Analysis of Battery Storage Usage of Heuristic Energy Flow Controllers

DOI

10.2991/ahe.k.220301.001How to use a DOI?

Keywords

Energy Management System; Genetic Programming; Symbolic Regression

Abstract

Due to the increasing usage of renewable energy sources like photovoltaic (PV) systems in the private sector and their fluctuations in production, energy management systems (EMS) are becoming more and more important. As such system use the produced energy as efficiently as possible, they also have an influence on a battery storage which is often installed together with the PV system. Nowadays batteries are already durable and cost efficient, but the possible negative effects an EMS might have on its usage and lifetime still need to be taken into account and be aware of. This is why this work analyses the battery usage of heuristic energy management controllers in detail and compares them to two existing energy management systems. It is shown that the heuristic energy management controllers are able to reduce the number of used battery cycles and therefore also the charged and discharged energy remarkable compared to the rule-based self-consumption optimization and the linear MPC, which also leads to a prolongation of the battery lifetime.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Kathrin Kefer
AU  - Patrick Kefer
AU  - Markus Stöger
AU  - Bernd Hofer
AU  - Michael Affenzeller
AU  - Stephan Winkler
PY  - 2022
DA  - 2022/03/03
TI  - Analysis of Battery Storage Usage of Heuristic Energy Flow Controllers
BT  - Proceedings of the International Renewable Energy Storage Conference 2021 (IRES 2021)
PB  - Atlantis Press
SP  - 1
EP  - 7
SN  - 2589-4943
UR  - https://doi.org/10.2991/ahe.k.220301.001
DO  - 10.2991/ahe.k.220301.001
ID  - Kefer2022
ER  -