This commit is contained in:
linnce
parent
da75a621b8
commit
554b21a3f0
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import pandas as pd
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import math
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import numpy as np
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import requests
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from scipy.optimize import fsolve
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from tabulate import tabulate
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import json
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# 默认文件路径
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PV_EXCEL_PATH = r"./pv_product.xlsx" # 请确保此文件存在或更改为正确路径
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CONFIG_PATH = r"./config.json" # 配置文件路径
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# 地形类型与复杂性因子范围
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TERRAIN_COMPLEXITY_RANGES = {
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"distributed": {
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"耕地": (1.0, 1.2), "裸地": (1.0, 1.2), "草地": (1.1, 1.3),
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"灌木": (1.3, 1.5), "湿地": (1.5, 1.8), "林地": (1.5, 1.8), "建筑": (1.2, 1.5)
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},
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"centralized": {
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"耕地": (1.0, 1.2), "裸地": (1.0, 1.2), "草地": (1.1, 1.3),
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"灌木": (1.3, 1.6), "湿地": (1.5, 1.8), "林地": (1.6, 2.0)
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},
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"floating": {"水域": (1.2, 1.5)}
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}
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# 地形类型与土地可用性、发电效率的映射
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TERRAIN_ADJUSTMENTS = {
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"耕地": {"land_availability": 0.85, "K": 0.8}, "裸地": {"land_availability": 0.85, "K": 0.8},
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"草地": {"land_availability": 0.85, "K": 0.8}, "灌木": {"land_availability": 0.75, "K": 0.75},
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"湿地": {"land_availability": 0.65, "K": 0.75}, "水域": {"land_availability": 0.85, "K": 0.8},
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"林地": {"land_availability": 0.65, "K": 0.7}, "建筑": {"land_availability": 0.6, "K": 0.75}
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}
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# 光伏类型的装机容量上限 (MW/平方千米)
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CAPACITY_LIMITS = {
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"distributed": 25.0, "centralized": 50.0, "floating": 25.0
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}
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# 实际面板间距系数
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PANEL_SPACING_FACTORS = {
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"distributed": 1.5, "centralized": 1.2, "floating": 1.3
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}
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def get_slope_from_api(lat, lon):
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"""
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通过 OpenTopoData API 获取地形坡度（单位：度）。
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返回：坡度（0-25°），失败时返回 None（由调用者处理）
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"""
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if not isinstance(lat, (int, float)) or not isinstance(lon, (int, float)):
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print("警告：经纬度必须是数值")
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return None
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if not (-90 <= lat <= 90) or not (-180 <= lon <= 180):
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print(f"警告：经纬度超出范围 (lat={lat}, lon={lon})")
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return None
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# 尝试多个数据集
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datasets = ["srtm30m", "etopo1"]
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step = 0.001 # 约100米
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points = [
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f"{lat:.6f},{lon:.6f}",
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f"{lat + step:.6f},{lon:.6f}",
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f"{lat - step:.6f},{lon:.6f}",
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f"{lat:.6f},{lon + step:.6f}",
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f"{lat:.6f},{lon - step:.6f}"
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]
