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eptr2-price-analysis

스타25

포크3

업데이트2026년 2월 21일 12:34

Query and analyze Turkish electricity market prices including MCP (PTF/Piyasa Takas Fiyatı), SMP (SMF/Sistem Marjinal Fiyatı), WAP (Ağırlıklı Ortalama Fiyat), and imbalance prices. Use when asking about electricity prices, market clearing prices, day-ahead prices, system marginal prices, weighted average prices, or price comparisons in Turkey's energy market. Triggers on: PTF, SMF, GÖP fiyat, GİP fiyat, elektrik fiyatı.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

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출처

Tideseed

Tideseed/eptr2

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Turkish Electricity Price Analysis with eptr2

Overview

This skill helps you query and analyze electricity market prices from Turkey's EPIAS Transparency Platform using the eptr2 Python library.

Quick Start

from eptr2 import EPTR2

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

# Get Market Clearing Price (MCP/PTF)
mcp = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")
print(mcp)

Available Price Endpoints

Call	Alias	Description (EN)	Description (TR)
`mcp`	`ptf`	Market Clearing Price (Day-Ahead)	Piyasa Takas Fiyatı
`smp`	`smf`	System Marginal Price	Sistem Marjinal Fiyatı
`wap`	-	Weighted Average Price (Intraday)	Ağırlıklı Ortalama Fiyat
`mcp-smp-imb`	`imbalance-price`	Positive/Negative Imbalance Prices	Dengesizlik Fiyatları
`interim-mcp`	-	Interim MCP (before finalization)	Kesinleşmemiş PTF
`mcp-smp-imb`	-	Combined MCP, SMP and Imbalance	PTF, SMF ve Dengesizlik

Composite Function for Comprehensive Pricing

For complete price and cost analysis including imbalance costs:

from eptr2.composite import get_hourly_price_and_cost_data

df = get_hourly_price_and_cost_data(
    eptr,
    start_date="2024-07-29",
    end_date="2024-07-29",
    include_wap=True,       # Include IDM weighted average price
    add_kupst_cost=True     # Calculate KUPST deviation costs
)

Output Columns

Column	Description
`date`	Datetime in ISO format (+03:00 timezone)
`mcp`	Market Clearing Price (TL/MWh)
`smp`	System Marginal Price (TL/MWh)
`wap`	Weighted Average Price (TL/MWh)
`system_direction`	Enerji Açığı (deficit), Enerji Fazlası (surplus), Dengede (balanced)
`sd_sign`	-1 (deficit/up-regulation), 1 (surplus/down-regulation), 0 (balanced)
`pos_imb_price`	Positive imbalance price (TL/MWh)
`neg_imb_price`	Negative imbalance price (TL/MWh)
`pos_imb_cost`	Positive imbalance cost = MCP - pos_imb_price
`neg_imb_cost`	Negative imbalance cost = neg_imb_price - MCP
`kupst_cost`	KUPST unit deviation cost

Common Use Cases

1. Daily Price Comparison (MCP vs SMP)

mcp_df = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")
smp_df = eptr.call("smp", start_date="2024-07-29", end_date="2024-07-29")

# Merge for comparison
import pandas as pd
comparison = mcp_df.merge(smp_df, on="date", suffixes=("_mcp", "_smp"))

2. Intraday vs Day-Ahead Price Analysis

# Day-ahead price
mcp_df = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")

# Intraday weighted average price
wap_df = eptr.call("wap", start_date="2024-07-29", end_date="2024-07-29")

# Compare DAM vs IDM
comparison = mcp_df.merge(wap_df, on="date")
comparison["dam_idm_spread"] = comparison["price"] - comparison["wap"]

3. Imbalance Price Analysis

imb_df = eptr.call("mcp-smp-imb", start_date="2024-07-29", end_date="2024-07-29")
# Returns: positiveImbalancePrice, negativeImbalancePrice columns

Date Format

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

Authentication

Set credentials in .env file:

EPTR_USERNAME=your_email@example.com
EPTR_PASSWORD=your_password

Then initialize with:

eptr = EPTR2(use_dotenv=True, recycle_tgt=True)

For More Details

See api-reference.md for complete endpoint documentation
See examples.md for additional code examples

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name

eptr2-price-analysis

description

Turkish Electricity Price Analysis with eptr2

Overview

This skill helps you query and analyze electricity market prices from Turkey's EPIAS Transparency Platform using the eptr2 Python library.

