216 lines
8.2 KiB
Python
216 lines
8.2 KiB
Python
"""
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测试优先上网逻辑
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该程序创建一个测试场景，验证系统是否优先上网而不是弃风弃光。
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作者: iFlow CLI
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创建日期: 2025-12-26
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"""
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import sys
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import os
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src'))
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import pandas as pd
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from excel_reader import create_excel_template
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from storage_optimization import optimize_storage_capacity, SystemParameters
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def create_test_excel():
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"""创建测试用的Excel文件，有明显的发电盈余"""
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# 创建24小时数据，其中某些小时有大量盈余
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hours = 24
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# 设计数据：在6-12点有大量光伏出力，超过负荷
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solar = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 10.0, 15.0, 20.0, 20.0, 15.0, 10.0, 5.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
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wind = [2.0] * 24 # 稳定的风电
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thermal = [3.0] * 24 # 稳定的火电
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load = [5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 8.0, 8.0, 9.0, 9.0, 8.0, 8.0, 6.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0]
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# 验证长度
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print(f"数据长度检查: solar={len(solar)}, wind={len(wind)}, thermal={len(thermal)}, load={len(load)}")
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# 设置严格的上网电量限制（10%），迫使系统在超出限制时弃风弃光
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params = SystemParameters(
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max_curtailment_wind=0.15, # 允许15%弃风
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max_curtailment_solar=0.15, # 允许15%弃光
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max_grid_ratio=0.1, # 严格限制上网电量比例10%
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storage_efficiency=0.9,
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discharge_rate=1.0,
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charge_rate=1.0,
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max_storage_capacity=5.0 # 限制储能容量，增加上网压力
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)
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# 创建DataFrame
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df = pd.DataFrame({
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'小时': range(1, hours + 1),
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'光伏出力(MW)': solar,
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'风电出力(MW)': wind,
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'火电出力(MW)': thermal,
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'负荷需求(MW)': load
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})
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# 保存到Excel
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filename = 'test_grid_priority.xlsx'
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with pd.ExcelWriter(filename, engine='openpyxl') as writer:
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df.to_excel(writer, sheet_name='数据', index=False)
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# 添加参数工作表
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parameters_df = pd.DataFrame({
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'参数名称': [
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'最大弃风率',
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'最大弃光率',
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'最大上网电量比例',
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'储能效率',
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'放电倍率',
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'充电倍率',
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'最大储能容量'
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],
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'参数值': [
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0.15, # 最大弃风率
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0.15, # 最大弃光率
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0.1, # 最大上网电量比例（严格限制）
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0.9, # 储能效率
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1.0, # 放电倍率
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1.0, # 充电倍率
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5.0 # 最大储能容量（限制）
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],
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'参数说明': [
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'允许的最大弃风率（0.0-1.0）',
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'允许的最大弃光率（0.0-1.0）',
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'允许的最大上网电量比例（0.0-∞，只限制上网电量）',
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'储能充放电效率（0.0-1.0）',
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'储能放电倍率（C-rate，>0）',
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'储能充电倍率（C-rate，>0）',
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'储能容量上限（MWh，空表示无限制）'
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],
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'取值范围': [
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'0.0-1.0',
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'0.0-1.0',
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'≥0.0',
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'0.0-1.0',
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'>0',
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'>0',
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'>0或空'
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],
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'默认值': [
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'0.1',
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'0.1',
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'0.2',
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'0.9',
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'1.0',
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'1.0',
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'无限制'
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]
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})
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parameters_df.to_excel(writer, sheet_name='参数', index=False)
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# 添加说明工作表
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description_df = pd.DataFrame({
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'项目': ['数据说明', '数据类型', '时间范围', '单位', '注意事项', '参数说明'],
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'内容': [
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'测试优先上网逻辑的数据',
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'24小时电力数据',
