cloud
255 lines
5.1 KiB
Markdown
255 lines
5.1 KiB
Markdown
# 接口文档
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## 通用响应
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后端接口统一返回：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {}
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}
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```
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`status` 为 `0` 表示成功，非 `0` 表示业务失败。
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## 系统接口
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### GET /api/system/health
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返回服务健康状态。
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {
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"status": "ok"
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}
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}
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```
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### GET /api/system/version
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返回服务版本信息。
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {
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"name": "wind_power_cal",
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"version": "0.1.0"
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}
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}
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```
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## 风功率计算接口
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### POST /api/wind/jobs/start
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创建风功率计算任务。前端已完成 Excel 表头解析和字段映射，后端只保存任务元数据。
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请求：
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```json
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{
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"files": [
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{
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"file_name": "01_风机历史数据.xls",
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"row_count": 51906
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}
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],
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"mapping": {
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"time": "时间",
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"fan_id": "风机编号",
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"wind_speed": "风速(m/s)",
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"active_power": "有功功率(kW)",
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"generator_speed": "发电机转速(rpm)"
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}
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}
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```
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {
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"job_id": "job_123"
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}
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}
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```
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### POST /api/wind/jobs/chunk
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上传标准化后的数据分片。每行字段必须使用标准字段名。
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请求：
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```json
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{
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"job_id": "job_123",
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"chunk_index": 0,
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"rows": [
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{
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"time": "2024-09-01 14:00:00",
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"fan_id": "01#",
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"wind_speed": 3.414,
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"active_power": 114.3471,
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"generator_speed": 1109.3143
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}
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]
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}
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```
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {
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"accepted_rows": 1
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}
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}
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```
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### POST /api/wind/jobs/finish
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完成任务并执行清洗、排序、分箱和功率曲线计算。
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请求：
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```json
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{
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"job_id": "job_123",
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"options": {
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"power_step": 5,
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"cleaning_wind_speed_step": 0.25,
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"curve_wind_speed_step": 0.5,
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"wind_speed_change_threshold": 1,
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"iqr_lower_multiplier": 1.8,
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"iqr_upper_multiplier": 2,
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"minimum_generator_speed": 1,
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"generator_speed_k": 0.9
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}
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}
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```
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": {
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"summary": {
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"raw_rows": 51906,
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"valid_rows": 38017,
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"invalid_rows": 13889,
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"duplicate_rows": 0,
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"limit_power_rows": 0,
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"tip_speed_ratio_outlier_rows": 0,
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"speed_power_outlier_rows": 0,
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"high_wind_low_power_rows": 0,
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"curve_residual_outlier_rows": 0,
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"rated_plateau_low_power_rows": 0,
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"invalid_reasons": {
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"invalid_active_power": 13889,
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"limit_power": 0,
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"tip_speed_ratio_outlier": 0,
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"speed_power_outlier": 0,
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"high_wind_low_power": 0,
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"curve_residual_outlier": 0,
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"rated_plateau_low_power": 0
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},
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"fan_count": 1
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},
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"fans": ["01#"],
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"curves": {
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"01#": [
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{
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"wind_speed_start": 3.0,
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"wind_speed_end": 3.5,
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"wind_speed": 3.25,
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"sample_count": 120,
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"average_power": 180.5,
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"median_power": 176.2,
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"stddev_power": 32.1,
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"p25_power": 150.0,
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"p75_power": 205.0,
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"confidence": "脚本分箱"
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}
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]
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},
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"bins": {
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"01#": []
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},
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"scatter_points": {
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"01#": [
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{
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"wind_speed": 3.414,
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"active_power": 114.3471
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}
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]
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},
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"filtered_points": {
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"01#": [
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{
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"wind_speed": 5.2,
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"active_power": 430.0,
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"reason": "speed_power_outlier"
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}
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]
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},
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"estimated_params": {
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"01#": {
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"rated_power": 3120.5,
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"rated_wind_speed": 10.75,
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"source": "auto"
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}
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}
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}
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}
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```
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清洗规则：
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- `active_power <= 0` 的数据剔除。
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- `generator_speed < generator_speed_k * minimum_generator_speed` 的数据剔除。
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- 时间不可解析的数据剔除。
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- 风机编号为空的数据剔除。
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- `wind_speed <= 0` 的数据剔除。
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- 同一风机同一时间重复记录保留第一条。
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- 限功率识别按参考脚本执行：按功率分箱、按日期分组，组内风速跨度大于阈值时剔除。
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- 叶尖速比使用参考脚本公式 `generator_speed * 3.14 * 162 * 78 * 30 / wind_speed`，按风速分箱做 IQR 清洗。
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- 风速-功率关系按同一风速分箱和 IQR 参数清洗。
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- 每台风机在 IQR 清洗后自动估算平台功率和平台起始风速，返回到 `estimated_params`。
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- 高风速平台区明显低于平台功率的点剔除为 `high_wind_low_power`。
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- 基于分箱中位功率曲线的残差异常点剔除为 `curve_residual_outlier`。
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- 严格额定平台区残留偏低点剔除为 `rated_plateau_low_power`。
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- 最终曲线按 `curve_wind_speed_step` 左开右闭分箱，区间非空即输出平均功率点。
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- `scatter_points` 返回清洗后保留点，`filtered_points` 返回所有过滤阶段滤除的点和原因。
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- `estimated_params.source` 为 `auto`、`auto_power_fallback_wind` 或 `fallback`。
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### DELETE /api/wind/jobs/{job_id}
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清理未完成任务的临时文件。
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成功响应：
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```json
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{
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"status": 0,
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"msg": "success",
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"data": null
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}
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```
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