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locations = "|".join(points)
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for dataset in datasets:
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url = f"https://api.opentopodata.org/v1/{dataset}"
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params = {
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"locations": locations,
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"interpolation": "cubic"
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}
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print(f"发送请求：dataset={dataset}, locations={locations}")
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try:
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response = requests.get(url, params=params, timeout=10)
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response.raise_for_status()
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data = response.json()
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if "results" not in data or len(data["results"]) != 5:
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print(f"警告：{dataset} 返回无效数据: {data.get('error', '无错误信息')}")
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continue
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elevations = [result["elevation"] for result in data["results"]]
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if any(elev is None for elev in elevations):
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print(f"警告：{dataset} 高程数据包含空值")
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continue
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distance = 100
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height_diffs = [
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abs(elevations[1] - elevations[0]),
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abs(elevations[2] - elevations[0]),
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abs(elevations[3] - elevations[0]),
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abs(elevations[4] - elevations[0])
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]
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avg_height_diff = sum(height_diffs) / len(height_diffs)
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slope_rad = math.atan2(avg_height_diff, distance)
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slope_deg = math.degrees(slope_rad)
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slope_deg = min(max(slope_deg, 0), 25)
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print(f"获取成功！坡度: {slope_deg:.2f}° (dataset={dataset})")
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return slope_deg
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except requests.exceptions.HTTPError as e:
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print(f"警告：{dataset} 请求失败 (HTTP {e.response.status_code}): {e.response.text}")
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continue
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except requests.exceptions.RequestException as e:
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print(f"警告：{dataset} 请求失败: {e}")
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continue
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except Exception as e:
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print(f"警告：处理 {dataset} 数据出错: {e}")
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continue
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print("警告：所有数据集均失败")
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return None
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def calculate_psh_average(lat, lon, start_year=2010, end_year=2023):
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"""
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从 NASA POWER API 获取峰值日照小时数（PSH）。
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返回：平均 PSH（小时/天），失败时返回默认值 4.0
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"""
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url = "https://power.larc.nasa.gov/api/temporal/monthly/point"
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params = {
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"parameters": "ALLSKY_SFC_SW_DWN",
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"community": "RE",
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"longitude": lon,
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"latitude": lat,
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"format": "JSON",
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"start": str(start_year),
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"end": str(end_year)
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}
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try:
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response = requests.get(url, params=params, timeout=10)
