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