GB Curtailment Calculator

GB_curtailment.py

# Imports
import os
import dotenv

import pandas as pd

import ElexonDataPortal.API as edp_API

# Helper Functions
def create_BMRS_wrapper(API_key=None, env_fp='.env'):
    if API_key is None:
        if env_fp is not None:
            assert dotenv.load_dotenv(env_fp), 'No `.env` file was identified'
        API_key = os.environ['BMRS_API_key']
    
    edp_wrapper = edp_API.Wrapper(API_key)

    return edp_wrapper
  
flatten_list = lambda list_: [item for sublist in list_ for item in sublist]

def get_wf_ids(dictionary_url='https://raw.githubusercontent.com/OSUKED/Power-Station-Dictionary/main/data/output/power_stations.csv'):
    df_dictionary = pd.read_csv(dictionary_url)
    wf_ids = flatten_list(df_dictionary.query('fuel_type=="wind"')['sett_bmu_id'].str.split(', ').to_list())
    
    return wf_ids

def calc_curt_wind(df_detsysprices, wf_ids=[]):
    s_curt_wind = (df_detsysprices
                   .query('recordType=="BID" & soFlag=="T" & id in @wf_ids')
                   .astype({'bidVolume': float})
                   .groupby('datetime')
                   ['bidVolume']
                   .sum()
                   .abs()
                  )

    return s_curt_wind
  
# Retrieval
stream = 'DETSYSPRICES'

query_args = {
    'start_date' : '2019-12-01',
    'end_date' : '2019-12-07 23:30',
}

edp_wrapper = create_BMRS_wrapper()
df_detsysprices = edp_wrapper.query_orchestrator(stream, query_args)

wf_ids = get_wf_ids()
s_curt_wind = calc_curt_wind(df_detsysprices, wf_ids)

s_curt_wind.plot()