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response.raise_for_status()
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data = response.json()
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if "properties" not in data or "parameter" not in data["properties"]:
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return 4.0
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ghi_data = data["properties"]["parameter"].get("ALLSKY_SFC_SW_DWN", {})
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if not ghi_data:
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return 4.0
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ghi_data = {k: v for k, v in ghi_data.items() if not k.endswith("13")}
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if not ghi_data:
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return 4.0
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df = pd.DataFrame.from_dict(ghi_data, orient="index", columns=["GHI (kWh/m²/day)"])
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new_index = [f"{k[:4]}-{k[-2:]:0>2}" for k in df.index]
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df.index = new_index
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if df.empty:
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return 4.0
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df["PSH (hours/day)"] = df["GHI (kWh/m²/day)"]
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if df["PSH (hours/day)"].isna().any():
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return 4.0
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df['Year'] = df.index.str[:4]
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annual_avg = df.groupby('Year')['PSH (hours/day)'].mean()
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if annual_avg.empty:
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return 4.0
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psh = annual_avg.mean()
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if math.isnan(psh):
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return 4.0
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print(f"获取成功！平均PSH: {psh:.2f} 小时/天")
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return psh
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except requests.exceptions.RequestException:
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return 4.0
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except Exception:
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return 4.0
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def calculate_optimal_tilt(lat):
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"""根据纬度计算最佳倾角（单位：度）"""
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try:
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lat_abs = abs(lat)
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if lat_abs < 25:
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optimal_tilt = lat_abs * 0.87
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elif lat_abs <= 50:
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optimal_tilt = lat_abs * 0.76 + 3.1
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else:
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optimal_tilt = lat_abs * 0.5 + 16.3
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return optimal_tilt
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except ValueError as e:
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raise Exception(f"倾角计算错误: {e}")
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def pv_area(panel_capacity, slope_deg, shading_factor=0.1, land_compactness=1.0, terrain_complexity=1.0):
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"""计算单块光伏组件占地面积"""
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base_area = panel_capacity * 6
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slope_factor = 1 + (slope_deg / 50) if slope_deg <= 15 else 1.5
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shade_factor = 1 + shading_factor * 2
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compact_factor = 1 / land_compactness if land_compactness > 0 else 1.5
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terrain_factor = terrain_complexity
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return base_area * slope_factor * shade_factor * compact_factor * terrain_factor
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def calculate_pv_potential(available_area_sq_km, component_name, longitude, latitude, slope_deg=10,
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shading_factor=0.1, land_compactness=0.8, terrain_complexity=1.2,
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terrain_type="耕地", pv_type="centralized", land_availability=0.85,
