203 lines
7.9 KiB
Python
203 lines
7.9 KiB
Python
"""
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多能互补系统储能容量优化可视化程序
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该程序绘制负荷曲线、发电曲线和储能出力曲线，直观展示系统运行状态。
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作者: iFlow CLI
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创建日期: 2025-12-25
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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from storage_optimization import optimize_storage_capacity, SystemParameters
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# 设置中文字体
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plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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def plot_system_curves(solar_output, wind_output, thermal_output, load_demand, result):
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"""
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绘制系统运行曲线
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Args:
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solar_output: 光伏出力曲线 (MW) - 支持24小时或8760小时
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wind_output: 风电出力曲线 (MW) - 支持24小时或8760小时
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thermal_output: 火电出力曲线 (MW) - 支持24小时或8760小时
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load_demand: 负荷曲线 (MW) - 支持24小时或8760小时
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result: 优化结果字典
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"""
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hours = np.arange(len(solar_output))
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data_length = len(solar_output)
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# 确定图表标题和采样率
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if data_length == 8760:
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title_suffix = " (全年8760小时)"
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# 对于全年数据，我们采样显示（每6小时显示一个点）
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sample_rate = 6
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sampled_hours = hours[::sample_rate]
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sampled_solar = solar_output[::sample_rate]
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sampled_wind = wind_output[::sample_rate]
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sampled_thermal = thermal_output[::sample_rate]
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sampled_load = load_demand[::sample_rate]
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sampled_storage = result['storage_profile'][::sample_rate]
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sampled_charge = result['charge_profile'][::sample_rate]
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sampled_discharge = result['discharge_profile'][::sample_rate]
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else:
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title_suffix = " (24小时)"
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sampled_hours = hours
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sampled_solar = solar_output
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sampled_wind = wind_output
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sampled_thermal = thermal_output
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sampled_load = load_demand
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sampled_storage = result['storage_profile']
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sampled_charge = result['charge_profile']
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sampled_discharge = result['discharge_profile']
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# 创建图形
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fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(14, 12))
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fig.suptitle('多能互补系统24小时运行曲线', fontsize=16, fontweight='bold')
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# === 第一个子图：发电和负荷曲线 ===
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ax1.plot(sampled_hours, sampled_load, 'r-', linewidth=2, label='负荷需求')
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ax1.plot(sampled_hours, sampled_thermal, 'b-', linewidth=2, label='火电出力')
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ax1.plot(sampled_hours, sampled_wind, 'g-', linewidth=2, label='风电出力')
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ax1.plot(sampled_hours, sampled_solar, 'orange', linewidth=2, label='光伏出力')
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# 计算总发电量
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total_generation = [sampled_thermal[i] + sampled_wind[i] + sampled_solar[i] for i in range(len(sampled_thermal))]
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ax1.plot(sampled_hours, total_generation, 'k--', linewidth=1.5, alpha=0.7, label='总发电量')
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ax1.set_xlabel('时间 (小时)')
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ax1.set_ylabel('功率 (MW)')
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ax1.set_title(f'发电与负荷曲线{title_suffix}')
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ax1.legend(loc='upper right')
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ax1.grid(True, alpha=0.3)
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ax1.set_xlim(0, max(sampled_hours))
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# === 第二个子图：储能充放电曲线 ===
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discharge_power = [-x for x in sampled_discharge] # 放电显示为负值
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ax2.bar(sampled_hours, sampled_charge, color='green', alpha=0.7, label='充电功率')
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ax2.bar(sampled_hours, discharge_power, color='red', alpha=0.7, label='放电功率')
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ax2.set_xlabel('时间 (小时)')
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ax2.set_ylabel('功率 (MW)')
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ax2.set_title(f'储能充放电功率{title_suffix}')
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ax2.legend(loc='upper right')
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ax2.grid(True, alpha=0.3)
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ax2.set_xlim(0, max(sampled_hours))
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ax2.axhline(y=0, color='black', linestyle='-', linewidth=0.5)
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# === 第三个子图：储能状态曲线 ===
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ax3.plot(sampled_hours, sampled_storage, 'b-', linewidth=1, marker='o', markersize=2)
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ax3.fill_between(sampled_hours, 0, sampled_storage, alpha=0.3, color='blue')
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ax3.set_xlabel('时间 (小时)')
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ax3.set_ylabel('储能容量 (MWh)')
