1.可以读excel文件

2.可以计算8760小时

advanced_visualization.py

@@ -153,7 +153,7 @@ def create_comprehensive_plot(solar_output, wind_output, thermal_output, load_de
     """
     
     ax7.text(0.1, 0.5, metrics_text, fontsize=11, verticalalignment='center',
-             fontfamily='monospace', bbox=dict(boxstyle='round', facecolor='lightgray', alpha=0.8))
+             fontfamily='SimHei', bbox=dict(boxstyle='round', facecolor='lightgray', alpha=0.8))
     
     # 保存图片
     plt.savefig('comprehensive_analysis.png', dpi=300, bbox_inches='tight')

excel_reader.py

@@ -0,0 +1,266 @@
+"""
+Excel数据读取模块
+
+该模块提供从Excel文件中读取8760小时负荷和发电曲线数据的功能。
+
+作者: iFlow CLI
+创建日期: 2025-12-25
+"""
+
+import pandas as pd
+import numpy as np
+from typing import Dict, List, Optional, Tuple
+import os
+
+
+def validate_excel_data(df: pd.DataFrame, data_type: str = "8760") -> bool:
+    """
+    验证Excel数据格式是否正确
+    
+    Args:
+        df: pandas DataFrame对象
+        data_type: 数据类型，"24"或"8760"
+        
+    Returns:
+        bool: 验证是否通过
+    """
+    expected_length = 8760 if data_type == "8760" else 24
+    
+    # 检查行数
+    if len(df) != expected_length:
+        print(f"错误：数据行数应为{expected_length}，实际为{len(df)}")
+        return False
+    
+    # 检查必需的列
+    required_columns = ['光伏出力(MW)', '风电出力(MW)', '火电出力(MW)', '负荷需求(MW)']
+    missing_columns = [col for col in required_columns if col not in df.columns]
+    
+    if missing_columns:
+        print(f"错误：缺少必需的列：{missing_columns}")
+        return False
+    
+    # 检查数据类型和非负值
+    for col in required_columns:
+        if not pd.api.types.is_numeric_dtype(df[col]):
+            print(f"错误：列'{col}'必须为数值类型")
+            return False
+        
+        if (df[col] < 0).any():
+            print(f"错误：列'{col}'包含负值")
+            return False
+    
+    return True
+
+
+def read_excel_data(file_path: str, sheet_name: str = 0) -> Dict[str, List[float]]:
+    """
+    从Excel文件读取8760小时数据
+    
+    Args:
+        file_path: Excel文件路径
+        sheet_name: 工作表名称或索引，默认为第一个工作表
+        
+    Returns:
+        包含所有数据的字典
+        
+    Raises:
+        FileNotFoundError: 文件不存在
+        ValueError: 数据格式错误
+    """
+    # 检查文件是否存在
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"文件不存在：{file_path}")
+    
+    try:
+        # 读取Excel文件
+        df = pd.read_excel(file_path, sheet_name=sheet_name)
+        
+        # 自动检测数据类型
+        data_type = "8760" if len(df) >= 8760 else "24"
+        
+        # 验证数据格式
+        if not validate_excel_data(df, data_type):
+            raise ValueError("Excel数据格式验证失败")
+        
+        # 提取数据并转换为列表
+        solar_output = df['光伏出力(MW)'].tolist()
+        wind_output = df['风电出力(MW)'].tolist()
+        thermal_output = df['火电出力(MW)'].tolist()
+        load_demand = df['负荷需求(MW)'].tolist()
+        
+        # 如果是24小时数据，扩展到8760小时（重复365天）
+        if data_type == "24" and len(df) == 24:
+            print("检测到24小时数据，自动扩展到8760小时（重复365天）")
+            solar_output = solar_output * 365
+            wind_output = wind_output * 365
+            thermal_output = thermal_output * 365
+            load_demand = load_demand * 365
+        
+        return {
+            'solar_output': solar_output,
+            'wind_output': wind_output,
+            'thermal_output': thermal_output,
+            'load_demand': load_demand,
+            'data_type': data_type,
+            'original_length': len(df)
+        }
+        
+    except Exception as e:
+        raise ValueError(f"读取Excel文件失败：{str(e)}")
+
+
+def create_excel_template(file_path: str, data_type: str = "8760"):
+    """
+    创建Excel数据模板文件
+    
+    Args:
+        file_path: 保存路径
+        data_type: 数据类型，"24"或"8760"
+    """
+    # 生成示例数据
+    if data_type == "24":
+        hours = 24
+        # 24小时典型日数据
+        solar = [0.0] * 6 + [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.0] + [0.0] * 6
+        wind = [2.0, 3.0, 4.0, 3.0, 2.0, 1.0] * 4
+        thermal = [5.0] * 24
+        load = [3.0, 4.0, 5.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 18.0, 
+                16.0, 14.0, 12.0, 10.0, 8.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 2.0]
+        description = "24小时典型日数据模板"
+    else:
+        hours = 8760
+        # 生成8760小时的模拟数据（基于日模式加季节变化）
