diff --git a/Wind/temperature.txt b/Wind/temperature.txt
new file mode 100644
index 0000000..62e82ed
--- /dev/null
+++ b/Wind/temperature.txt
@@ -0,0 +1,12 @@
+10
+12
+15
+18
+20
+22
+25
+24
+20
+15
+12
+10
\ No newline at end of file
diff --git a/Wind/wind_product.xlsx b/Wind/wind_product.xlsx
new file mode 100644
index 0000000..5d5b94b
Binary files /dev/null and b/Wind/wind_product.xlsx differ
diff --git a/Wind/wind_speed.txt b/Wind/wind_speed.txt
new file mode 100644
index 0000000..3370b0f
--- /dev/null
+++ b/Wind/wind_speed.txt
@@ -0,0 +1,12 @@
+3.5
+4.0
+4.2
+3.8
+5.0
+5.5
+6.0
+5.8
+5.2
+4.5
+4.0
+3.7
\ No newline at end of file
diff --git a/Wind/wind_total.py b/Wind/wind_total.py
new file mode 100644
index 0000000..4e3c087
--- /dev/null
+++ b/Wind/wind_total.py
@@ -0,0 +1,192 @@
+import pandas as pd
+import math
+from scipy.optimize import fsolve
+
+def wind_farm_analysis(device_name, area_km2, electricity_price, file_path, velocity_path, T_path,
+                       lateral_spacing_factor=5, longitudinal_spacing_factor=10, q=0.02, altitude=11,
+                       hub_height=100, Cp=0.45, eta=0.8, cost_per_mw=5000):
+    """
+    封装函数：分析风电场的风机数量及各项经济和技术指标
+
+    参数：
+        device_name (str): 设备名称
+        area_km2 (float): 风电场面积（平方公里）
+        electricity_price (float): 电价（元/kWh）
+        file_path (str): 风机参数 Excel 文件路径
+        velocity_path (str): 风速数据文件路径（12 个月平均风速）
+        T_path (str): 温度数据文件路径（12 个月平均温度）
+        lateral_spacing_factor (float): 横向间距因子（默认为 5D）
+        longitudinal_spacing_factor (float): 纵向间距因子（默认为 10D）
+        q (float): 运维成本占初始投资成本的比例（默认 0.02 表示 2%）
+        altitude (float): 海拔高度（m），默认 11m
+        hub_height (float): 轮毂高度（m），默认 100m
+        Cp (float): 风能利用系数，默认 0.45
+        eta (float): 总系统效率，默认 0.8
+        cost_per_mw (float): 每 MW 投资成本（万元/MW），默认 5000 万元/MW
+
+    返回：
+        dict: 包含风电场分析结果的字典
+    """
+    def estimate_wind_turbine_count(area_km2, blade_diameter):
+        area_m2 = area_km2 * 1_000_000
+        lateral_spacing = lateral_spacing_factor * blade_diameter
+        longitudinal_spacing = longitudinal_spacing_factor * blade_diameter
+        turbine_area = lateral_spacing * longitudinal_spacing
+        turbine_count = int(area_m2 / turbine_area)
+        print(f"单台风机占地面积: {turbine_area:,} 平方米 "
+              f"(横向间距: {lateral_spacing} 米, 纵向间距: {longitudinal_spacing} 米)")
+        print(f"估算风机数量: {turbine_count} 台")
+        return turbine_count
+
+    def get_wind_turbine_specs(device_name, file_path):
+        try:
+            df = pd.read_excel(file_path)
+            match = df[df.iloc[:, 0] == device_name]
+            if not match.empty:
+                rated_power = match.iloc[0, 1] / 1000  # kW 转换为 MW
+                swept_area = match.iloc[0, 7]  # 扫风面积
+                blade_diameter = match.iloc[0, 6]  # 叶片直径
+                print(f"找到设备 '{device_name}'，额定功率: {rated_power} MW, "
+                      f"扫风面积: {swept_area} m², 叶片直径: {blade_diameter} 米")
+                return rated_power, swept_area, blade_diameter
+            else:
+                raise ValueError(f"未找到设备名称: {device_name}")
+        except FileNotFoundError:
+            raise FileNotFoundError(f"文件未找到: {file_path}")
+        except Exception as e:
+            raise Exception(f"发生错误: {str(e)}")
+
+    def read_monthly_temperatures(file_path):
+        try:
+            with open(file_path, 'r', encoding='utf-8') as file:
+                temperatures = [float(line.strip()) for line in file.readlines()]
+            if len(temperatures) != 12:
+                raise ValueError(f"温度文件应包含 12 个月的数据，但实际有 {len(temperatures)} 条")
+            return temperatures
+        except Exception as e:
+            raise Exception(f"读取温度文件时出错: {str(e)}")
+
+    def air_density(altitude, hub_height, T0):
+        z = altitude + hub_height
+        LR = 0.0065
+        T = T0 - LR * z + 273.15
+        return (353.05 / T) * math.exp(-0.034 * (z / T))
+
+    def wind_power_density(densities, file_path):
+        try:
+            with open(file_path, 'r', encoding='utf-8') as file:
+                wind_speeds = [float(line.strip()) for line in file.readlines()]
+            if len(wind_speeds) != 12:
