如何计算每个时间间隔的机器总功耗，并跟踪开始和结束时间？

Question

我有一个数据集，其中多台机器（A、B、C）在特定时间段内以不同的速率消耗电力。数据包括每台机器用电的开始和结束时间以及用电率。我想计算每个有变化的时间间隔的总功耗，并跟踪这些时间段的开始和结束时间。

如何在 R 中实现这一目标，同时确保正确处理开始和结束时间？

示例数据：

data <- data.frame(
  MachineID = c(1, 1, 2, 2),
  PowerA_Start = c("2022-01-01 00:00:00", "2022-01-01 02:00:00", "2022-01-02 00:00:00", "2022-01-02 02:00:00"),
  PowerA_End = c("2022-01-01 01:00:00", "2022-01-01 03:00:00", "2022-01-02 01:00:00", "2022-01-02 03:00:00"),
  PowerA_Consumption = c(5, 10, 7, 12),
  PowerB_Start = c("2022-01-01 00:30:00", "2022-01-01 02:30:00", "2022-01-02 00:30:00", "2022-01-02 02:30:00"),
  PowerB_End = c("2022-01-01 01:30:00", "2022-01-01 03:30:00", "2022-01-02 01:30:00", "2022-01-02 03:30:00"),
  PowerB_Consumption = c(3, 6, 5, 8),
  PowerC_Start = c("2022-01-01 01:00:00", "2022-01-01 03:00:00", "2022-01-02 01:00:00", "2022-01-02 03:00:00"),
  PowerC_End = c("2022-01-01 02:00:00", "2022-01-01 04:00:00", "2022-01-02 02:00:00", "2022-01-02 04:00:00"),
  PowerC_Consumption = c(4, 8, 6, 10)
)

预期结果：

• 对于每台机器，计算每个时间间隔的总功耗，并返回功耗发生变化的那些间隔的开始和结束时间。

           MachineID Start_Time          End_Time            Total_Consumption
           <dbl> <dttm>              <dttm>                   <dbl>
     1         1 2022-01-01 00:00:00 2022-01-01 00:30:00          5
     2         1 2022-01-01 00:30:00 2022-01-01 01:00:00          8
     .
     .

Answer 1

有更短的方法可以做到这一点，但我认为如果我们将更长的形状重塑两次，首先放置各种“PowerA/PowerB/etc”，这是最清晰的。观察结果分成各自的行，然后将开始和结束分开。这很有帮助，因为开始代表消耗增加，而结束代表消耗减少。

data |>
  pivot_longer(-MachineID,
               names_to = c("phase", ".value"),
               names_pattern = "(.*)_(.*)") |>
  pivot_longer(Start:End, values_to = "dt") |>
  arrange(MachineID, dt) |>
  mutate(Total_Consumption = cumsum(Consumption * ifelse(name == "End", -1, 1)),
         .by = MachineID) |>
  slice_max(name, by = c(MachineID, dt)) |>
  mutate(MachineID, Start_time = dt, End_time = lead(dt), Total_Consumption,
        .keep = "none", .by = MachineID) |>
  filter(!is.na(End_time))

结果

# A tibble: 16 × 4
   MachineID Total_Consumption Start_time          End_time           
       <dbl>             <dbl> <chr>               <chr>              
 1         1                 5 2022-01-01 00:00:00 2022-01-01 00:30:00
 2         1                 8 2022-01-01 00:30:00 2022-01-01 01:00:00
 3         1                 7 2022-01-01 01:00:00 2022-01-01 01:30:00
 4         1                 4 2022-01-01 01:30:00 2022-01-01 02:00:00
 5         1                10 2022-01-01 02:00:00 2022-01-01 02:30:00
 6         1                16 2022-01-01 02:30:00 2022-01-01 03:00:00
 7         1                14 2022-01-01 03:00:00 2022-01-01 03:30:00
 8         1                 8 2022-01-01 03:30:00 2022-01-01 04:00:00
 9         2                 7 2022-01-02 00:00:00 2022-01-02 00:30:00
10         2                12 2022-01-02 00:30:00 2022-01-02 01:00:00
11         2                11 2022-01-02 01:00:00 2022-01-02 01:30:00
12         2                 6 2022-01-02 01:30:00 2022-01-02 02:00:00
13         2                12 2022-01-02 02:00:00 2022-01-02 02:30:00
14         2                20 2022-01-02 02:30:00 2022-01-02 03:00:00
15         2                18 2022-01-02 03:00:00 2022-01-02 03:30:00
16         2                10 2022-01-02 03:30:00 2022-01-02 04:00:00