Open-source electricity planning model for least-cost capacity expansion and dispatch. Used in World Bank and ESMAP power-sector studies.
NREL Engage Project
Building a network flow model for planning
Domain specific language for generating EnergyPlus idf files and DOE-2 BDL files.
The exergy analysis of different power plant components is brought into this repository. The primary focus is on the Rankin and Brayton cycles. The repository consists of two main parts: the components level models and the cycle level.
⚡ A fast, modern EnergyPlus IDF/epJSON toolkit for Python
IDA ICE Energy Simulation ETL Pipeline, ETL pipeline for extracting, transforming, and loading IDA ICE building energy simulation outputs for analysis outside of the software, useful only for huge and long simulations.
Canadian transportation aggregator for the CANOE energy model (Temoa-compatible datasets)
Canadian industry sector aggregator for the CANOE energy model (Temoa-compatible datasets)
Canadian electricity sector aggregator for the CANOE energy model (Temoa-compatible datasets)
Simple stochastic energy model
Desktop app built with Flutter to simulate solar PV array energy assessment using the OSM-MEPS model at fixed tilt-azimuth orientations (check the releases sidebar/tab).
Hacettepe University SEC 597 Energy Modeling elective course illustrative materials
📖 Interactive EnergyPlus Input/Output reference documentation
Bottom-up cooling-demand model and life-cycle environmental impact assessment of residential and office cooling in The Hague — MSc thesis in Industrial Ecology.
A 3-layer spatial optimization framework for the German energy transition. Analyzing energy autarky across 16 states, 4 grid zones, and the national system to identify strategic storage and generation placement (2019–2025+).
Canadian residential buildings aggregator for the CANOE energy model (Temoa-compatible datasets)
Calculates heating power, electrical power, and COP maps for heat pumps based on user-defined temperature envelopes and empirical efficiency curves. Supports multiple refrigerants, customizable compressor parameters, and exports results to CSV and interactive HTML heatmaps.
Machine Learning project for optimizing wind turbine blade performance using Random Forest models, with a full Flask web app and live deployment.
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