TRNSYS-AgentControl: A Python-based framework for agent-driven supervisory control workflows in TRNSYS
Lopullinen julkaistu versio - 1.45 MB
Haddad, M., Asadi, S., & Lü, X. (2026). TRNSYS-AgentControl: A Python-based framework for agent-driven supervisory control workflows in TRNSYS. SoftwareX, 35, 102759. https://doi.org/10.1016/j.softx.2026.102759
© 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Pysyvä osoite
Kuvaus
This software provides a Python-based workflow for agent-driven supervisory control in TRNSYS. It supports baseline data preparation from TRNSYS-exported datasets, control-environment construction, external agent training, and runtime inference through the TRNSYS Python interface. The framework is intended for researchers and engineers performing energy simulation and analysis in TRNSYS, enabling agent-based optimization in place of conventional rule-based supervisory logic while remaining configurable for project-specific states, actions, rewards, and operational constraints. Although the implementation demonstrates a Deep Q-Network (DQN) controller for building-scale photovoltaic-battery energy management, the workflow is not restricted to a single algorithm and can be extended to Python-based decision agents.
Emojulkaisu
ISBN
ISSN
2352-7110
Aihealue
Kausijulkaisu
SoftwareX|35
OKM-julkaisutyyppi
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä (vertaisarvioitu)