+                raise ValueError(f"风速文件应包含 12 个月的数据，但实际有 {len(wind_speeds)} 条")
+            sum_rho_v3 = sum(rho * (v ** 3) for rho, v in zip(densities, wind_speeds))
+            return (1 / (2 * 12)) * sum_rho_v3
+        except Exception as e:
+            raise Exception(f"读取风速文件时出错: {str(e)}")
+
+    def estimated_wind_power(num_turbines, rated_power):
+        if not isinstance(num_turbines, int) or num_turbines < 0:
+            raise ValueError("风机数量必须为非负整数")
+        return rated_power * num_turbines
+
+    def calculate_power_output(S, w, Cp, eta):
+        return w * S * Cp * 8760 * eta
+
+    def calculate_equivalent_hours(P, P_r):
+        if P_r == 0:
+            raise ValueError("额定功率不能为 0")
+        return (P / 1000) / (P_r * 1000)
+
+    def calculate_reference_yield(E_p, electricity_price, IC, q, n=20):
+        def npv_equation(irr, p, w, ic, q_val, n=n):
+            term1 = (1 + irr) ** (-1)
+            term2 = irr * (1 + irr) ** (-1) if irr != 0 else float('inf')
+            pv_revenue = p * w * (term1 / term2) * (1 - (1 + irr) ** (-n))
+            pv_salvage = q_val * ic * (term1 / term2) * (1 - (1 + irr) ** (-n))
+            return pv_revenue - ic + pv_salvage
+
+        irr_guess = 0.1
+        irr = float(fsolve(npv_equation, irr_guess, args=(E_p, electricity_price, IC, q))[0])
+        if not 0 <= irr <= 1:
+            raise ValueError(f"IRR计算结果{irr:.4f}不合理")
+        return irr * 100
+
+    try:
+        # 获取设备信息
+        rated_power, swept_area, blade_diameter = get_wind_turbine_specs(device_name, file_path)
+
+        # 估算风机数量
+        num_turbines = estimate_wind_turbine_count(area_km2, blade_diameter)
+
+        # 读取温度数据并计算空气密度
+        monthly_temps = read_monthly_temperatures(T_path)
+        densities = [air_density(altitude, hub_height, T0) for T0 in monthly_temps]
+        avg_density = sum(densities) / len(densities)
+
+        # 计算风功率密度
+        wpd = wind_power_density(densities, velocity_path)
+
+        # 计算装机容量
+        total_power = estimated_wind_power(num_turbines, rated_power)
+
+        # 计算初始投资成本
+        IC = total_power * cost_per_mw * 1000000
+
+        # 计算年发电量
+        P_test = calculate_power_output(swept_area, wpd, Cp, eta) * num_turbines
+
+        # 计算等效小时数
+        h = calculate_equivalent_hours(P_test, rated_power)
+
+        # 计算 IRR
+        irr = calculate_reference_yield(P_test, electricity_price, IC, q)
+
+        # 返回结果
+        return {
+            "device": device_name,
+            "rated_power": rated_power,
+            "swept_area": swept_area,
+            "blade_diameter": blade_diameter,
+            "num_turbines": num_turbines,
+            "avg_density": avg_density,
+            "wpd": wpd,
+            "total_power": total_power,
+            "annual_power_output": P_test / 10000000,  # 万 kWh
+            "equivalent_hours": h,
+            "IRR": irr
+        }
+    except Exception as e:
+        raise Exception(f"风电场分析出错: {str(e)}")
+
+# 主程序
+if __name__ == "__main__":
+    file_path = r".\wind_product.xlsx"
+    velocity_path = r".\wind_speed.txt"
+    T_path = r".\temperature.txt"
+
+    device_name = input("请输入设备名称: ")
+    area_km2 = float(input("请输入风电场面积（平方公里）: "))
+    electricity_price = float(input("请输入电价（元/kWh）: "))
+
+    try:
+        result = wind_farm_analysis(
+            device_name=device_name,
+            area_km2=area_km2,
+            electricity_price=electricity_price,
+            file_path=file_path,
+            velocity_path=velocity_path,
+            T_path=T_path
+        )
+
+        print(f"\n设备: {result['device']}")
+        print(f"额定功率: {result['rated_power']:.2f} MW")
+        print(f"扫风面积: {result['swept_area']:.2f} m^2")
+        print(f"叶片直径: {result['blade_diameter']:.2f} m")
+        print(f"风机数量: {result['num_turbines']} 台")
+        print(f"平均空气密度: {result['avg_density']:.3f} kg/m^3")
+        print(f"风功率密度: {result['wpd']:.2f} W/m^2")
+        print(f"项目装机容量: {result['total_power']:.2f} MW")
+        print(f"年发电量: {result['annual_power_output']:.3f} 万 kWh")
+        print(f"等效小时数: {result['equivalent_hours']:.2f} 小时")
+        print(f"内部收益率 IRR: {result['IRR']:.2f}%")
+    except Exception as e:
+        print(f"错误: {str(e)}")
\ No newline at end of file