Title Estimacija i prediktivno upravljanje baterijom u mikromreži
Title (english) Estimation and predictive control of a battery in a microgrid
Author Goran Kujundžić MBZ: -333751
Mentor Mario Vašak (mentor)
Committee member Mario Vašak (član povjerenstva)
Granter University of Zagreb Faculty of Electrical Engineering and Computing (Department of Control and Computer Engineering) Zagreb
Defense date and country 2017, Croatia
Scientific / art field, discipline and subdiscipline TECHNICAL SCIENCES Electrical Engineering Automation and Robotics
Universal decimal classification (UDC ) 621.3 - Electrical engineering
Abstract Elektrokemijske baterije otvaraju velike mogućnosti u mikromrežama s obzirom na optimizaciju troškova električne energije uz uvjet da se striktno pridržava planiranog profila energije koju je potrebno razmijeniti između baterijskog sustava upravljanja i ostalih elemenata mikromreže. Ventilom regulirane olovne (engl. Valve-Regulated Lead-Acid - VRLA) baterije gotovo su potisnule iz uporabe otvorene olovne baterije i dobile su veliku ulogu u mikromrežama i sustavima napajanja u komunikacijama.
... More Odabir pravilnog načina punjenja i pražnjenja ovog tipa baterija jako je važan aspekt kako bi se ekonomski opravdala njihova ugradnja, minimizirali degradacijski učinci unutar njih, te kako bi imale životni vijek kao što ga je proizvođač deklarirao. Kako bi se ispravno upravljalo punjenjem i pražnjenjem baterija, važno je točno odrediti vrijednosti njihovih stanja i parametara. U doktorskom radu prvo je provedena združena estimacija baterijskih stanja i parametara Kalmanovim filtrom sa sigma točkama (eng. Sigma-Point Kalman Filter – SPKF), a pritom je proveden predidentifikacijski eksperiment za određivanje parametara. Nakon toga, obavljena je združena estimacija stanja i parametara SPKF-om uz korištenje isključivo tvorničkih podataka iz kataloga proizvođača. Eksperimentlna ispitivanja provedena su na VRLA baterijskom slogu nominalnog napona 48 V. Nakon provedene združene estimacije, napravljen je algoritam punjenja baterija korištenjem modelskog prediktivnog upravljanja gdje su kao ograničenja korišteni gornja naponska granica punjenja, maksimalna temperatura i/ili maksimalni porast temperature u odnosu na temperaturu okoline, maksimalna struja punjenja baterije i maksimalna vrijednost stanja napunjenosti. Cilj je predloženog algoritma je što prije potpuno napuniti VRLA baterijski slog, a da se ne prekrše ograničenja njegovih varijabli dana od proizvođača. U doktorskom radu analizirana je i primjena sustava za pohranu električne energije tj. baterija u mikromreži. Baterijski sustav upravljanja jedan je od podređenih sustava upravljanja mikromrežom. Optimizacija tokova energije na razini mikromreže zadaje energiju prema baterijskom sustavu upravljanja. Prvo je obavljena simulacijska usporedba triju različitih pristupa rada baterijskog sustava upravljanja (konstantnom strujom, konstantnom snagom i optimalnom strujom). Potom je razvijen algoritam optimalnog upravljanja baterijom u mikromreži s obzirom na zadanu energiju koju je potrebno razmijeniti između mikromreže i baterije. Unutar algoritma koriste se sva ograničenja struja, napona i stanja napunjenosti baterije dana od proizvođača baterija. Nakon izlaganja metode za rješavanje postavljenog optimizacijskog problema, provedena je analiza rada predloženog algoritma pri upravljanju u zatvorenoj upravljačkoj petlji za punjenje i pražnjenje VRLA baterijskog sloga. Učinkovitost pristupa te mogućnost stvarnovremene implementacije demonstrirani su simulacijski i eksperimentalno. Kroz cjelokupnu disertaciju koristi se hibridni električni model korištenih VRLA baterijskih svežnjeva kao najprecizniji od svih električkih modela baterija. Less
Abstract (english) Electrochemical batteries open possibilities for cost optimization in microgrids and electricity distribution grids as long as the planned energy exchange profile between the battery system and the remaining grid is strictly adhered to. The valve-regulated lead-acid (VRLA) batteries have almost suppressed out of use the flooded lead-acid batteries and got an important role in microgrids and power supply systems in telecommunications. Choosing the proper charging and discharging methods for
... More this type of batteries is a very important aspect to economically justify their installation, minimize the degradation effects inside them, and to have their lifetime as declared by the manufacturer. In order to properly control the charging and discharging of the batteries, it is important to accurately determine the values of their states and parameters. Firstly, in the doctoral thesis the joint estimation of battery states and parameters using the Sigma-point Kalman filter (SPKF) is preformed where the pre-identification experiment was carried out for parameter identification. After that, joint estimation of battery states and parameters is performed where the initial states and parameters for SPKF algorithm are calculated from the manufacturer data sheet of the battery. The experimental tests are performed using a 48 V VRLA battery stack. After the joint estimation is preformed, a control algorithm for battery charging using model predictive control is created where the upper threshold voltage level, the maximum battery temperature and/or the maximum battery temperature increase compared to the ambient temperature, the maximum charge current and the maximum state of charge are used as constraints. The main objective of the proposed algorithm is to fully charge the VRLA battery stack as fast as possible without violating constraints on its variables provided by the manufacturer. In the doctoral thesis the application of the energy storage systems i.e. the batteries in microgrid is also analyzed. The battery management system is one of the subordinated systems to the microgrid energy flow optimization. The energy flow optimization yields an energy flow command towards the subordinated battery management system. Firstly, the approaches of the optimal battery current, constant current and constant power to the battery management system operation are compared by simulations. Then the battery management procedure based on optimal control paradigm for efficient adherence to the issued energy exchange commands is developed. The proposed battery management system retains the states and inputs of the batteries within the longevity constraints provided by the manufacturer in order to reduce their degradation effects and prolong their lifetime. After presenting the method for solving the posed optimization problem, its application within a closed-loop feedback control system for charging and discharging of the VRLA battery stack is carried out. The effectiveness of the approach and the feasibility of real-time implementation are demonstrated both in simulations and experimentally. Throughout the thesis the hybrid electrical model, which is the most precise of all battery electrical models, is used for modelling the behavior of the considered VRLA battery stacks. Less
Keywords
ventilom regulirana olovna baterija
stanje napunjenosti
napon praznog hoda
hibridni električni model
združena estimacija
Kalmanov filtar
modelsko prediktivno upravljanje
punjenje
ograničenja
baterijski sustav upravljanja
optimizacija tokova energije u mikromreži
pridržavanje naredbe o zadanoj razmjeni energije u zadanom vremenu
stvarnovremena implementacija
Keywords (english)
valve-regulated lead-acid battery
state-of-charge
open-circuit voltage
hybrid electrical model
joint estimation
Kalman filter
model predictive control
charging
constraints
battery management system
energy flow optimization in microgrid
adherence to command of energy exchange in time
real-time implementation
Language croatian
URN:NBN urn:nbn:hr:168:014116
Study programme Title: Electrical Engineering and Computing Study programme type: university Study level: postgraduate Academic / professional title: Doktor znanosti elektrotehnike i računarstva (Doktor znanosti elektrotehnike i računarstva)
Type of resource Text
Extent 194 str. ; 30 cm
File origin Born digital
Access conditions Closed access
Terms of use
Created on 2019-04-04 12:44:22