{"id":{"repo_id":"tu-berlin","oai_identifier":"oai:depositonce.tu-berlin.de:11303/26690"},"canonical_url":"https://search.dev.ndltd.org/etd/tu-berlin/oai:depositonce.tu-berlin.de:11303/26690","repository":{"repo_id":"tu-berlin","name":"Technische Universität Berlin","base_url":"https://api-depositonce.tu-berlin.de/server/oai/request"},"display":{"title":"Optimizing battery swapping stations for electric vehicles and power system integration","abstract":"The rapid expansion of electric vehicle (EV) adoption has introduced new challenges in power system infrastructure and energy management. Issues like long waiting times at charging stations and battery degradation due to fast charging are some of the major barriers to widespread EV deployment. Battery swapping stations (BSS) arise as a promising alternative by enabling quick battery replacements. Moreover, BSS has a critical role in balancing power grids through ancillary services. This thesis presents a comprehensive framework for the optimization of BSS operation by focusing on three key aspects: scheduling of battery charging–discharging operations, optimal placement and sizing of BSS, and integration of mobile battery swapping stations (MSS). The first study investigates the optimal location and capacity of a BSS in a microgrid environment to maximize revenue while supporting grid stability. Using real-world public transportation data from Berlin, Germany for an analytical demand estimation approach, an optimization model determines the optimal BSS location and its impact on ancillary service provision. The second study extends this analysis by developing an optimal scheduling framework for multiple BSS that serve EVs and electric bus (EB) fleets. It introduces the concept of MSS, a dynamic and mobile alternative that strategically distributes battery swaps based on demand patterns in different regions. The results demonstrate that BSS, coupled with MSS, improve grid interaction efficiency and financial sustainability. The third study formulates a mixed-integer programming model to optimize the operations of a central BSS and its affiliated MSS units in an urban environment. The model optimally allocates resources to maximize revenue from swap operations of MSS and energy sales of BSS to the grid. Developed model also solves the problem of MSS distribution to urban areas within the scope of demand estimation. The findings highlight the financial potential of BSS-MSS infrastructure offers a dual benefit of efficient EV adoption and grid support. Overall, this thesis provides a strategic approach to BSS planning and operation, bridging the gap between EV infrastructure and power grid economics. With real-world data and optimization techniques, it offers an applicable pathway for improving EV accessibility, grid reliability, and financial sustainability in the evolving energy and mobility landscape.","abstract_html":"The rapid expansion of electric vehicle (EV) adoption has introduced new challenges in power system infrastructure and energy management. Issues like long waiting times at charging stations and battery degradation due to fast charging are some of the major barriers to widespread EV deployment. Battery swapping stations (BSS) arise as a promising alternative by enabling quick battery replacements. Moreover, BSS has a critical role in balancing power grids through ancillary services. This thesis presents a comprehensive framework for the optimization of BSS operation by focusing on three key aspects: scheduling of battery charging–discharging operations, optimal placement and sizing of BSS, and integration of mobile battery swapping stations (MSS). The first study investigates the optimal location and capacity of a BSS in a microgrid environment to maximize revenue while supporting grid stability. Using real-world public transportation data from Berlin, Germany for an analytical demand estimation approach, an optimization model determines the optimal BSS location and its impact on ancillary service provision. The second study extends this analysis by developing an optimal scheduling framework for multiple BSS that serve EVs and electric bus (EB) fleets. It introduces the concept of MSS, a dynamic and mobile alternative that strategically distributes battery swaps based on demand patterns in different regions. The results demonstrate that BSS, coupled