Quick Start

from eptr2 import EPTR2

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

# Get Market Clearing Price (MCP/PTF)
mcp = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")
print(mcp)

Available Price Endpoints

Call	Alias	Description (EN)	Description (TR)
`mcp`	`ptf`	Market Clearing Price (Day-Ahead)	Piyasa Takas Fiyatı
`smp`	`smf`	System Marginal Price	Sistem Marjinal Fiyatı
`wap`	-	Weighted Average Price (Intraday)	Ağırlıklı Ortalama Fiyat
`mcp-smp-imb`	`imbalance-price`	Positive/Negative Imbalance Prices	Dengesizlik Fiyatları
`interim-mcp`	-	Interim MCP (before finalization)	Kesinleşmemiş PTF
`mcp-smp-imb`	-	Combined MCP, SMP and Imbalance	PTF, SMF ve Dengesizlik

Composite Function for Comprehensive Pricing

For complete price and cost analysis including imbalance costs:

from eptr2.composite import get_hourly_price_and_cost_data

df = get_hourly_price_and_cost_data(
    eptr,
    start_date="2024-07-29",
    end_date="2024-07-29",
    include_wap=True,       # Include IDM weighted average price
    add_kupst_cost=True     # Calculate KUPST deviation costs
)

Output Columns

Column	Description
`date`	Datetime in ISO format (+03:00 timezone)
`mcp`	Market Clearing Price (TL/MWh)
`smp`	System Marginal Price (TL/MWh)
`wap`	Weighted Average Price (TL/MWh)
`system_direction`	Enerji Açığı (deficit), Enerji Fazlası (surplus), Dengede (balanced)
`sd_sign`	-1 (deficit/up-regulation), 1 (surplus/down-regulation), 0 (balanced)
`pos_imb_price`	Positive imbalance price (TL/MWh)
`neg_imb_price`	Negative imbalance price (TL/MWh)
`pos_imb_cost`	Positive imbalance cost = MCP - pos_imb_price
`neg_imb_cost`	Negative imbalance cost = neg_imb_price - MCP
`kupst_cost`	KUPST unit deviation cost

Common Use Cases

1. Daily Price Comparison (MCP vs SMP)

mcp_df = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")
smp_df = eptr.call("smp", start_date="2024-07-29", end_date="2024-07-29")

# Merge for comparison
import pandas as pd
comparison = mcp_df.merge(smp_df, on="date", suffixes=("_mcp", "_smp"))

2. Intraday vs Day-Ahead Price Analysis

# Day-ahead price
mcp_df = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")

# Intraday weighted average price
wap_df = eptr.call("wap", start_date="2024-07-29", end_date="2024-07-29")

# Compare DAM vs IDM
comparison = mcp_df.merge(wap_df, on="date")
comparison["dam_idm_spread"] = comparison["price"] - comparison["wap"]

3. Imbalance Price Analysis

imb_df = eptr.call("mcp-smp-imb", start_date="2024-07-29", end_date="2024-07-29")
# Returns: positiveImbalancePrice, negativeImbalancePrice columns

Date Format

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

Authentication

Set credentials in .env file:

EPTR_USERNAME=your_email@example.com
EPTR_PASSWORD=your_password

Then initialize with:

eptr = EPTR2(use_dotenv=True, recycle_tgt=True)

For More Details

See api-reference.md for complete endpoint documentation
See examples.md for additional code examples