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Averaging favors MPC: How typical evaluation setups overstate MPC performance for residential battery scheduling

Pinter, Janik ORCID iD icon 1; Beichter, Maximilian ORCID iD icon 1; Mikut, Ralf ORCID iD icon 1; Zahn, Frederik 1; Hagenmeyer, Veit ORCID iD icon 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

Residential prosumers with PV-battery systems increasingly manage their electricity exchange with the power grid to minimize costs. This study investigates the performance of Model Predictive Control (MPC) and Rule-Based Control (RBC) under 15/30/60 min averaging commonly used in research, when Net Billing and battery degradation are considered. We simulate five consecutive months for 15 buildings in northern Germany, generating costs at up to 1-min resolution while scheduling at 15/30/60 min. We find that time-averaged evaluations make MPC look consistently better than RBC, yet when costs are recomputed at minute-level ground-truth, the reported advantage shrinks by 69% on average for hourly schedulers. For individual buildings, the finer evaluation can reverse conclusions, and simple RBC can achieve lower total costs than an MPC with perfect foresight. These findings caution against drawing conclusions from coarse averages and show how a fair assessment of battery scheduling approaches can be obtained.


Verlagsausgabe §
DOI: 10.5445/IR/1000195884
Veröffentlicht am 04.08.2026
Originalveröffentlichung
DOI: 10.1016/j.epsr.2026.113517
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 03.2027
Sprache Englisch
Identifikator ISSN: 0378-7796
KITopen-ID: 1000195884
HGF-Programm 37.12.01 (POF IV, LK 01) Digitalization & System Technology for Flexibility Solutions
Erschienen in Electric Power Systems Research
Verlag Elsevier
Band 264
Seiten 113517
Vorab online veröffentlicht am 23.07.2026
Nachgewiesen in OpenAlex
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