
    }
    t_list = np.asarray(t_list)
    dhi_list = np.asarray(dhi_list)
    t_cell = t_list + (float(t_noct) - t_a_noct)*(dhi_list / g_noct)*(1-ita)
    if sigma is None:
        sigma = sigma_dict.get(materials, -0.42)
    else:
        sigma = float(sigma)
    K = 1 + sigma / 100 * (t_cell - t_a_noct)
    return list(cap * math.cos(math.radians(abs(angle - best_angle))) * dhi_list) * K


if __name__ == '__main__':
    print(cal_generation(200., 32, 33, [15., 21., 33., 94.]))