with MSS, improve grid interaction efficiency and financial sustainability. The third study formulates a mixed-integer programming model to optimize the operations of a central BSS and its affiliated MSS units in an urban environment. The model optimally allocates resources to maximize revenue from swap operations of MSS and energy sales of BSS to the grid. Developed model also solves the problem of MSS distribution to urban areas within the scope of demand estimation. The findings highlight the financial potential of BSS-MSS infrastructure offers a dual benefit of efficient EV adoption and grid support. Overall, this thesis provides a strategic approach to BSS planning and operation, bridging the gap between EV infrastructure and power grid economics. With real-world data and optimization techniques, it offers an applicable pathway for improving EV accessibility, grid reliability, and financial sustainability in the evolving energy and mobility landscape.","abstract_has_math":false,"creators":["Kocer, Mustafa Cagatay"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Albayrak, Sahin"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-07-27T21:28:37Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":["https://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://doi.org/10.14279/depositonce-25520"],"render_values":[{"text":"https://doi.org/10.14279/depositonce-25520","href":"https://doi.org/10.14279/depositonce-25520","code":true}]}]},"links":{"outbound_url":"https://depositonce.tu-berlin.de/handle/11303/26690","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Albayrak, Sahin"]},{"key":"dc:creator","label":"Author","values":["Kocer, Mustafa Cagatay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-03-27T13:21:46Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-03-27T13:21:46Z"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://depositonce.tu-berlin.de/handle/11303/26690","https://doi.org/10.14279/depositonce-25520"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The rapid expansion of electric vehicle (EV) adoption has introduced new challenges in power system infrastructure and energy management. Issues like long waiting times at charging stations and battery degradation due to fast charging are some of the major barriers to widespread EV deployment. Battery swapping stations (BSS) arise as a promising alternative by enabling quick battery replacements. Moreover, BSS has a critical role in balancing power grids through ancillary services. This thesis presents a comprehensive framework for the optimization of BSS operation by focusing on three key aspects: scheduling of battery charging–discharging operations, optimal placement and sizing of BSS, and integration of mobile battery swapping stations (MSS). The first study investigates the optimal location and capacity of a BSS in a microgrid environment to maximize revenue while supporting grid stability. Using real-world public transportation data from Berlin, Germany for an analytical demand estimation approach, an optimization model determines the optimal BSS location and its impact on ancillary service provision. The second study extends this analysis by developing an optimal scheduling framework for multiple BSS that serve EVs and electric bus (EB) fleets. It introduces the concept of MSS, a dynamic and mobile alternative that strategically distributes battery swaps based on demand patterns in different regions. The results demonstrate that BSS, coupled with MSS, improve grid interaction efficiency and financial sustainability. The third study formulates a mixed-integer programming model to optimize the operations of a central BSS and its affiliated MSS units in an urban environment. The model optimally allocates resources to maximize revenue from swap operations of MSS and energy sales of BSS to the grid. Developed model also solves the problem of MSS distribution to urban areas within the scope of demand estimation. The findings highlight the financial potential of BSS-MSS infrastructure offers a dual benefit of efficient EV adoption and grid support. Overall, this thesis provides a strategic approach to BSS planning and operation, bridging the gap between EV infrastructure and power grid economics. With real-world data and optimization techniques, it offers an applicable pathway for improving EV accessibility, grid reliability, and