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min_irradiance=800, max_slope=25, electricity_price=0.65, q=0.02,
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is_fixed=True, optimize=True, peak_load_hour=16, cost_per_kw=3.4,
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E_S=1.0, K=0.8, project_lifetime=25, discount_rate=0.06):
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"""计算最小和最大组件数量的光伏系统潜力"""
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if available_area_sq_km <= 0:
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raise ValueError("可用面积必须大于0")
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if slope_deg < 0 or slope_deg > max_slope:
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raise ValueError(f"坡度必须在0-{max_slope}度之间")
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available_area_hectares = available_area_sq_km * 100
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valid_terrains = TERRAIN_COMPLEXITY_RANGES.get(pv_type, {})
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if terrain_type not in valid_terrains:
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raise ValueError(f"{pv_type} 光伏不支持 {terrain_type} 地形。可选地形：{list(valid_terrains.keys())}")
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terrain_adjustments = TERRAIN_ADJUSTMENTS.get(terrain_type, {"land_availability": 0.85, "K": 0.8})
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adjusted_land_availability = terrain_adjustments["land_availability"] / max(1.0, terrain_complexity)
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adjusted_K = terrain_adjustments["K"] / max(1.0, terrain_complexity)
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pv_info = get_pv_product_info(component_name)
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single_panel_capacity = pv_info["max_power"] / 1000
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pv_size = pv_info["pv_size"].split("×")
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panel_length = float(pv_size[0]) / 1000
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panel_width = float(pv_size[1]) / 1000
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panel_area_sqm = panel_length * panel_width
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tilt, azimuth = get_tilt_and_azimuth(is_fixed, optimize, longitude, latitude, peak_load_hour)
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array_distance = calculate_array_distance(panel_width * 1.1, tilt, latitude)
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spacing_factor = PANEL_SPACING_FACTORS.get(pv_type, 1.2)
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adjusted_array_distance = array_distance * spacing_factor
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effective_area_hectares = available_area_hectares * adjusted_land_availability
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effective_area_sqm = effective_area_hectares * 10000
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area_per_mw = 10000 * (1 + slope_deg / 50 if slope_deg <= 15 else 1.5) * (
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1 + shading_factor * 2) * terrain_complexity * spacing_factor
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capacity_density_limit = CAPACITY_LIMITS.get(pv_type, 5.0) / 1000
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max_capacity_by_density = effective_area_sqm * capacity_density_limit
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row_spacing = panel_length * math.sin(math.radians(tilt)) + adjusted_array_distance
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effective_panel_area = panel_area_sqm * (row_spacing / panel_length) * 1.2
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min_area_per_panel = effective_panel_area * 0.8
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max_area_per_panel = effective_panel_area * 1.5
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max_panels = math.floor(effective_area_sqm / min_area_per_panel)
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min_panels = math.floor(effective_area_sqm / max_area_per_panel)
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max_capacity_raw = calculate_installed_capacity(pv_info["max_power"], max_panels)
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min_capacity_raw = calculate_installed_capacity(pv_info["max_power"], min_panels)
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max_capacity = min(max_capacity_raw, max_capacity_by_density)
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min_capacity = min(min_capacity_raw, max_capacity_by_density * 0.8)
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theoretical_max_capacity_mw = available_area_sq_km * CAPACITY_LIMITS.get(pv_type, 5.0)
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if max_capacity / 1000 > theoretical_max_capacity_mw:
