Model predictive control of battery systems in a microgrid

doctoral thesis

• Title (croatian): Modelsko prediktivno upravljanje baterijskim sustavima u mikromreži
• Author: Mateja Car
• Mentor: Vinko Lešić (mentor)
• Committee member: Mario Vašak (predsjednik povjerenstva)
• Committee member: Anita Banjac (član povjerenstva)
• Committee member: Danijel Pavković (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-12-22, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering
• Universal decimal classification (UDC): 621.3 - Electrical engineering

Abstract

The research is focused on the control of heterogeneous battery storage systems by taking into account the chemical processes inside a battery which are reflected in variable battery efficiency and consequently, battery longevity. This is motivated by economic benefits that stem from more efficient control of microgrid components in microgrid optimal power flow problems. The control objective is formulated as a model predictive control problem and decomposed into two levels. The higher level is in charge of microgrid optimal power flows and is based on a high level of abstraction model of storage system. The lower level is based on a detailed storage system model and is in charge of delivering the demanded power profiles in the most efficient way. The battery converter model includes power-dependent efficiency in the form of look-up-tables and the internal resistor of the battery model is a function of battery states. The parameters are obtained by model-based identification techniques.

Abstract (croatian)

Istraživanje se fokusira na upravljanje heterogenim baterijskim sustavima za pohranu uzimajući u obzir kemijske procese unutar baterija koji se odražavaju u obliku promjenjive učinkovitosti, a posljedično i dugotrajnosti sustava. Istraživanje je motivirano ekonomskom korišćuu koja proizlazi iz efikasnijeg upravljanja mikromrežnim komponentama prilikom rješavanja problema optimalnih tokova snaga u mikromreži. Modelski prediktivni upravljački problem rastavljen je na dvije razine. Viša razina upravlja tokovima snaga u mikromreži, a temelji se na pojednostavljenom modelu baterijskog sustava. Niža razina temelji se na detaljnom modelu, a zadužena je za ostvarivanje traženih profila snaga na najefikasniji način. Model pretvarača baterije uključuje promjenjivu efikasnost ovisnu o snazi, a unutarnji otpor baterije funkcija je trenutnog stanja baterije. Vrijednosti parametara dobivaju se metodama identifikacije temeljenim na modelu.

• Keywords: battery storage system; microgrid; two level control problem; optimal power flow; efficient battery charging and discharging; microgrid components; grid converter control; variable efficiency models; parameter identification; model predictive control
• Keywords (croatian): baterijski spremnici nenergije; mikromreža; upravljački problem na dvije razine; optimalni tokovi snaga; efikasno punjenje i praˇznjenje baterija; komponente mikromreže; upravljanje mrežnim pretvaračem; modeli s promjenjivom efikasnošću; identifikacija parametara; modelsko prediktivno upravljanje
• Language: english
• URN:NBN: urn:nbn:hr:168:508141
• Promotion: 2024
• Study programme: Title: Doctoral study programme "Electrical Engineering and Computing"; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, po-dručje tehničkih znanosti (doktor/doktorica znanosti, po-dručje tehničkih znanosti)
• Type of resource: Text
• Extent: ix, 119 str. : graf.prikazi
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-02-28 08:42:03