financial sustainability in the evolving energy and mobility landscape.","Die schnelle Verbreitung von Elektrofahrzeugen (EV) stellt neue Herausforderungen für Stromnetze und Energiemanagement dar. Lange Ladezeiten und Batteriedegradation durch Schnellladen zählen zu den größten Hürden. Batteriewechselstationen (BSS) bieten eine vielversprechende Alternative mit schnellem Batteriewechsel und unterstützen zudem das Stromnetz durch Hilfsdienste. In dieser Arbeit wird ein umfassender Rahmen für die Optimierung des Betriebs von BSS vorgestellt, der sich auf drei Schlüsselaspekte konzentriert: die Planung der Lade- und Entladevorgänge von Batterien, die optimale Platzierung und Dimensionierung von BSS und die Integration von mobilen Batteriewechselstationen (MSS). Die erste Studie untersucht den optimalen Standort und die Kapazität eines BSS in einer Microgrid-Umgebung, um die Einnahmen zu maximieren und gleichzeitig die Netzstabilität zu unterstützen. Unter Verwendung von realen Daten des öffentlichen Nahverkehrs in Berlin, Deutschland, für einen analytischen Ansatz zur Abschätzung der Nachfrage, bestimmt ein Optimierungsmodell den optimalen Standort von BSS und seine Auswirkungen auf die Bereitstellung von Hilfsdiensten. Die zweite Studie erweitert diese Analyse durch die Entwicklung eines optimalen Planungsrahmens für mehrere BSS, die EVs und Elektrobusflotten (EB) bedienen. Sie führt das Konzept der MSS ein, eine dynamische und mobile Alternative, die den Batteriewechsel strategisch auf der Grundlage von Nachfragemustern in verschiedenen Regionen verteilt. Die Ergebnisse zeigen, dass BSS in Verbindung mit MSS die Effizienz der Netzinteraktion und die finanzielle Nachhaltigkeit verbessern. Die dritte Studie formuliert ein gemischt-ganzzahliges Programmierungsmodell zur Optimierung des Betriebs eines zentralen BSS und seiner angeschlossenen MSS-Einheiten in einem städtischen Umfeld. Das Modell weist die Ressourcen optimal zu, um die Einnahmen aus dem Tauschbetrieb der MSS und dem Energieverkauf der BSS an das Netz zu maximieren. Das entwickelte Modell löst auch das Problem der Verteilung von MSS in städtischen Gebieten im Rahmen der Bedarfsabschätzung. Die Ergebnisse unterstreichen das finanzielle Potenzial der BSS-MSS-Infrastruktur, um einen doppelten Nutzen in Bezug auf die effiziente Einführung von EV und die Netzunterstützung zu bieten. Insgesamt bietet diese Arbeit einen strategischen Ansatz für die Planung und den Betrieb von BSS und überbrückt die Lücke zwischen der EV-Infrastruktur und der Wirtschaftlichkeit des Stromnetzes. Mithilfe von realen Daten und Optimierungstechniken bietet sie einen anwendbaren Weg zur Verbesserung der EV-Zugänglichkeit, der Netzzuverlässigkeit und der finanziellen Nachhaltigkeit in der sich entwickelnden Energie- und Mobilitätslandschaft."]},{"key":"dc:title","label":"Title","values":["Optimizing battery swapping stations for electric vehicles and power system integration"]}]}],"canonical_facts":{"dc:contributor.advisor":["Albayrak, Sahin"],"dc:creator":["Kocer, Mustafa Cagatay"],"dc:date.accessioned":["2026-03-27T13:21:46Z"],"dc:date.available":["2026-03-27T13:21:46Z"],"dc:date.issued":["2026"],"dc:description.abstract":["The rapid expansion of electric vehicle (EV) adoption has introduced new challenges in power system infrastructure and energy management. Issues like long waiting times at charging stations and battery degradation due to fast charging are some of the major barriers to widespread EV deployment. Battery swapping stations (BSS) arise as a promising alternative by enabling quick battery replacements. Moreover, BSS has a critical role in balancing power grids through ancillary services. This thesis presents a comprehensive framework for the optimization of BSS operation by focusing on three key aspects: scheduling of battery charging–discharging operations, optimal placement and sizing of BSS, and integration of mobile battery swapping stations (MSS). The first study investigates the optimal location and capacity of a BSS in a microgrid environment to maximize revenue while supporting grid stability. Using real-world public transportation data from Berlin, Germany for an analytical demand estimation approach, an optimization model determines the optimal BSS location and its impact on ancillary service provision. The second study extends this analysis by developing an optimal scheduling framework for multiple BSS that serve EVs and electric bus (EB) fleets. It introduces the concept of MSS, a dynamic and mobile alternative that strategically distributes battery swaps based on demand patterns in different regions. The results demonstrate that BSS, coupled with MSS, improve grid interaction efficiency and financial sustainability. The third study formulates a mixed-integer programming model to optimize the operations of a central BSS and its affiliated MSS units in an urban environment. The model optimally allocates resources to maximize revenue from swap operations of MSS and energy sales of BSS to the grid. Developed model also solves the problem of MSS distribution to urban areas within the scope of demand estimation. The findings highlight the financial potential of BSS-MSS infrastructure offers a dual benefit of efficient EV adoption and grid support. Overall, this thesis provides a strategic approach to BSS planning and operation, bridging the gap between EV infrastructure and power grid economics. With real-world data and optimization techniques, it offers an applicable pathway for improving EV accessibility, grid reliability, and financial sustainability in the evolving energy and mobility landscape.","Die schnelle Verbreitung von Elektrofahrzeugen (EV) stellt neue Herausforderungen für Stromnetze und Energiemanagement dar. Lange Ladezeiten und Batteriedegradation durch Schnellladen zählen zu den größten Hürden. Batteriewechselstationen (BSS) bieten eine vielversprechende Alternative mit schnellem Batteriewechsel und unterstützen zudem das Stromnetz durch Hilfsdienste. In dieser Arbeit wird ein umfassender Rahmen für die Optimierung des Betriebs von BSS vorgestellt, der sich auf drei Schlüsselaspekte konzentriert: die Planung der Lade- und Entladevorgänge von Batterien, die optimale Platzierung und Dimensionierung von BSS und die Integration von mobilen Batteriewechselstationen (MSS). Die erste Studie untersucht den optimalen Standort und die Kapazität eines BSS in einer Microgrid-Umgebung, um die Einnahmen zu maximieren und gleichzeitig die Netzstabilität zu unterstützen. Unter Verwendung von realen Daten des öffentlichen Nahverkehrs in Berlin, Deutschland, für einen analytischen Ansatz zur Abschätzung der Nachfrage, bestimmt ein Optimierungsmodell den optimalen Standort von BSS und seine Auswirkungen auf die Bereitstellung von Hilfsdiensten. Die zweite Studie erweitert diese Analyse durch die Entwicklung eines optimalen Planungsrahmens für mehrere BSS, die EVs und Elektrobusflotten (EB) bedienen. Sie führt das Konzept der MSS ein, eine dynamische und mobile Alternative, die den Batteriewechsel strategisch auf der Grundlage von Nachfragemustern in verschiedenen Regionen verteilt. Die Ergebnisse zeigen, dass BSS in Verbindung mit MSS die Effizienz der Netzinteraktion und die finanzielle Nachhaltigkeit verbessern. Die dritte Studie formuliert ein gemischt-ganzzahliges Programmierungsmodell zur Optimierung des Betriebs eines zentralen BSS und seiner angeschlossenen MSS-Einheiten in einem städtischen Umfeld. Das Modell weist die Ressourcen optimal zu, um die Einnahmen aus dem Tauschbetrieb der MSS und dem Energieverkauf der BSS an das Netz zu maximieren. Das entwickelte Modell löst auch das Problem der Verteilung von MSS in städtischen Gebieten im Rahmen der Bedarfsabschätzung. Die Ergebnisse unterstreichen das finanzielle Potenzial der BSS-MSS-Infrastruktur, um einen doppelten Nutzen in Bezug auf die effiziente Einführung von EV und die Netzunterstützung zu bieten. Insgesamt bietet diese Arbeit einen strategischen Ansatz für die Planung und den Betrieb von BSS und überbrückt die Lücke zwischen der EV-Infrastruktur und der Wirtschaftlichkeit des Stromnetzes. Mithilfe von realen Daten und Optimierungstechniken bietet sie einen anwendbaren Weg zur Verbesserung der EV-Zugänglichkeit, der Netzzuverlässigkeit und der finanziellen Nachhaltigkeit in der sich entwickelnden Energie- und Mobilitätslandschaft."],"dc:identifier.uri":["https://depositonce.tu-berlin.de/handle/11303/26690","https://doi.org/10.14279/depositonce-25520"],"dc:language.iso":["en"],"dc:rights.uri":["https://creativecommons.org/licenses/by/4.0/"],"dc:title":["Optimizing battery swapping stations for electric vehicles and power system integration"],"dc:type":["Doctoral Thesis"]},"updated_at":"2026-07-27T21:28:37Z"}