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max_capacity = theoretical_max_capacity_mw * 1000
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max_panels = math.floor(max_capacity * 1000 / pv_info["max_power"])
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if min_capacity / 1000 > theoretical_max_capacity_mw * 0.8:
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min_capacity = theoretical_max_capacity_mw * 1000 * 0.8
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min_panels = math.floor(min_capacity * 1000 / pv_info["max_power"])
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min_metrics = calculate_pv_metrics(
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component_name=component_name, electricity_price=electricity_price, pv_number=min_panels,
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q=q, longitude=longitude, latitude=latitude, is_fixed=is_fixed, optimize=optimize,
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peak_load_hour=peak_load_hour, cost_per_kw=cost_per_kw * terrain_complexity, E_S=E_S, K=adjusted_K,
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override_capacity=min_capacity
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)
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min_lcoe = calculate_lcoe(
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capacity=min_metrics["capacity"], annual_energy=min_metrics["annual_energy"],
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cost_per_kw=cost_per_kw * terrain_complexity, q=q, project_lifetime=project_lifetime,
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discount_rate=discount_rate
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)
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max_metrics = calculate_pv_metrics(
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component_name=component_name, electricity_price=electricity_price, pv_number=max_panels,
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q=q, longitude=longitude, latitude=latitude, is_fixed=is_fixed, optimize=optimize,
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peak_load_hour=peak_load_hour, cost_per_kw=cost_per_kw * terrain_complexity, E_S=E_S, K=adjusted_K,
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override_capacity=max_capacity
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)
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max_lcoe = calculate_lcoe(
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capacity=max_metrics["capacity"], annual_energy=max_metrics["annual_energy"],
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cost_per_kw=cost_per_kw * terrain_complexity, q=q, project_lifetime=project_lifetime,
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discount_rate=discount_rate
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)
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if min_panels == max_panels:
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print(f"警告：最小和最大组件数量相同 ({min_panels})，请检查地形复杂性或面积是否过小")
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if min_panels == 0 or max_panels == 0:
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print(f"警告：组件数量为0，请检查输入参数")
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return {
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"min_case": {
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**min_metrics, "lcoe": min_lcoe, "actual_panels": min_panels,
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"available_area_sq_km": available_area_sq_km, "available_area_hectares": available_area_hectares,
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"effective_area_hectares": effective_area_hectares, "panel_area_sqm": max_area_per_panel,
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"terrain_type": terrain_type, "pv_type": pv_type, "theoretical_max_capacity_mw": theoretical_max_capacity_mw
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},
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"max_case": {
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**max_metrics, "lcoe": max_lcoe, "actual_panels": max_panels,
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"available_area_sq_km": available_area_sq_km, "available_area_hectares": available_area_hectares,
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"effective_area_hectares": effective_area_hectares, "panel_area_sqm": min_area_per_panel,
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"terrain_type": terrain_type, "pv_type": pv_type, "theoretical_max_capacity_mw": theoretical_max_capacity_mw
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}
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}
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def calculate_lcoe(capacity, annual_energy, cost_per_kw, q, project_lifetime=25, discount_rate=0.06):
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"""计算平准化度电成本(LCOE)"""
