增加正负显示购电量。

main.py

@@ -11,6 +11,8 @@ import matplotlib
 matplotlib.use('TkAgg')  # 设置为TkAgg后端以支持图形窗口显示
 import matplotlib.pyplot as plt
 import numpy as np
+import pandas as pd
+from datetime import datetime
 from storage_optimization import optimize_storage_capacity, SystemParameters
 from excel_reader import read_excel_data, create_excel_template, analyze_excel_data
 
@@ -54,6 +56,7 @@ def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, r
         sampled_storage = result['storage_profile'][::sample_rate]
         sampled_charge = result['charge_profile'][::sample_rate]
         sampled_discharge = result['discharge_profile'][::sample_rate]
+        sampled_grid_feed_in = result['grid_feed_in'][::sample_rate]
     else:
         title_suffix = " (24小时)"
         sampled_hours = hours
@@ -64,9 +67,10 @@ def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, r
         sampled_storage = result['storage_profile']
         sampled_charge = result['charge_profile']
         sampled_discharge = result['discharge_profile']
+        sampled_grid_feed_in = result['grid_feed_in']
     
-    # 创建图形
-    fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(14, 12))
+    # 创建图形（4个子图）
+    fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(14, 16))
     fig.suptitle('多能互补系统24小时运行曲线', fontsize=16, fontweight='bold')
     
     # === 第一个子图：发电和负荷曲线 ===
@@ -111,6 +115,31 @@ def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, r
     ax3.set_xlim(0, max(sampled_hours))
     ax3.set_ylim(bottom=0)
     
+    # === 第四个子图：购电量和上网电量曲线 ===
+    # 直接使用原始数据：正值表示上网电量，负值表示购电量
+    grid_power = sampled_grid_feed_in
+    
+    # 绘制电网交互电量（正值上网，负值购电）
+    colors = ['brown' if x >= 0 else 'purple' for x in grid_power]
+    ax4.bar(sampled_hours, grid_power, color=colors, alpha=0.7, label='电网交互电量')
+    
+    # 添加零线
+    ax4.axhline(y=0, color='black', linestyle='-', linewidth=0.5)
+    
+    # 添加图例说明
+    from matplotlib.patches import Patch
+    legend_elements = [
+        Patch(facecolor='brown', alpha=0.7, label='上网电量 (+)'),
+        Patch(facecolor='purple', alpha=0.7, label='购电量 (-)')
+    ]
+    ax4.legend(handles=legend_elements, loc='upper right')
+    
+    ax4.set_xlabel('时间 (小时)')
+    ax4.set_ylabel('功率 (MW)')
+    ax4.set_title(f'电网交互电量{title_suffix} (正值:上网, 负值:购电)')
+    ax4.grid(True, alpha=0.3)
+    ax4.set_xlim(0, max(sampled_hours))
+    
     # 调整布局
     plt.tight_layout()
     
@@ -146,6 +175,173 @@ def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, r
     print(f"弃光率: {result['total_curtailment_solar_ratio']:.3f}")
     print(f"上网电量比例: {result['total_grid_feed_in_ratio']:.3f}")
     
