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Annual RPS stringency indices

Source: R/rps_stringency.R
rps_stringency.Rd

Turns coded RPS rules (rps_rules()) into comparable state-year measures, so you can study how strong a policy is, not only whether it exists.

Usage

rps_stringency(
  years,
  states = NULL,
  method = c("adoption", "nominal", "coverage_adjusted", "incremental", "flexibility"),
  rules = rps_rules(),
  baseline = NULL,
  interpolation = c("linear", "step"),
  adopt_from = c("enactment", "first_compliance"),
  floor_zero = FALSE,
  sales = NULL,
  capacity_factor = 0.33
)

Arguments

years

Years to compute.

states

States to include (default: all 50 + DC).

method

One or more of "adoption", "nominal", "coverage_adjusted", "incremental", "flexibility".

rules

An rps_rules object; defaults to the bundled coding.

baseline

Optional data frame with columns state and baseline_share, the existing (eligible) renewable share of sales or generation at enactment. Overrides baseline_re_share in the rules.

interpolation

"linear" or "step".

adopt_from

Year from which adoption is 1: "enactment" or "first_compliance".

floor_zero

If TRUE, negative incremental requirements are set to 0.

sales

Optional data frame with columns state, year and sales_gwh (retail electricity sales, GWh, the same as EIA's million kWh), used to convert capacity-based standards into shares. build_panel() supplies it from EIA retail sales.

capacity_factor

Assumed capacity factor of the resources that meet a capacity-based standard. The default 0.33 is typical of wind, which met most of the Texas and Iowa requirements.

Value

A data frame with state, year and the columns for each method: rps_adoption, rps_nominal, rps_coverage_adj, rps_incremental, rps_baseline_share, rps_oos_rec, rps_carveout, rps_acp.

Details

Methods:

  • adoption: 1 if an RPS is in force that year (from adopt_from until any repeal), else 0.

  • nominal: required renewable share of retail sales in that year. Zero before the first compliance year. Between legal targets the requirement is interpolated linearly (interpolation = "linear") or held at the last legal target ("step"); after the final target year it is held constant. If the first coded target lies after the enactment year, linear interpolation starts from zero at enactment. Capacity-based (MW) standards (Texas, Iowa) are converted to an equivalent share of covered sales: MW * capacity_factor * 8.76 / (sales_gwh * coverage_share), the same approach Berkeley Lab uses. This needs sales; without it they are NA.

  • coverage_adjusted: nominal requirement times the share of retail sales covered by the standard.

  • incremental: requirement beyond the renewable share the state already had at enactment, following Yin and Powers (2010): nominal * coverage - baseline_share while the nominal requirement is positive, otherwise 0. The baseline is taken from baseline, or from the baseline_re_share column of the rules. Also returns the baseline used (rps_baseline_share). build_panel() measures the baseline the same way the target is defined: including hydro for states whose targets count existing hydro (baseline_includes_hydro = 1, New York), excluding it otherwise.

  • flexibility: indicators for out-of-state renewable credits, carve-outs and alternative compliance payments, set to 0 when no RPS is in force.

States missing from the rule coding get NA for every measure.

References

Yin, H., & Powers, N. (2010). Do state renewable portfolio standards promote in-state renewable generation? Energy Policy, 38(2), 1140-1149.

Examples

s <- rps_stringency(2000:2030, states = c("CA", "WA", "TX", "FL"),
                    method = c("adoption", "nominal"))
s[s$state == "WA" & s$year %in% 2011:2021, ]
#>     state year rps_adoption rps_nominal
#> 105    WA 2011            1        0.00
#> 106    WA 2012            1        0.03
#> 107    WA 2013            1        0.03
#> 108    WA 2014            1        0.03
#> 109    WA 2015            1        0.03
#> 110    WA 2016            1        0.09
#> 111    WA 2017            1        0.09
#> 112    WA 2018            1        0.09
#> 113    WA 2019            1        0.09
#> 114    WA 2020            1        0.15
#> 115    WA 2021            1        0.15

# Capacity (MW) standards become shares when sales are supplied
tx_sales <- data.frame(state = "TX", year = 2015, sales_gwh = 380000)
rps_stringency(2015, "TX", method = "nominal", sales = tx_sales)
#>   state year rps_nominal
#> 1    TX 2015  0.05909026

# Step interpolation follows the legal schedule exactly
rps_stringency(2012:2020, states = "WA", method = "nominal",
               interpolation = "step")
#>   state year rps_nominal
#> 1    WA 2012        0.03
#> 2    WA 2013        0.03
#> 3    WA 2014        0.03
#> 4    WA 2015        0.03
#> 5    WA 2016        0.09
#> 6    WA 2017        0.09
#> 7    WA 2018        0.09
#> 8    WA 2019        0.09
#> 9    WA 2020        0.15