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total_investment = capacity * cost_per_kw * 1000
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annual_om_cost = total_investment * q
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discount_factors = [(1 + discount_rate) ** -t for t in range(1, project_lifetime + 1)]
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discounted_energy = sum(annual_energy * discount_factors[t] for t in range(project_lifetime))
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discounted_costs = total_investment + sum(annual_om_cost * discount_factors[t] for t in range(project_lifetime))
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if discounted_energy == 0:
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return float('inf')
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return discounted_costs / discounted_energy
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def get_pv_product_info(component_name, excel_path=PV_EXCEL_PATH):
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"""从Excel获取光伏组件信息"""
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INDIAN_SITES = {
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"Gujarat": {"latitude": 22.2587, "longitude": 71.1924},
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"Rajasthan": {"latitude": 27.0238, "longitude": 74.2179},
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"Tamil Nadu": {"latitude": 11.1271, "longitude": 78.6569}
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}
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try:
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df = pd.read_excel(excel_path)
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if len(df.columns) < 10:
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raise ValueError("Excel文件需包含至少10列：组件名称、尺寸、功率等")
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row = df[df.iloc[:, 1] == component_name]
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if row.empty:
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raise ValueError(f"未找到组件：{component_name}")
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return {
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"component_name": component_name,
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"max_power": row.iloc[0, 5],
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"efficiency": row.iloc[0, 9],
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"pv_size": row.iloc[0, 3]
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}
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except FileNotFoundError:
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raise FileNotFoundError(f"未找到Excel文件：{excel_path}")
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except Exception as e:
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raise Exception(f"读取Excel出错：{e}")
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def get_tilt_and_azimuth(is_fixed=True, optimize=True, longitude=116, latitude=None, peak_load_hour=16):
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"""计算光伏系统的倾角和方位角"""
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if optimize and latitude is None:
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raise ValueError("优化模式下需提供纬度")
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if is_fixed:
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if optimize:
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tilt = calculate_optimal_tilt(latitude)
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azimuth = (peak_load_hour - 12) * 15 + (longitude - 116)
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azimuth = azimuth % 360 if azimuth >= 0 else azimuth + 360
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else:
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print("倾角：0°(水平)-90°(垂直) | 方位角：0°(正北)-180°(正南)，顺时针")
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tilt = float(input("请输入倾角(度)："))
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azimuth = float(input("请输入方位角(度)："))
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if not (0 <= tilt <= 90) or not (0 <= azimuth <= 360):
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raise ValueError("倾角需在0-90°，方位角需在0-360°")
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else:
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azimuth = 180
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if optimize:
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tilt = calculate_optimal_tilt(latitude)
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else:
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print("倾角：0°(水平)-90°(垂直)")
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||||
tilt = float(input("请输入倾角(度)："))
|
||||
if not (0 <= tilt <= 90):
|
||||
raise ValueError("倾角需在0-90°")
