Context and challenge: Growing demand for space cooling motivates the development of radiative and evaporative passive cooling panels to improve AC efficiency. The main challenge here is quantifying annual building-level energy savings across diverse climates and integration pathways, and comparing the net benefit of these panels against PV cells to guide optimal technology selection.
Expected activities:
– Define the modular modeling architecture, specifying submodel inputs, outputs, and coupling requirements.
– Implement a utility to fetch and preprocess TMY weather data for arbitrary locations.
– Develop an EnergyPlus model to estimate cooling load and potential energy savings based on building archetype and panel/PV surface coverage.
– Quantify the annual energy savings of hybrid cooling relative to PV allocation scenarios.
What we expect:
– Solid background in thermodynamics and heat transfer
– Minimum programming skills (any programming language, versioning)
What you will learn:
– Modeling with EnergyPlus
– Experience designing modular energy system models
– Programming and data management skills (Python, PostgreSQL)
– Scientific communications in the lab
Contact: Gautier Rouaze ([email protected])