+        daily_solar = [0.0] * 6 + [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.0] + [0.0] * 6
+        daily_wind = [2.0, 3.0, 4.0, 3.0, 2.0, 1.0] * 4
+        daily_thermal = [5.0] * 24
+        daily_load = [3.0, 4.0, 5.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 18.0, 
+                     16.0, 14.0, 12.0, 10.0, 8.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 2.0]
+        
+        solar = []
+        wind = []
+        thermal = []
+        load = []
+        
+        np.random.seed(42)  # 确保可重复性
+        
+        for day in range(365):
+            # 季节性因子
+            season_factor = 1.0 + 0.3 * np.sin(2 * np.pi * day / 365)
+            
+            for hour in range(24):
+                # 添加随机变化
+                solar_variation = 1.0 + 0.2 * (np.random.random() - 0.5)
+                wind_variation = 1.0 + 0.3 * (np.random.random() - 0.5)
+                load_variation = 1.0 + 0.1 * (np.random.random() - 0.5)
+                
+                solar.append(daily_solar[hour] * season_factor * solar_variation)
+                wind.append(daily_wind[hour] * wind_variation)
+                thermal.append(daily_thermal[hour])
+                load.append(daily_load[hour] * (2.0 - season_factor) * load_variation)
+        
+        description = "8760小时全年数据模板"
+    
+    # 创建DataFrame
+    df = pd.DataFrame({
+        '小时': range(1, hours + 1),
+        '光伏出力(MW)': solar,
+        '风电出力(MW)': wind,
+        '火电出力(MW)': thermal,
+        '负荷需求(MW)': load
+    })
+    
+    # 保存到Excel
+    with pd.ExcelWriter(file_path, engine='openpyxl') as writer:
+        df.to_excel(writer, sheet_name='数据', index=False)
+        
+        # 添加说明工作表
+        description_df = pd.DataFrame({
+            '项目': ['数据说明', '数据类型', '时间范围', '单位', '注意事项'],
+            '内容': [
+                description,
+                f'{data_type}小时电力数据',
+                f'1-{hours}小时',
+                'MW (兆瓦)',
+                '所有数值必须为非负数'
+            ]
+        })
+        description_df.to_excel(writer, sheet_name='说明', index=False)
+    
+    print(f"Excel模板已创建：{file_path}")
+
+
+def analyze_excel_data(file_path: str) -> Dict[str, float]:
+    """
+    分析Excel数据的基本统计信息
+    
+    Args:
+        file_path: Excel文件路径
+        
+    Returns:
+        包含统计信息的字典
+    """
+    try:
+        data = read_excel_data(file_path)
+        
+        solar = data['solar_output']
+        wind = data['wind_output']
+        thermal = data['thermal_output']
+        load = data['load_demand']
+        
+        return {
+            'data_length': len(solar),
+            'total_solar': sum(solar),
+            'total_wind': sum(wind),
+            'total_thermal': sum(thermal),
+            'total_generation': sum(solar) + sum(wind) + sum(thermal),
+            'total_load': sum(load),
+            'max_solar': max(solar),
+            'max_wind': max(wind),
+            'max_thermal': max(thermal),
+            'max_load': max(load),
+            'avg_solar': np.mean(solar),
+            'avg_wind': np.mean(wind),
+            'avg_thermal': np.mean(thermal),
+            'avg_load': np.mean(load)
+        }
+    except Exception as e:
+        print(f"分析数据失败：{str(e)}")
+        return {}
+
+
+def main():
+    """主函数，演示Excel数据读取功能"""
+    print("=== Excel数据读取模块演示 ===")
+    
+    # 创建模板文件
+    template_8760 = "data_template_8760.xlsx"
+    template_24 = "data_template_24.xlsx"
+    
+    print("\n1. 创建Excel模板文件...")
+    create_excel_template(template_8760, "8760")
+    create_excel_template(template_24, "24")
+    
+    # 分析模板数据
+    print(f"\n2. 分析{template_8760}数据...")
+    stats = analyze_excel_data(template_8760)
+    if stats:
+        print("数据统计信息：")
+        for key, value in stats.items():
+            print(f"  {key}: {value:.2f}")
+    
+    print(f"\n3. 演示读取{template_24}数据...")
+    try:
+        data = read_excel_data(template_24)
+        print(f"成功读取数据，类型：{data['data_type']}")
+        print(f"光伏出力前10小时：{data['solar_output'][:10]}")
+        print(f"风电出力前10小时：{data['wind_output'][:10]}")
+        print(f"负荷需求前10小时：{data['load_demand'][:10]}")
+    except Exception as e:
+        print(f"读取失败：{str(e)}")
+    
+    print("\n=== 演示完成 ===")
+    print("模板文件已创建，您可以根据实际数据修改Excel文件。")
+
+
+if __name__ == "__main__":
+    main()

