rdtools.degradation.degradation_year_on_year¶
-
rdtools.degradation.
degradation_year_on_year
(energy_normalized, recenter=True, exceedance_prob=95, confidence_level=68.2)¶ Estimate the trend of a timeseries using the year-on-year decomposition approach and calculate a Monte Carlo-derived confidence interval of slope.
Parameters: - energy_normalized (pd.Series) -- Daily or lower frequency time series of normalized system ouput.
- recenter (bool, default True) -- Specify whether data is internally recentered to normalized yield
of 1 based on first year median. If False,
Rd_pct
is calculated assumingenergy_normalized
is passed already normalized to the year 0 system capacity. - exceedance_prob (float, default 95) -- The probability level to use for exceedance value calculation, in percent.
- confidence_level (float, default 68.2) -- The size of the confidence interval to return, in percent.
Returns: - Rd_pct (float) -- Estimated degradation relative to the year 0 median system capacity [%/year]
- confidence_interval (np.array) -- confidence interval (size specified by
confidence_level
) of degradation rate estimate - calc_info (dict) --
- YoY_values - pandas series of right-labeled year on year slopes
- renormalizing_factor - float of value used to recenter data
- exceedance_level - the degradation rate that was outperformed with probability of exceedance_prob