PySAM风力涡轮机模拟报错：嵌套元组转矩阵行失败求助

问题描述 #

运行PySAM风力涡轮机模拟代码时触发报错：

Exception: Error (-4) converting nested tuple 0 into row in matrix

报错位置在wind_turbine.Resource.wind_resource_data赋值语句处。

问题原因 #

PySAM对wind_resource_data的结构有严格要求：每个字段（如wind_speed、perc）的格式需要是外层列表对应高度维度，内层列表包含该高度下的所有数据点。当前代码中生成的[[float(key)] for key in data_dict]会把每个数据点单独放在一个子列表里，形成[[v1], [v2], ...]的结构，不符合PySAM预期的[[v1, v2, ...]]格式，导致矩阵转换失败。

解决方法 #

修改wind_resource_data中各字段的生成方式，将同一高度的所有数据合并到一个内层列表中，外层保留一个列表对应高度[0]：

import PySAM.Windpower as wp
import csv

# Create a Windpower object
wind_turbine = wp.default("WindPowerSingleOwner")

# Set the turbine parameters
wind_turbine.system_capacity = 200  # Turbine capacity in kW
wind_turbine.max_cp = 0.45  # Maximum power coefficient
wind_turbine.max_tip_speed = 80  # Maximum tip speed in m/s
wind_turbine.cut_in_speed = 3  # Cut-in wind speed in m/s
wind_turbine.cut_out_speed = 25  # Cut-out wind speed in m/s

def csv_to_dict(file_path):
    result_dict = {}
    with open(file_path, 'r') as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            val = float(row['val'])
            perc = float(row['perc'])
            sel_perc = float(row['sel_perc'])
            result_dict[val] = (perc, sel_perc)
    return result_dict

# Provide the file path to your CSV file
csv_file_path = 'C:/Users/arthu/OneDrive/Documents/INTERNSHIP/SAM/05-07-2023/windSpeed.csv'

# Convert the CSV file to a dictionary
data_dict = csv_to_dict(csv_file_path)
print(data_dict)

# Set the wind resource data - 修改后的结构
wind_turbine.Resource.wind_resource_data = {
    'fields': ['wind_speed', 'perc', 'sel_perc'],
    'heights': [0],
    # 将所有数据合并到一个内层列表中，外层用列表包裹对应高度
    'wind_speed': [[float(key) for key in data_dict]],
    'perc': [[data_dict[key][0] for key in data_dict]],
    'sel_perc': [[data_dict[key][1] for key in data_dict]]
}

# Run the simulation
wind_turbine.execute()

# Access the wind turbine outputs
annual_energy = wind_turbine.Outputs.annual_energy

# Print the annual energy production
print("Annual Energy Production:", annual_energy, "kWh")

额外说明 #

• 确保CSV中的数据是按合理顺序排列的（比如风速从小到大），避免模拟结果出现异常
• 如果有多个高度的风资源数据，只需在heights中添加对应高度值，并为每个字段添加对应高度的数据列表，例如'wind_speed': [[height0_data], [height1_data]]

内容的提问来源于stack exchange，提问作者Arthur Martineau