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'1-24小时',
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'MW (兆瓦)',
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'所有数值必须为非负数',
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'设置了严格的上网电量限制(10%)和储能容量限制(5MWh)'
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]
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})
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description_df.to_excel(writer, sheet_name='说明', index=False)
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print(f"测试Excel文件已创建：{filename}")
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return filename
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def test_grid_priority():
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"""测试优先上网逻辑"""
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print("=== 测试优先上网逻辑 ===\n")
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# 创建测试文件
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test_file = create_test_excel()
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# 从Excel读取数据
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from excel_reader import read_excel_data
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data = read_excel_data(test_file, include_parameters=True)
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solar_output = data['solar_output']
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wind_output = data['wind_output']
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thermal_output = data['thermal_output']
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load_demand = data['load_demand']
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params = data['system_parameters']
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print("测试数据概况：")
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print(f"光伏出力范围: {min(solar_output):.1f} - {max(solar_output):.1f} MW")
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print(f"风电出力: {wind_output[0]:.1f} MW (恒定)")
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print(f"火电出力: {thermal_output[0]:.1f} MW (恒定)")
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print(f"负荷需求范围: {min(load_demand):.1f} - {max(load_demand):.1f} MW")
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print(f"\n系统参数：")
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print(f"最大上网电量比例: {params.max_grid_ratio}")
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print(f"最大储能容量: {params.max_storage_capacity} MWh")
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print(f"最大弃风率: {params.max_curtailment_wind}")
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print(f"最大弃光率: {params.max_curtailment_solar}")
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# 计算总发电量和负荷
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total_generation = sum(solar_output) + sum(wind_output) + sum(thermal_output)
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total_load = sum(load_demand)
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total_surplus = total_generation - total_load
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print(f"\n能量平衡：")
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print(f"总发电量: {total_generation:.1f} MWh")
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print(f"总负荷: {total_load:.1f} MWh")
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print(f"总盈余: {total_surplus:.1f} MWh")
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# 运行优化
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print("\n正在运行储能容量优化...")
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result = optimize_storage_capacity(
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solar_output, wind_output, thermal_output, load_demand, params
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)
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# 分析结果
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total_grid_feed_in = sum(result['grid_feed_in'])
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total_curtailed_wind = sum(result['curtailed_wind'])
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total_curtailed_solar = sum(result['curtailed_solar'])
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print(f"\n=== 优化结果 ===")
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print(f"所需储能容量: {result['required_storage_capacity']:.2f} MWh")
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print(f"实际上网电量: {total_grid_feed_in:.2f} MWh")
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print(f"上网电量比例: {result['total_grid_feed_in_ratio']:.3f}")
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print(f"弃风量: {total_curtailed_wind:.2f} MWh")
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print(f"弃光量: {total_curtailed_solar:.2f} MWh")
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print(f"弃风率: {result['total_curtailment_wind_ratio']:.3f}")
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print(f"弃光率: {result['total_curtailment_solar_ratio']:.3f}")
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# 验证优先上网逻辑
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max_allowed_grid = total_generation * params.max_grid_ratio
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print(f"\n=== 验证优先上网逻辑 ===")
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print(f"最大允许上网电量: {max_allowed_grid:.2f} MWh")
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print(f"实际上网电量: {total_grid_feed_in:.2f} MWh")
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if abs(total_grid_feed_in - max_allowed_grid) < 1.0: # 允许1MW误差
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print("[OK] 验证通过：系统优先上网，达到上网电量限制上限")
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else:
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print("[ERROR] 验证失败：系统未充分利用上网电量限制")
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if total_curtailed_wind > 0 or total_curtailed_solar > 0:
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print("[OK] 验证通过：在上网电量限制达到后，系统开始弃风弃光")
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else:
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print("[INFO] 注意：没有弃风弃光，可能盈余电力全部被储能或上网消化")
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# 查看具体小时的弃风弃光情况
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print(f"\n=== 详细分析（盈余时段） ===")
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for hour in range(6, 13): # 6-12点是光伏出力高峰
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available = solar_output[hour] + wind_output[hour] + thermal_output[hour]
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demand = load_demand[hour]
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surplus = available - demand
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grid = result['grid_feed_in'][hour]
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curtailed = result['curtailed_wind'][hour] + result['curtailed_solar'][hour]
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if surplus > 0:
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print(f"小时{hour}: 盈余{surplus:.1f}MW -> 上网{grid:.1f}MW + 弃风弃光{curtailed:.1f}MW")
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print(f"\n测试完成！")
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if __name__ == "__main__":
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test_grid_priority() |