|
||||
return tilt, azimuth
|
||||
|
||||
|
||||
def calculate_array_distance(L, tilt, latitude):
|
||||
"""计算阵列间距"""
|
||||
beta_rad = math.radians(tilt)
|
||||
phi_rad = math.radians(latitude)
|
||||
return (L * math.cos(beta_rad) +
|
||||
L * math.sin(beta_rad) * 0.707 * math.tan(phi_rad) +
|
||||
0.4338 * math.tan(phi_rad))
|
||||
|
||||
|
||||
def calculate_equivalent_hours(P, P_r):
|
||||
"""计算等效小时数"""
|
||||
if P_r == 0:
|
||||
raise ValueError("额定功率不能为 0")
|
||||
return P / P_r
|
||||
|
||||
|
||||
def calculate_installed_capacity(max_power, num_components):
|
||||
"""计算装机容量"""
|
||||
if max_power < 0 or num_components < 0 or not isinstance(num_components, int):
|
||||
raise ValueError("功率和数量需为非负数，数量需为整数")
|
||||
return (max_power * num_components) / 1000
|
||||
|
||||
|
||||
def calculate_annual_energy(peak_hours, capacity, E_S=1.0, K=0.8):
|
||||
"""计算年发电量"""
|
||||
if any(x < 0 for x in [peak_hours, capacity]) or E_S <= 0 or not 0 <= K <= 1:
|
||||
raise ValueError("输入参数需满足：辐射量、容量≥0，E_S>0，K∈[0,1]")
|
||||
return peak_hours * 365 * (capacity / E_S) * K
|
||||
|
||||
|
||||
def calculate_environmental_benefits(E_p_million_kwh):
|
||||
"""计算环境收益"""
|
||||
if E_p_million_kwh < 0:
|
||||
raise ValueError("年发电量需≥0")
|
||||
return {
|
||||
"coal_reduction": E_p_million_kwh * 0.404 * 10,
|
||||
"CO2_reduction": E_p_million_kwh * 0.977 * 10,
|
||||
"SO2_reduction": E_p_million_kwh * 0.03 * 10,
|
||||
"NOX_reduction": E_p_million_kwh * 0.015 * 10
|
||||
}
|
||||
|
||||
|
||||
def calculate_reference_yield(E_p, electricity_price, IC, q, n=25):
|
||||
"""计算净现值(NPV)和内部收益率(IRR)"""
|
||||
if E_p < 0 or electricity_price < 0 or IC <= 0 or not 0 <= q <= 1:
|
||||
raise ValueError("发电量、电价≥0，投资成本>0，回收比例∈[0,1]")
|
||||
|
||||
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，请检查输入")
|
||||
npv = npv_equation(irr, E_p, electricity_price, IC, q)
|
||||
return {"NPV": npv, "IRR": irr * 100}
|
||||
|
||||
|
||||
def calculate_pv_metrics(component_name, electricity_price, pv_number, q, longitude, latitude,
|
||||
is_fixed=True, optimize=True, peak_load_hour=16, cost_per_kw=3.4, E_S=1.0, K=0.8,
|
||||
override_capacity=None):
|
||||
"""计算光伏项目的各项指标"""
|
||||
try:
|
||||
tilt, azimuth = get_tilt_and_azimuth(is_fixed, optimize, longitude, latitude, peak_load_hour)
|
||||
pv_info = get_pv_product_info(component_name)
|
||||
width_mm = float(pv_info["pv_size"].split("×")[1])
|
||||
L = (width_mm / 1000) * 1.1
|
||||
array_distance = calculate_array_distance(L, tilt, latitude)
|
||||
max_power = pv_info["max_power"]
|
||||
if override_capacity is not None:
|
||||
capacity = override_capacity
|
||||
else:
|
||||
capacity = calculate_installed_capacity(max_power, pv_number)
|
||||
peak_hours = calculate_psh_average(latitude, longitude)
|
||||
single_daily_energy = peak_hours * (capacity / pv_number) * K if pv_number > 0 else 0
|
||||
E_p = calculate_annual_energy(peak_hours, capacity, E_S, K)
|
||||
h = calculate_equivalent_hours(E_p, capacity) if capacity > 0 else 0
|
||||
E_p_million_kwh = E_p / 1000000
|
||||
env_benefits = calculate_environmental_benefits(E_p_million_kwh)
|
||||
IC = capacity * cost_per_kw * 1000
|
||||
ref_yield = calculate_reference_yield(E_p, electricity_price, IC, q)
|
||||
return {
|
||||
"longitude": longitude,
|
||||
"latitude": latitude,
|
||||
"component_name": component_name,
|
||||
"tilt": tilt,
|
||||
"azimuth": azimuth,
|
||||
"array_distance": array_distance,
|
||||
"max_power": max_power,
|
||||
"capacity": capacity,
|
||||
"peak_sunshine_hours": peak_hours,
|
||||
"single_daily_energy": single_daily_energy,
|
||||
"annual_energy": E_p,
|
||||
"equivalent_hours": h,
|
||||
"coal_reduction": env_benefits["coal_reduction"],
|
||||
"CO2_reduction": env_benefits["CO2_reduction"],
|
||||
"SO2_reduction": env_benefits["SO2_reduction"],
|
||||
"NOX_reduction": env_benefits["NOX_reduction"],
|
||||
"IRR": ref_yield["IRR"]
|
||||
}
|
||||
except Exception as e:
|
||||
raise Exception(f"计算过程中发生错误: {str(e)}")
|
||||
|
||||
|
||||
def print_result(min_case, max_case):
|
||||
"""优化输出格式，使用表格展示结果"""
|
||||
headers = ["指标", "最小组件数量", "最大组件数量"]
|
||||
table_data = [
|
||||
["经度", f"{min_case['longitude']:.2f}", f"{max_case['longitude']:.2f}"],
|
||||
["纬度", f"{min_case['latitude']:.2f}", f"{max_case['latitude']:.2f}"],
|
||||
["光伏类型", min_case["pv_type"], max_case["pv_type"]],
|
||||
["地形类型", min_case["terrain_type"], max_case["terrain_type"]],
|
||||
["组件型号", min_case["component_name"], max_case["component_name"]],
|
||||
["识别面积 (平方千米)", f"{min_case['available_area_sq_km']:.2f}", f"{max_case['available_area_sq_km']:.2f}"],
|
||||
["识别面积 (公顷)", f"{min_case['available_area_hectares']:.2f}", f"{max_case['available_area_hectares']:.2f}"],
|
||||
["有效面积 (公顷)", f"{min_case['effective_area_hectares']:.2f}", f"{max_case['effective_area_hectares']:.2f}"],
|
||||
["理论最大容量 (MW)", f"{min_case['theoretical_max_capacity_mw']:.2f}",