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ax3.set_title(f'储能状态 (总容量: {result["required_storage_capacity"]:.2f} MWh){title_suffix}')
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ax3.grid(True, alpha=0.3)
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ax3.set_xlim(0, max(sampled_hours))
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ax3.set_ylim(bottom=0)
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# 调整布局
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plt.tight_layout()
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# 保存图片
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plt.savefig('system_curves.png', dpi=300, bbox_inches='tight')
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plt.close() # 关闭图形，不显示窗口
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# 打印统计信息
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print("\n=== 系统运行统计 ===")
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print(f"所需储能总容量: {result['required_storage_capacity']:.2f} MWh")
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print(f"最大储能状态: {max(result['storage_profile']):.2f} MWh")
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print(f"最小储能状态: {min(result['storage_profile']):.2f} MWh")
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print(f"总充电量: {sum(result['charge_profile']):.2f} MWh")
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print(f"总放电量: {sum(result['discharge_profile']):.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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print(f"上网电量比例: {result['total_grid_feed_in_ratio']:.3f}")
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def generate_yearly_data():
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"""生成8760小时的示例数据"""
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# 基础日模式
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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
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daily_wind = [2.0, 3.0, 4.0, 3.0, 2.0, 1.0] * 4
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daily_thermal = [5.0] * 24
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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,
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16.0, 14.0, 12.0, 10.0, 8.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 2.0]
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# 添加季节性变化
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import random
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random.seed(42)
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yearly_solar = []
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yearly_wind = []
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yearly_thermal = []
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yearly_load = []
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for day in range(365):
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# 季节性因子（夏季光伏更强，冬季负荷更高）
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season_factor = 1.0 + 0.3 * np.sin(2 * np.pi * day / 365)
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for hour in range(24):
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# 添加随机变化
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solar_variation = 1.0 + 0.2 * (random.random() - 0.5)
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wind_variation = 1.0 + 0.3 * (random.random() - 0.5)
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load_variation = 1.0 + 0.1 * (random.random() - 0.5)
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yearly_solar.append(daily_solar[hour] * season_factor * solar_variation)
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yearly_wind.append(daily_wind[hour] * wind_variation)
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yearly_thermal.append(daily_thermal[hour])
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yearly_load.append(daily_load[hour] * (2.0 - season_factor) * load_variation)
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return yearly_solar, yearly_wind, yearly_thermal, yearly_load
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def main():
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"""主函数"""
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import sys
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# 检查命令行参数
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use_yearly_data = len(sys.argv) > 1 and sys.argv[1] == '--yearly'
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if use_yearly_data:
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print("生成8760小时全年数据...")
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solar_output, wind_output, thermal_output, load_demand = generate_yearly_data()
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print(f"数据长度: {len(solar_output)} 小时")
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else:
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print("使用24小时示例数据...")
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# 示例数据
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solar_output = [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
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wind_output = [2.0, 3.0, 4.0, 3.0, 2.0, 1.0] * 4
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thermal_output = [5.0] * 24
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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,
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16.0, 14.0, 12.0, 10.0, 8.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 2.0]
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# 系统参数
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params = SystemParameters(
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max_curtailment_wind=0.1,
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max_curtailment_solar=0.1,
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max_grid_ratio=0.2,
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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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)
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# 计算最优储能容量
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print("正在计算最优储能容量...")
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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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# 绘制曲线
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print("正在绘制系统运行曲线...")
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plot_system_curves(solar_output, wind_output, thermal_output, load_demand, result)
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print("\n曲线图已保存为 'system_curves.png'")
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if __name__ == "__main__":
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main()
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