Adaptive Fuzzy Logic Controller Based Energy Management for a Stand-alone PV Hybrid System with Battery and Hydrogen Storage Path

DOI

10.2991/978-94-6463-156-2_33How to use a DOI?

Keywords

photovoltaics (PV); stand-alone hybrid system; hybrid energy storage system (HESS); adaptive energy management; fuzzy logic controller (FLC); particle swarm optimization (PSO)

Abstract

The paper describes a novel adaptive fuzzy logic controller based energy management concept (A-FLC-EM) for a stand-alone photovoltaic (PV) hybrid system with battery and hydrogen storage path. The reference application is a single family home. The basic idea is to switch and optimally adjust the energy management parameters according to identified changes of distinct long-term energy supply and/or demand situations. Key elements of the offline learning phase are the analysis of the energy time series and the automatic determination of distinct energy situations on the basis of a segmentation algorithm and a vector of suitable statistical features calculated for a short-term, sliding observation window. A bottom-up approach is used, ranking and selecting statistical features that are particularly good at distinguishing certain long-term energy situations. The selected features form the basis for a clustering algorithm to detect and describe distinct energy situations. For each energy situation, the calculation of optimal energy management parameters is performed for a training data set employing particle swarm optimization (PSO). The performance of the novel A-FLC-EM is demonstrated compared to a conventional fuzzy logic controller based energy management (FLC-EM) with an all-year fixed parameter setting. Qualitative and quantitative improvements as well as further challenges are discussed.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Konrad Warner
AU  - Thilo Bocklisch
PY  - 2023
DA  - 2023/05/25
TI  - Adaptive Fuzzy Logic Controller Based Energy Management for a Stand-alone PV Hybrid System with Battery and Hydrogen Storage Path
BT  - Proceedings of the International Renewable Energy Storage  Conference (IRES 2022)
PB  - Atlantis Press
SP  - 511
EP  - 526
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-156-2_33
DO  - 10.2991/978-94-6463-156-2_33
ID  - Warner2023
ER  -