Python library for Montel EQ's Time Series API.
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Updated
Aug 18, 2026 - Python
Python library for Montel EQ's Time Series API.
Unified Python client for European power market data. Nord Pool, EPEX SPOT, ENTSO-E, EEX.
Python library for building day-ahead and intraday auction bids for European power markets. Curve construction, block bids, linked orders, exclusive groups, and EUPHEMIA-compatible output. Built for the 15-minute MTU era. Part of the Phase Nexa toolkit.
Holistic Optimization Program for Electricity
Python client to interact with EnAppSys' API services.
Open-source electricity spot price forecasting toolkit for China power markets.
A power market simulator for day-ahead, intraday and balancing markets in pure Python.
Energy Trading Library - Power Asset Modelisation - Forecasts - Dashboard - PPA
Python client for the EXAA Trading API. Day-ahead auction order management, results retrieval, and state polling for Austrian, German, and Dutch power markets.
Open version of the European Model for Power system Investments with Renewable Energy (EMPIRE) implemented in Julia programming language
OpenPTS · 开放式电力交易系统 — 可二次开发的电力交易平台开源骨架(Go + Next.js + PostgreSQL)
Generate and validate EUPHEMIA-compatible day-ahead and intraday auction bids for European power markets using Python.
Quantitative analysis of French Renewable Assets (Wind/Solar) & Hedging Strategies (Merchant vs PPA).
A dashboard for viewing historic NESO demand flexibility service (DFS) data and same-day forecasting.
两个细则Excel月度费用分析、模板填充与年度累计工具 | Bilingual Python toolkit with dual XLSX validation
Which PV plant design earns the most, not just the most kWh? A pvlib model valuing fixed, east-west, and single-axis-tracker layouts against real German day-ahead prices.
MILP dispatch optimizer for a grid-scale battery in the German day-ahead market. Quantifies perfect-foresight vs. forecast-driven revenue on real SMARD data.
AI4S power-market forecasting and energy-storage strategy pipeline with LightGBM, NWP diagnostics, and submission validation.
Analysis and Streamlit dashboard of renewable price cannibalization in Germany (2019–2024), built on real SMARD data.
A few files from the exercises and course project in TET4185 (Power markets)
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