Turkish Electricity Generation Tracking with eptr2

Overview

This skill helps you query electricity generation data from Turkey's EPIAS Transparency Platform using the eptr2 Python library.

Quick Start

python

from eptr2 import EPTR2

# Initialize with environment variables
eptr = EPTR2(use_dotenv=True, recycle_tgt=True)

# Get real-time generation by resource type
rt_gen = eptr.call("rt-generation", start_date="2024-07-29", end_date="2024-07-29")
print(rt_gen)

Available Generation Endpoints

Call	Description (EN)	Description (TR)
`rt-generation`	Real-time generation by resource type	Kaynak Bazlı Gerçek Zamanlı Üretim
`rt-gen`	Real-time generation (same as above)	Gerçek Zamanlı Üretim
`uevm`	Settlement generation (UEVM)	Uzlaştırmaya Esas Veriş Miktarı
`dpp` / `kgup`	Daily Production Plan	Kesinleşmiş Günlük Üretim Planı (KGÜP)
`rt-gen-org`	Real-time generation by organization	Organizasyon Bazlı GZÜ
`uevm-pp`	UEVM by power plant	Santral Bazlı UEVM

Resource Types (Fuel Types)

Turkish	English	Code
Doğalgaz	Natural Gas	naturalGas
Kömür	Coal	coal
Linyit	Lignite	lignite
İthal Kömür	Imported Coal	importedCoal
Rüzgar	Wind	wind
Güneş	Solar	sun
Hidroelektrik	Hydro	river, dammedHydro
Biyokütle	Biomass	biomass
Jeotermal	Geothermal	geothermal
Nükleer	Nuclear	nuclear

Composite Function for Generation Data

python

from eptr2.composite import get_hourly_production_data

df = get_hourly_production_data(
    eptr,
    start_date="2024-07-29",
    end_date="2024-07-29",
    verbose=True
)

Output Columns

Columns include _rt (real-time) and _uevm (settlement) suffixes:

Column	Description
`dt`	Datetime in ISO format
`naturalGas_rt`	Natural gas real-time generation
`wind_rt`	Wind real-time generation
`sun_rt`	Solar real-time generation
`total_rt`	Total real-time generation
`naturalGas_uevm`	Natural gas settlement generation
`total_uevm`	Total settlement generation
`contract`	Contract symbol

Common Use Cases

1. Total Generation Mix

python

rt_gen = eptr.call("rt-generation", start_date="2024-07-15", end_date="2024-07-15")

# Sum by resource type
fuel_mix = rt_gen.drop(columns=['date', 'hour']).sum()
total = fuel_mix.sum()

print("Generation Mix (July 15, 2024):")
for fuel, gen in fuel_mix.items():
    pct = (gen / total) * 100
    print(f"  {fuel}: {gen:,.0f} MWh ({pct:.1f}%)")

2. Renewable Energy Share

python

rt_gen = eptr.call("rt-generation", start_date="2024-07-15", end_date="2024-07-15")

# Define renewable columns
renewables = ['wind', 'sun', 'river', 'dammedHydro', 'geothermal', 'biomass']
renewable_cols = [c for c in rt_gen.columns if any(r in c.lower() for r in renewables)]

rt_gen['renewable'] = rt_gen[renewable_cols].sum(axis=1)
rt_gen['total'] = rt_gen.drop(columns=['date', 'hour']).sum(axis=1)
rt_gen['renewable_share'] = (rt_gen['renewable'] / rt_gen['total']) * 100

print(f"Average Renewable Share: {rt_gen['renewable_share'].mean():.1f}%")

3. Plant-Specific Generation

python

from eptr2.composite import get_hourly_production_data

# Example: Atatürk Dam (HES)
df = get_hourly_production_data(
    eptr,
    start_date="2024-07-15",
    end_date="2024-07-15",
    rt_pp_id=641,    # Real-time ID for Atatürk HES
    uevm_pp_id=142   # UEVM ID for Atatürk HES
)

print(f"Atatürk Dam Daily Generation: {df['total_rt'].sum():,.0f} MWh")

4. Production Plan vs Actual

python

from eptr2.composite import get_hourly_production_plan_data

df = get_hourly_production_plan_data(
    eptr,
    start_date="2024-07-15",
    end_date="2024-07-15",
    org_id=195,      # ELEKTRİK ÜRETİM AŞ
    uevcb_id=733     # ATATÜRK HES DB
)

# Compare KGUP (plan) with actual

Understanding Generation Data Types

Real-Time Generation (GZÜ)

•What: Measured generation in near real-time
•When: Available ~15 minutes after each hour
•Use: Monitoring, market tracking

UEVM (Uzlaştırmaya Esas Veriş Miktarı)

•What: Official settlement generation after reconciliation
•When: Available after settlement period (~T+10 days)
•Use: Settlement, billing, final analysis

KGÜP (Kesinleşmiş Günlük Üretim Planı)

•What: Finalized daily production plan
•When: Published day-ahead
•Use: Market planning, deviation analysis

Date Format

Always use ISO format: YYYY-MM-DD (e.g., "2024-07-29")

Authentication

Set credentials in .env file:

code

EPTR_USERNAME=your_email@example.com
EPTR_PASSWORD=your_password

For More Details

•See examples.md for additional code examples