07-11, 16:30–16:40 (Europe/Amsterdam), While Loop (4.2)
TulipaEnergyModel.jl is a Julia/JuMP package developed by TNO and eScience Center that models the electricity market and its coupling with other energy sectors (e.g., hydrogen, heat, natural gas, etc.). Its main features are flexible connection based on graph theory, flexible temporal resolution, and the use of representative periods without losing accuracy.
TulipaEnergyModel.jl provides an optimization model for the electricity market and its coupling with other energy sectors (e.g., hydrogen, heat, natural gas, etc.). The optimization model determines the optimal investment and operation decisions for different types of assets (e.g., producers, consumers, conversion, storage, and transport). Currently, TulipaEnergyModel.jl has two main core features. The first one uses graph theory for a more adaptable model representation. This representation provides a more flexible framework to model energy assets in the system as vertices, and to model flows between energy assets as edges. This carrier-agnostic approach makes it adaptable to different systems. Furthermore, in the classic approach, nodes play a crucial role in modelling. By implementing our approach, as the nodes are no longer needed to connect assets, we can connect assets directly to each other, thus reducing the model size. The other core feature is fully flexible time resolution. TulipaEnergyModel.jl can handle different time resolutions on the assets and the flows even if they are not multiples of each other. Typically, the time resolution in an energy model is hourly and fixed through most of the model. Depending on the input data and the level of detail you want to model, hourly resolution in all the variables might not be necessary. TulipaEnergyModel.jl allows different time resolutions for each asset and flow to simplify the optimization problem and approximate hourly representation. This feature is particularly useful for large-scale energy systems that involve different sectors, so greatly speeding solving times since detailed granularity is not always necessary due to the unique temporal dynamics of each sector.
I'm an electrical engineer with extensive experience in modeling and analyzing power systems. My expertise includes developing optimization models for unit commitment, generation, and transmission expansion planning. My doctoral thesis focused on the optimization of energy storage systems under large-scale renewable penetration.