Stochastic Mobility Integration into Residential Energy Hubs

ESARS-ITEC24 26-29 November 2024

Description

Code for reproducing the case studies of "Stochastic Mobility Integration into Residential Energy Hubs" presented in the ESARS-ITEC 2024 Conference held in Naples on 26-29th of November.

The code implements a stochastic optimization model for the integration of electric vehicles and residential energy hubs. The model is based on a single-stage stochastic programming formulation that considers the uncertainty in the mobility patterns of the electric vehicles. The problem is modelled using Random Field Optimization. The code is implemented in Julia, JuMP and InfiniteOpt and uses the Ipopt solver.

The pipeline of paper is as follows:

Installation

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julia> cd("[INSERT_PATH_TO_FILES]/StochMobilityMCES-ITEC24/")

julia> ]

(@v1.10) pkg> activate .

(itec24) pkg> instantiate

Usage

The scripts in folder src build and optimize the models for the case studies presented in the paper. The scripts are organized as follows:

runCaseStudy1_DET.jl --> deterministic model for case study 1
runCaseStudy1_RFO.jl --> stochastic model for case study 1
runCaseStudy2_RFO.jl --> stochastic model for case study 2

to run the scripts, open a terminal and type:

julia> runCaseStudy1_DET.jl

All necessary functions are stored in fns folder. The data for the case studies is stored in data folder.

Results can be visualized in the notebooks. The notebooks are organized as follows:

cs1_analysis.ipynb --> analysis of the results for case study 1
cs2_analysis.ipynb --> analysis of the results for case study 2

Support

For support on code usage please submit an issue on the repository.

Authors and acknowledgment

This paper was done by Dario Slaifstein, Alvaro Menendez Agudin, Gautham Ram Chandra Mouli, Laura Ramirez Elizondo, and Pavol Bauer.

License

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