Proceedings of the International Renewable Energy Storage Conference (IRES 2022)

Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System

Authors
Ronny Gelleschus1, *, Thilo Bocklisch1
1Technische Universität Dresden, Chair of Energy Storage Systems, Dresden, Germany
*Corresponding author. Email: ronny.gelleschus@tu-dresden.de
Corresponding Author
Ronny Gelleschus
Available Online 25 May 2023.
DOI
10.2991/978-94-6463-156-2_13How to use a DOI?
Keywords
energy management; model predictive control; PV battery energy storage system; heat pump; modeling
Abstract

Recent research has shown that model predictive control (MPC) is a practical tool for the realization of an intelligent single- or multi-use energy management for both single and hybrid energy storage systems. Based on a system model and forecasts of external influences, such a controller will find the supposedly optimum decision to take in the immediate future. However, this decision will only be optimal for the given forecast and model. The inevitable model and forecast uncertainties may lead to decisions that are mathematically infeasible. Usually, underlying control loops ensure system stability and safety. However, uncertainties can be detrimental to the performance of the MPC, especially in multi-use applications, which have been shown to be preferable in practice due to a more economical usage of the storage devices.

For this study, the authors carried out various analyses on the impact of both model and forecast uncertainties on the performance of the MPC in the case of a PV-Battery-Heat Pump-Heat Storage system in a single-family house providing self-consumption optimization and grid relief. Concerning the impact of model uncertainties, the use case was simulated repeatedly, varying both structure (linear and quadratic) and parameters of the optimization model. The impact of forecast uncertainties was investigated by simulating with real and ideal forecasts and identifying “typical” forecast errors that led to deviations in the system’s behaviour using statistical methods. The results show that the influence of forecast uncertainties is usually higher than that of model uncertainties, but large model uncertainties may drastically alter the MPC’s usage of a hybrid energy storage system. The identification of the most influential uncertainties forms the basis for developing a more robust MPC-based energy management technique.

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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Volume Title
Proceedings of the International Renewable Energy Storage Conference (IRES 2022)
Series
Atlantis Highlights in Engineering
Publication Date
25 May 2023
ISBN
10.2991/978-94-6463-156-2_13
ISSN
2589-4943
DOI
10.2991/978-94-6463-156-2_13How to use a DOI?
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.

Cite this article

TY  - CONF
AU  - Ronny Gelleschus
AU  - Thilo Bocklisch
PY  - 2023
DA  - 2023/05/25
TI  - Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System
BT  - Proceedings of the International Renewable Energy Storage  Conference (IRES 2022)
PB  - Atlantis Press
SP  - 162
EP  - 192
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-156-2_13
DO  - 10.2991/978-94-6463-156-2_13
ID  - Gelleschus2023
ER  -