+    # 计算购电和上网电量统计
+    total_grid_feed_in = sum(result['grid_feed_in'])
+    total_grid_purchase = sum(-x for x in result['grid_feed_in'] if x < 0)  # 购电量
+    total_grid_feed_out = sum(x for x in result['grid_feed_in'] if x > 0)   # 上网电量
+    
+    print(f"\n=== 电网交互统计 ===")
+    if total_grid_feed_in >= 0:
+        print(f"净上网电量: {total_grid_feed_in:.2f} MWh")
+    else:
+        print(f"净购电量: {-total_grid_feed_in:.2f} MWh")
+    print(f"总购电量: {total_grid_purchase:.2f} MWh")
+    print(f"总上网电量: {total_grid_feed_out:.2f} MWh")
+
+
+def export_results_to_excel(solar_output, wind_output, thermal_output, load_demand, result, params, filename=None):
+    """
+    将优化结果导出到Excel文件
+    
+    Args:
+        solar_output: 光伏出力曲线 (MW)
+        wind_output: 风电出力曲线 (MW)
+        thermal_output: 火电出力曲线 (MW)
+        load_demand: 负荷曲线 (MW)
+        result: 优化结果字典
+        params: 系统参数
+        filename: 输出文件名，如果为None则自动生成
+    """
+    if filename is None:
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filename = f"storage_optimization_results_{timestamp}.xlsx"
+    
+    print(f"\n正在导出结果到Excel文件: {filename}")
+    
+    # 准备数据
+    hours = list(range(1, len(solar_output) + 1))
+    
+    # 分离购电和上网电量
+    grid_purchase = []
+    grid_feed_out = []
+    
+    for power in result['grid_feed_in']:
+        if power < 0:
+            grid_purchase.append(-power)  # 购电，转换为正值
+            grid_feed_out.append(0)
+        else:
+            grid_purchase.append(0)
+            grid_feed_out.append(power)  # 上网电量
+    
+    # 创建主要数据DataFrame
+    data_df = pd.DataFrame({
+        '小时': hours,
+        '光伏出力(MW)': solar_output,
+        '风电出力(MW)': wind_output,
+        '火电出力(MW)': thermal_output,
+        '总发电量(MW)': [solar_output[i] + wind_output[i] + thermal_output[i] for i in range(len(solar_output))],
+        '负荷需求(MW)': load_demand,
+        '储能充电(MW)': result['charge_profile'],
+        '储能放电(MW)': result['discharge_profile'],
+        '储能状态(MWh)': result['storage_profile'],
+        '弃风量(MW)': result['curtailed_wind'],
+        '弃光量(MW)': result['curtailed_solar'],
+        '购电量(MW)': grid_purchase,
+        '上网电量(MW)': grid_feed_out
+    })
+    
+    # 创建统计信息DataFrame
+    total_grid_feed_in = sum(result['grid_feed_in'])
+    total_grid_purchase = sum(-x for x in result['grid_feed_in'] if x < 0)  # 购电量
+    total_grid_feed_out = sum(x for x in result['grid_feed_in'] if x > 0)   # 上网电量
+    
+    stats_df = pd.DataFrame({
+        '指标': [
+            '所需储能总容量',
+            '最大储能状态',
+            '最小储能状态',
+            '总充电量',
+            '总放电量',
+            '弃风率',
+            '弃光率',
+            '上网电量比例',
+            '能量平衡校验',
+            '净购电量/净上网电量',
+            '总购电量',
+            '总上网电量',
+            '容量限制是否达到'
+        ],
+        '数值': [
+            f"{result['required_storage_capacity']:.2f} MWh",
+            f"{max(result['storage_profile']):.2f} MWh",
+            f"{min(result['storage_profile']):.2f} MWh",
+            f"{sum(result['charge_profile']):.2f} MWh",
+            f"{sum(result['discharge_profile']):.2f} MWh",
+            f"{result['total_curtailment_wind_ratio']:.3f}",
+            f"{result['total_curtailment_solar_ratio']:.3f}",
+            f"{result['total_grid_feed_in_ratio']:.3f}",
+            "通过" if result['energy_balance_check'] else "未通过",
+            f"{-total_grid_feed_in:.2f} MWh" if total_grid_feed_in < 0 else f"{total_grid_feed_in:.2f} MWh",
+            f"{total_grid_purchase:.2f} MWh",
+            f"{total_grid_feed_out:.2f} MWh",
+            "是" if result['capacity_limit_reached'] else "否"
+        ]
+    })
+    
+    # 创建系统参数DataFrame
+    params_df = pd.DataFrame({
+        '参数名称': [
+            '最大弃风率',
+            '最大弃光率',
+            '最大上网电量比例',
+            '储能效率',
+            '放电倍率',
+            '充电倍率',
+            '最大储能容量'
+        ],
+        '参数值': [
+            params.max_curtailment_wind,
+            params.max_curtailment_solar,
+            params.max_grid_ratio,
+            params.storage_efficiency,
+            params.discharge_rate,
+            params.charge_rate,
+            params.max_storage_capacity if params.max_storage_capacity is not None else "无限制"
+        ],
+        '单位': [
+            "比例",
+            "比例",
+            "比例",
+            "效率",
+            "C-rate",
+            "C-rate",
+            "MWh"
+        ]
+    })
+    
+    # 写入Excel文件
+    with pd.ExcelWriter(filename, engine='openpyxl') as writer:
+        # 写入主要数据
+        data_df.to_excel(writer, sheet_name='运行数据', index=False)
+        
+        # 写入统计信息
+        stats_df.to_excel(writer, sheet_name='统计结果', index=False)
+        
+        # 写入系统参数
+        params_df.to_excel(writer, sheet_name='系统参数', index=False)
+        
+        # 创建说明工作表
+        description_df = pd.DataFrame({
+            '项目': [
+                '文件说明',
+                '生成时间',
+                '数据长度',
+                '数据内容',
+                '注意事项'
+            ],
+            '内容': [
+                '多能互补系统储能容量优化结果',
+                datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+                f"{len(solar_output)} 小时",
+                '包含发电、负荷、储能、弃风弃光、购电上网等完整数据',
+                '负值表示购电，正值表示上网电量'
+            ]
+        })
+        description_df.to_excel(writer, sheet_name='说明', index=False)
+    
+    print(f"结果已成功导出到: {filename}")
+    return filename
+
 
 def generate_yearly_data():
     """生成8760小时的示例数据"""
@@ -313,6 +509,12 @@ def main():
     print("正在绘制系统运行曲线...")
     plot_system_curves(solar_output, wind_output, thermal_output, load_demand, result, show_window, display_only)
     
+    # 导出结果到Excel
+    try:
+        export_results_to_excel(solar_output, wind_output, thermal_output, load_demand, result, params)
+    except Exception as e:
+        print(f"导出Excel文件失败：{str(e)}")
+    
     if display_only:
         print("\n正在显示图形窗口...")
     elif show_window: