Title
Software system for multi-criteria planning and management of hybrid microgrids
Creator
Batić, Marko Č., 1985- 14750311
Copyright date
2019
Object Links
Select license
Autorstvo-Nekomercijalno 3.0 Srbija (CC BY-NC 3.0)
License description
Dozvoljavate umnožavanje, distribuciju i javno saopštavanje dela, i prerade, ako se navede ime autora na način odredjen od strane autora ili davaoca licence. Ova licenca ne dozvoljava komercijalnu upotrebu dela. Osnovni opis Licence: http://creativecommons.org/licenses/by-nc/3.0/rs/deed.sr_LATN Sadržaj ugovora u celini: http://creativecommons.org/licenses/by-nc/3.0/rs/legalcode.sr-Latn
Language
English
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 7. 3. 2019.
Other responsibilities
mentor
Vraneš, Sanja. 13801319
član komisije
Nikolić, Boško, 1972- 12843879
član komisije
Tomašević, Nikola M., 1983- 18550887
član komisije
Tomašević, Milo, 1957- 12493159
član komisije
Đurišić, Željko, 1972- 12836711
Academic Expertise
Tehničko-tehnološke nauke
University
Univerzitet u Beogradu
Faculty
Elektrotehnički fakultet
Alternative title
Softverski sistem za više-kriterijumsko planiranje i upravljanje hibridnom mikro-mrežom
Publisher
[M. Batić]
Format
III, 184 listova
description
Electrical and Computer Engineering - Computer Engineering and Informatics / Elektrotehnika i računarstvo - Računarska tehnika i informatika
Abstract (en)
Efficient operation and management of energy systems in the context of increasing
penetration of distributed resources and renewable energy sources combined with energy
storages, gird-tied configurations and deregulated energy market context pose a complex
energy-dispatching problem, the one conventional energy management systems are not
able to cope with. This complexity also hinders faster adoption of renewables and
aggravates their cost effectiveness. This thesis proposes an innovative software system,
which brings advanced microgrid planning, and operation algorithms while leveraging
existing supervision and control systems to collect data and information from the field
level but also to forward desired control action. Moreover, the thesis also proposes
innovative approach for seamless integration with diverse, legacy, ICT systems thus
contributing to system large-scale applicability. Following is a breakdown of concrete
results and outputs with emphasis on their specific advancements comparted to existing
approaches. Similarly, to existing approaches the underlying methodology of microgrid
planning tool considers hybrid energy infrastructures with both conventional and
renewable energy sources, converters and storages, featured by their mathematical
representation. However, proposed methodology advances existing tools and planning
approaches by simultaneously considering both electric and thermal energy domain, by
considering both grid-tied and isolated deployment scenarios and, foremost, by
leveraging demand side flexibility for optimized dimensioning of energy assets.
Moreover, multi-criteria decision-making algorithms are used to rank multiple feasible
planning alternatives. For the purpose of determining expected energy demand profile, an
approach to leverage user habits and behaviour together with characteristics of existing
energy infrastructure, rather than building physics, was developed.
The developed microgrid management tool aimed at providing additional intelligence to
existing supervision and control systems resulting in the cost savings typically exceeding
10%, as demonstrated in a real world use case, at the cost of ICT system retrofit. The
achieved level of cost savings is comparable to those of retrofit of energy assets, which
require considerable higher investments. The underlying microgrid management
methodology complements existing approaches that optimize energy imports for a desired
demand and available storages, by introducing appliance-level demand response actions,
which can be immediately translated into control actions. Lastly, an ontology-based
facility model of complex facilities and corresponding energy infrastructure was
developed together with unified messaging format to enable semantic interoperability of
existing diverse, legacy, supervision and control systems, which use proprietary
communication protocols. By employing semantic web technologies and leveraging
existing models and standards, the developed model stores contextual knowledge about
the entire facility, and not just energy infrastructure, thus enables enhancement of energy
management algorithms and allowing for application of dynamic energy efficiency
measures.
Abstract (sr)
Efikasno upravljanje energetskom infrastrukturom u kontekstu sve većeg udela
distribuiranih resursa i obnovljivih izvora energije u kombinaciji sa skladištima energije
postaje sve veći izazov. Kada se još ima u vidu da su ovakvi hibridni sistemi sve češće
povezani na distributivnu mrežu i da funkcionišu u kontekstu liberalnog tržišta energije,
postaje jasno zašto postojeći sistemi za upravljanje imaju sve više problema da ostvare
efikasan rad. Ova složenost upravljanja takođe otežava i bržu penetraciju obnovljivih
izvora i doprinosi nepredvidivosti po pitanju njihove ekonomičnosti. Ova teza predlaže
inovativni softverski sistem koji donosi napredne algoritme za planiranje i upravljanje
hibridnim mikro-mrežama, pri čemu se oslanja na postojeće sisteme nadzora upravljanja
za potrebe prikupljanja podataka i neophodnih informacija sa fizičkog sloja, ali i za
prosleđivanje i sprovođenje donesene kontrolne akcije. Imajući u vidu ovu vrstu
zavisnosti od postojećih sistema, jedan od doprinosa teze je bio upravo razvoj inovativnog
pristupa za jednostavnu integraciju sa postojećim IKT sistemima koji često koristite
posebne, nestandardne, protokole i mehanizme za komunikaciju. S tim u vezi, predloženo
rešenje prevazilazi potrebe za komunikacionom i semantičkom interoperabilnosti i otvara
prostor za napredno rezonovanje. U nastavku je dat kratak pregled konkretnih rezultata
kao i osnovnih doprinosa u odnosu na postojeća rešenja. Pre svega, razvijen je alat za
planiranje, odnosno dizajn, mikro-mreže koji slično postojećim pristupima razmatra
hibridne energetske infrastrukture sa konvencionalnim i obnovljivim izvorima energije,
različitim elementima za konverziju kao i skladištima energije putem odgovarajućih
matematičkih modela različite kompleksnosti. Međutim, predložena metodologija
unapređuje postojeće alate i pristupe u planiranju kroz integralno razmatranje domena
električne i toplotne energije, razmatranja kako izolovanih sistema tako i onih povezanih
na distributivnu mrežu, ali pre svega, primenom fleksibilnosti na strani potrošnje za
optimalno dimenzionisanje elemenata mikro-mreže. Pored toga, za potrebe rangiranja
višestrukog broja prihvatljivih alternativa, korišćeni su posebni algoritmi za
višekriterijumsko odlučivanje. Takođe, razvijen je inovativni model potrošnje koji ima
zadatak da utvrdi očekivani profila potrošnje energije. Predloženi model se ne naslanja
na uobičajene modele koji se zasnivaju na fizičkom modelu zgrade već se uvodi
metodologiju koja polazi od navika i zahteva samog korisnika kao i postojećih potrošača.
