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3952. Multi energy mixed integer linear programming model for generation and network expansion planning with coupled electricity and heat sectors considering renewable sources

Invited abstract in session WB-22: Capacity expansion planning for energy systems, stream Energy Management.

Wednesday, 10:30-12:00
Room: 81 (building: 116)

Authors (first author is the speaker)

1. Anibal Baradei
Department of Energy, Systems, Territory and Construction Engineering, University of Pisa
2. Matteo Pozzi
Optit srl
3. Angelo Gordini
Optit srl
4. Aldo Bischi
Department of Energy, Systems, Territory and Construction Engineering, University of Pisa

Abstract

Multi energy systems optimal planning main challenge is the equilibrium between model accuracy and computational feasibility. This is due to the need of large-scale, nationwide, generation and transmission expansion model that incorporates aspects such as optimal units and storage scheduling, space constraints, and renewable energy sources availability. Furthermore, the deep decarbonization needs of the future energy systems implies to have coupled energy infrastructures, e.g. electric, heat, gas, and long duration energy storage including all the possible interactions between them through multi year periods, yields an increasing model complexity. It is modeled as a mixed integer linear problem and aims to include all the key features of state-of-the-art models obtainable from a linear formulation. The objective function is the minimization of the overall system cost, and it includes investment, maintenance, network expansion, transmission hourly prices, energy regulations, and fuel prices.

The model has been implemented in Python language using Gurobi solver with an hourly time step. It can tackle in few minutes more than a year depending on the problem size: a yearly instance of 200 nodes yielded about 320 million continuous and tens of binary variables. The model flexibility enabled to run various sensitivity analyses to tackle uncertainty considering fuel availability, natural resources, different technologies, regulations, load profiles and time evolution.

Keywords

Status: accepted

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