Publication record · 18.cifr/2022.argiolas.bess-dispatch-ev

Optimal Battery Energy Storage Dispatch in Energy and Frequency Regulation Markets While Peak Shaving an EV Fast Charging Station

v1.0.0

Luca Argiolas (Delft University of Technology), Marco Stecca (Delft University of Technology), Laura M. Ramirez-Elizondo (Delft University of Technology), Thiago Batista Soeiro (Delft University of Technology), Pavol Bauer (Delft University of Technology)

RAI18.cifr/2022.argiolas.bess-dispatch-ev

IEEE Open Access Journal of Power and Energy· 2022· doi:10.1109/OAJPE.2022.3198553

Optimal dispatch of a battery energy storage system participating in energy and frequency regulation markets while peak shaving an EV fast charging station load using mixed-integer linear programming.

battery energy storagefrequency regulationpeak shavingEV fast chargingMILP optimizationenergy market

✦ Research context

What this agent contributes to the literature.

Problem solved

BESS operators lack a unified dispatch strategy covering energy markets, frequency regulation, and peak shaving at once.
Separate handling of FCR/aFRR and peak shaving leads to suboptimal revenue and constraint violations.
EV fast charging stations create sharp load peaks that stress grid connections and incur demand charges.

Novelty

Jointly optimizes BESS dispatch across energy markets, FCR/aFRR frequency regulation, and EV fast-charging peak shaving simultaneously.

Related research

Computing related research...

Canvas contract1-in / 1-out · unpacked into market_data, system_params legacy ports

Sample data

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Total calls

This month

Citations

Last called

4/15/2026

Image digest

sha256:ef3f57a38a26758a773c45ec01a73054ddca6cbb51b10de2024d58592aafc8f7

Invoke command

python main.py

Inputs

input:application/json

Outputs

output:application/json

Citation

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Invoke

CPU compute only

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Pre-filled with the paper's canonical scenario. Click Invoke agent to reproduce the original result, or edit the JSON below to run a counterfactual.

inputapplication/jsonoptional

Unified canvas input. The executor unpacks this JSON blob into legacy per-port files: market_data, system_params

Leave empty to run the paper's canonical scenario.

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  "system_params": {
    "E_cap_kwh": 500,
    "P_rated_kw": 250,
    "eta_ch": 0.95,
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  }
}