U okviru teze, razvijen je i alat za upravljanje mikro-mrežom koji ima za cilj nadogradnju
postojećih sistema za upravljanje. Naime, razvijeni alat je testiran u realnom okruženju
gde je ostvario prosečne uštede troškova reda 10% kroz jednostavnu, softversku,
nadgradnju postojeće upravljačke infrastrukture. Dobijeni rezultati su potpuno uporedivi
sa onima koji se dobijaju prilikom neuporedivo većih investicija koje se tiču zamene
pojedinih uređaja za neke efikasnije. Predložena metodologija, koja je implementirana u
okviru ovog alata, se konceptualno oslanja na neke od postojećih pristupa ali pravi
kvalitativni pomak u odnosu na njih jer uvodi u razmatranje upravljanje potrošnjom, i to
na nivou pojedinačnih uređaja, što dalje omogućuje direktnu primenu rezultata
optimizacije na odgovarajuće kontrolne akcije, što nije slučaj sa postojećim metodama.
Konačno, u okviru teze je razvijen i model kompleksnih objekata i njihove odgovarajuće
energetske infrastrukture kao i unificirani model za komunikaciju kako bi se omogućila
semantička interoperabilnost postojećih nadzornih i kontrolnih sistema koji često koriste
posebne, nestandardne, komunikacijske protokole. Korišćenjem tehnologija semantičkog
veba i polazeći od već postojećih modela i standarda, razvijeni model služi kao baza
znanje o čitavom sistemu, a ne samo energetskoj infrastrukturi, čime se omogućava
unapređenje algoritama za upravljanje energijom i omogućava primena dinamičkih mera
energetske efikasnosti.
Authors Key words
Energy informatics, energy management, facility data model, ontology
modelling, energy hub, demand side management, linear programming
Authors Key words
Energetska informatika, upravljanje energijom, modelovanje energetske
infrastrukture, modelovanje na bazi ontologija, energetski hab, upravljanje potrošnjom,
linerano programiranje
Classification
621.31:004.42(043.3)
Type
Tekst
Abstract (en)
Efficient operation and management of energy systems in the context of increasing
penetration of distributed resources and renewable energy sources combined with energy
storages, gird-tied configurations and deregulated energy market context pose a complex
energy-dispatching problem, the one conventional energy management systems are not
able to cope with. This complexity also hinders faster adoption of renewables and
aggravates their cost effectiveness. This thesis proposes an innovative software system,
which brings advanced microgrid planning, and operation algorithms while leveraging
existing supervision and control systems to collect data and information from the field
level but also to forward desired control action. Moreover, the thesis also proposes
innovative approach for seamless integration with diverse, legacy, ICT systems thus
contributing to system large-scale applicability. Following is a breakdown of concrete
results and outputs with emphasis on their specific advancements comparted to existing
approaches. Similarly, to existing approaches the underlying methodology of microgrid
planning tool considers hybrid energy infrastructures with both conventional and
renewable energy sources, converters and storages, featured by their mathematical
representation. However, proposed methodology advances existing tools and planning
approaches by simultaneously considering both electric and thermal energy domain, by
considering both grid-tied and isolated deployment scenarios and, foremost, by
leveraging demand side flexibility for optimized dimensioning of energy assets.
Moreover, multi-criteria decision-making algorithms are used to rank multiple feasible
planning alternatives. For the purpose of determining expected energy demand profile, an
approach to leverage user habits and behaviour together with characteristics of existing
energy infrastructure, rather than building physics, was developed.
The developed microgrid management tool aimed at providing additional intelligence to
existing supervision and control systems resulting in the cost savings typically exceeding
10%, as demonstrated in a real world use case, at the cost of ICT system retrofit. The
achieved level of cost savings is comparable to those of retrofit of energy assets, which
require considerable higher investments. The underlying microgrid management
methodology complements existing approaches that optimize energy imports for a desired
demand and available storages, by introducing appliance-level demand response actions,
which can be immediately translated into control actions. Lastly, an ontology-based
facility model of complex facilities and corresponding energy infrastructure was
developed together with unified messaging format to enable semantic interoperability of
existing diverse, legacy, supervision and control systems, which use proprietary
communication protocols. By employing semantic web technologies and leveraging
existing models and standards, the developed model stores contextual knowledge about
the entire facility, and not just energy infrastructure, thus enables enhancement of energy
management algorithms and allowing for application of dynamic energy efficiency
measures.
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