|
||||
f"{max_case['theoretical_max_capacity_mw']:.2f}"],
|
||||
["单块组件占地 (m²)", f"{min_case['panel_area_sqm']:.2f}", f"{max_case['panel_area_sqm']:.2f}"],
|
||||
["组件数量", f"{min_case['actual_panels']:,}", f"{max_case['actual_panels']:,}"],
|
||||
["倾角 (度)", f"{min_case['tilt']:.2f}", f"{max_case['tilt']:.2f}"],
|
||||
["方位角 (度)", f"{min_case['azimuth']:.2f}", f"{max_case['azimuth']:.2f}"],
|
||||
["阵列间距 (m)", f"{min_case['array_distance']:.2f}", f"{max_case['array_distance']:.2f}"],
|
||||
["单块功率 (Wp)", f"{min_case['max_power']}", f"{max_case['max_power']}"],
|
||||
["装机容量 (MW)", f"{min_case['capacity'] / 1000:.2f}", f"{max_case['capacity'] / 1000:.2f}"],
|
||||
["峰值日照 (小时/天)", f"{min_case['peak_sunshine_hours']:.2f}", f"{max_case['peak_sunshine_hours']:.2f}"],
|
||||
["年发电量 (kWh)", f"{min_case['annual_energy']:,.0f}", f"{max_case['annual_energy']:,.0f}"],
|
||||
["等效小时数", f"{min_case['equivalent_hours']:.2f}", f"{max_case['equivalent_hours']:.2f}"],
|
||||
["LCOE (元/kWh)", f"{min_case['lcoe']:.4f}", f"{max_case['lcoe']:.4f}"],
|
||||
["标准煤减排 (kg)", f"{min_case['coal_reduction']:,.0f}", f"{max_case['coal_reduction']:,.0f}"],
|
||||
["CO₂减排 (kg)", f"{min_case['CO2_reduction']:,.0f}", f"{max_case['CO2_reduction']:,.0f}"],
|
||||
["SO₂减排 (kg)", f"{min_case['SO2_reduction']:,.0f}", f"{max_case['SO2_reduction']:,.0f}"],
|
||||
["NOx减排 (kg)", f"{min_case['NOX_reduction']:,.0f}", f"{max_case['NOX_reduction']:,.0f}"],
|
||||
["IRR (%)", f"{min_case['IRR']:.2f}", f"{max_case['IRR']:.2f}"]
|
||||
]
|
||||
print("\n===== 光伏系统潜力评估结果 =====")
|
||||
print(tabulate(table_data, headers=headers, tablefmt="grid"))
|
||||
|
||||
|
||||
# 主程序
|
||||
if __name__ == "__main__":
|
||||
while True:
|
||||
try:
|
||||
# 加载配置文件
|
||||
try:
|
||||
with open(CONFIG_PATH, "r", encoding="utf-8") as f:
|
||||
config = json.load(f)
|
||||
except FileNotFoundError:
|
||||
print(f"错误：未找到配置文件 {CONFIG_PATH}，使用默认值")
|
||||
config = {
|
||||
"default_terrain_complexity": {
|
||||
"耕地": 1.1, "裸地": 1.1, "草地": 1.2, "灌木": 1.4,
|
||||
"湿地": 1.65, "林地": 1.65, "建筑": 1.35, "水域": 1.35
|
||||
}
|
||||
}
|
||||
except json.JSONDecodeError:
|
||||
print(f"错误：配置文件 {CONFIG_PATH} 格式错误，使用默认值")
|
||||
config = {
|
||||
"default_terrain_complexity": {
|
||||
"耕地": 1.1, "裸地": 1.1, "草地": 1.2, "灌木": 1.4,
|
||||
"湿地": 1.65, "林地": 1.65, "建筑": 1.35, "水域": 1.35
|
||||
}
|
||||
}
|
||||
|
||||
print("\n======= 光伏系统潜力评估 =======")
|
||||
print("请输入以下必要参数：")
|
||||
latitude = float(input("请输入纬度（-90到90，例如39.9）："))
|
||||
if not -90 <= latitude <= 90:
|
||||
raise ValueError("纬度必须在-90到90之间")
|
||||
longitude = float(input("请输入经度（-180到180，例如116.4）："))
|
||||
if not -180 <= longitude <= 180:
|
||||
raise ValueError("经度必须在-180到180之间")
|
||||
available_area_sq_km = float(input("请输入识别面积（平方千米，例如10）："))
|
||||
if available_area_sq_km <= 0:
|
||||
raise ValueError("识别面积必须大于0")
|
||||
pv_type = input("请输入光伏类型（distributed, centralized, floating）：").lower()
|
||||
if pv_type not in ["distributed", "centralized", "floating"]:
|
||||
raise ValueError("光伏类型必须是 distributed, centralized 或 floating")
|
||||
valid_terrains = list(TERRAIN_COMPLEXITY_RANGES.get(pv_type, {}).keys())
|
||||
print(f"支持的地形类型：{valid_terrains}")
|
||||
terrain_type = input("请输入地形类型：")
|
||||
if terrain_type not in valid_terrains:
|
||||
raise ValueError(f"不支持的地形类型：{terrain_type}")
|
||||
component_name = input("请输入光伏组件型号（需在Excel中存在，例如M10-72H）：")
|
||||
electricity_price = float(input("请输入电价（元/kWh，例如0.65）："))
|
||||
if electricity_price < 0:
|
||||
raise ValueError("电价必须非负")
|
||||
|
||||
# 从配置文件获取地形复杂性因子
|
||||
terrain_complexity = config["default_terrain_complexity"].get(terrain_type, 1.2)
|
||||
|
||||
# 验证复杂性因子范围
|
||||
min_complexity, max_complexity = TERRAIN_COMPLEXITY_RANGES[pv_type][terrain_type]
|
||||
if not min_complexity <= terrain_complexity <= max_complexity:
|
||||
raise ValueError(f"地形复杂性因子 {terrain_complexity} 超出范围 [{min_complexity}, {max_complexity}]")
|
||||
|
||||
# 通过 API 获取坡度
|
||||
slope_deg = get_slope_from_api(latitude, longitude)
|
||||
|
||||
print(f"使用参数：坡度={slope_deg:.2f}°，地形复杂性因子={terrain_complexity}")
|
||||
|
||||
# 计算光伏潜力
|
||||
result = calculate_pv_potential(
|
||||
available_area_sq_km=available_area_sq_km,
|
||||
component_name=component_name,
|
||||
longitude=longitude,
|
||||
latitude=latitude,
|
||||
slope_deg=slope_deg,
|
||||
terrain_complexity=terrain_complexity,
|
||||
terrain_type=terrain_type,
|
||||
pv_type=pv_type,
|
||||
electricity_price=electricity_price
|
||||
)
|
||||
|
||||
# 输出结果
|
||||
print_result(result["min_case"], result["max_case"])
|
||||
|
||||
# 询问是否继续
|
||||
if input("\n是否继续评估？(y/n)：").lower() != 'y':
|
||||
break
|
||||
|
||||
except ValueError as ve:
|
||||
print(f"输入错误：{ve}")
|
||||
except FileNotFoundError as fe:
|
||||
print(f"文件错误：{fe}")
|
||||
except Exception as e:
|
||||
print(f"发生错误：{e}")
|
||||
print("请重新输入参数或检查错误。\n")
|
||||
Loading…
Reference in New Issue