main.py

@@ -10,6 +10,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from storage_optimization import optimize_storage_capacity, SystemParameters
+from excel_reader import read_excel_data, create_excel_template, analyze_excel_data
 
 # 设置中文字体
 plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']
@@ -27,6 +28,12 @@ def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, r
         load_demand: 负荷曲线 (MW) - 支持24小时或8760小时
         result: 优化结果字典
     """
+    import matplotlib.pyplot as plt
+    import numpy as np
+    
+    # 设置中文字体
+    plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']
+    plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题
     hours = np.arange(len(solar_output))
     data_length = len(solar_output)
     
@@ -160,12 +167,56 @@ def main():
     import sys
     
     # 检查命令行参数
-    use_yearly_data = len(sys.argv) > 1 and sys.argv[1] == '--yearly'
+    if len(sys.argv) < 2:
+        print_usage()
+        return
     
-    if use_yearly_data:
+    command = sys.argv[1]
+    
+    if command == '--yearly':
         print("生成8760小时全年数据...")
         solar_output, wind_output, thermal_output, load_demand = generate_yearly_data()
         print(f"数据长度: {len(solar_output)} 小时")
+    elif command == '--excel':
+        if len(sys.argv) < 3:
+            print("错误：请指定Excel文件路径")
+            print("用法：python main.py --excel <文件路径>")
+            return
+        
+        excel_file = sys.argv[2]
+        print(f"从Excel文件读取数据：{excel_file}")
+        
+        try:
+            data = read_excel_data(excel_file)
+            solar_output = data['solar_output']
+            wind_output = data['wind_output']
+            thermal_output = data['thermal_output']
+            load_demand = data['load_demand']
+            
+            print(f"成功读取{data['data_type']}小时数据")
+            print(f"原始数据长度：{data['original_length']}小时")
+            print(f"处理后数据长度：{len(solar_output)}小时")
+            
+            # 显示数据统计
+            stats = analyze_excel_data(excel_file)
+            if stats:
+                print("\n数据统计：")
+                print(f"  总发电量: {stats['total_generation']:.2f} MW")
+                print(f"  总负荷: {stats['total_load']:.2f} MW")
+                print(f"  最大光伏出力: {stats['max_solar']:.2f} MW")
+                print(f"  最大风电出力: {stats['max_wind']:.2f} MW")
+                print(f"  最大负荷: {stats['max_load']:.2f} MW")
+                
+        except Exception as e:
+            print(f"读取Excel文件失败：{str(e)}")
+            return
+    elif command == '--create-template':
+        template_type = sys.argv[2] if len(sys.argv) > 2 else "8760"
+        template_file = f"data_template_{template_type}.xlsx"
+        
+        print(f"创建{template_type}小时Excel模板：{template_file}")
+        create_excel_template(template_file, template_type)
+        return
     else:
         print("使用24小时示例数据...")
         # 示例数据
@@ -175,6 +226,7 @@ def main():
         load_demand = [3.0, 4.0, 5.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 18.0, 
                        16.0, 14.0, 12.0, 10.0, 8.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 2.0]
 
+
 # 系统参数
     params = SystemParameters(
         max_curtailment_wind=0.1,
@@ -198,5 +250,19 @@ def main():
     print("\n曲线图已保存为 'system_curves.png'")
 
 
+def print_usage():
+    """打印使用说明"""
+    print("多能互补系统储能容量优化程序")
+    print("\n使用方法：")
+    print("  python main.py --excel <文件路径>     # 从Excel文件读取数据")
+    print("  python main.py --yearly              # 使用8760小时全年数据")
+    print("  python main.py --create-template [类型] # 创建Excel模板(24或8760)")
+    print("  python main.py                       # 使用24小时示例数据")
+    print("\n示例：")
+    print("  python main.py --excel data.xlsx")
+    print("  python main.py --create-template 8760")
+    print("  python main.py --create-template 24")
+
+
 if __name__ == "__main__":
     main()