library(tidyverse)

Tab1 <- tribble(
~Year,  ~UnitA, ~UnitB, ~UnitC, ~UnitD,
2023,   5000,   4000,   3000,   2000,
2024,   5000,   4000,   3000,   2000,
2025,   5000,   4000,   3000,   0,
2026,   0,  4000,   3000,   0,
2027,   0,  0,  3000,   0)

Tab2 <- tribble(
  ~Year,    ~UnitA, ~UnitB, ~UnitC, ~UnitD,
  2023, 120,    240,    170,    150,
  2024, 140,    250,    180,    175,
  2025, 160,    270,    190,    0,
  2026, 0,  300,    200,    0,
  2027, 0,  0,  215,    0)

Tab3 <- tribble(
  ~Year,    ~Hour,  ~Req_load,
  2023, 3,  10000,
  2023, 4,  13500,
  2025, 5,  8000,
  2025, 6,  18000,
)

consolidatedTab <- Tab1 %>%
  pivot_longer(cols = -c(Year), names_to = "Unit", names_prefix = "Unit", values_to = "load") %>%
  left_join(Tab2 %>%
              pivot_longer(cols = -c(Year), names_to = "Unit", names_prefix = "Unit", values_to = "marg")
            ) %>%
  group_by(Year) %>%
  arrange(marg, .by_group = TRUE) %>%
  mutate(totLoad = cumsum(load))

SummaryTab <- Tab3 %>%
  rowwise() %>%
  mutate(missingLoad = ifelse(Req_load - max(consolidatedTab[consolidatedTab$Year == Year,]$totLoad) <= 0,
         0,
         Req_load - max(consolidatedTab[consolidatedTab$Year == Year,]$totLoad)
         ),
         finalUnit = ifelse(missingLoad >0, "N/A", first(consolidatedTab[consolidatedTab$Year == Year & consolidatedTab$totLoad > Req_load,]$Unit)),
         finalunitprice = ifelse(missingLoad >0, 0, first(consolidatedTab[consolidatedTab$Year == Year & consolidatedTab$totLoad > Req_load,]$marg))
         )

我尽了最大努力，抱歉没有解释但我得走了!
给出：

>head(consolidatedTab)
# A tibble: 6 × 5
# Groups:   Year [2]
   Year Unit   load  marg totLoad
  <dbl> <chr> <dbl> <dbl>   <dbl>
1  2023 A      5000   120    5000
2  2023 D      2000   150    7000
3  2023 C      3000   170   10000
4  2023 B      4000   240   14000
5  2024 A      5000   140    5000
6  2024 D      2000   175    7000
>

以及

>
# A tibble: 4 × 6
# Rowwise: 

       Year  Hour Req_load missingLoad finalUnit finalunitprice
      <dbl> <dbl>    <dbl>       <dbl> <chr>              <dbl>
    1  2023     3    10000           0 B                    240
    2  2023     4    13500           0 B                    240
    3  2025     5     8000           0 B                    270
    4  2025     6    18000        6000 N/A                    0