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Planning and analysing competing en-route charging stations for electric vehicles: A game-theoretic approach

Planning and analysing competing en-route charging stations for electric vehicles: A game-theoretic approach
Planning and analysing competing en-route charging stations for electric vehicles: A game-theoretic approach
En-route charging stations are required to ensure the adoption of Electric Vehicles. However, careful planning is necessary due to high cost in infrastructure and potential queues, and literature on charging station competition is scarce. To address this and similar problems, this thesis proposes a versatile game-theoretic model for investor competition, where competing firm investors aim to maximise individual net profit by choosing locations, capacities, prices and the speed of service at their firms. On the other hand, self-interested customers aim to minimise the expected cost of acquiring the service firms sell. This includes a cost to access each firm, the fee for the service and an expected cost due to congestion at the firm. In addition, extraneous competition outside the investor system is considered as an option for customers. The solution combines analytical and algorithmic techniques to obtain subgame-perfect equilibria, and enables to assess both qualitative and quantitative aspects of firm competition. The model is applied to building charging stations for Electric Vehicles, and it is shown theoretically and empirically that equilibrium charging prices deviate upward of the marginal charging cost due to the inability to satisfy charging demand immediately, even with vast improvements in charging technology. Further results show that private investors will prefer to compete on the same route, because stations on longer routes have to set lower prices at their stations and this consists a significant disadvantage. Moreover, the more drivers are willing to pay in order to save time from their journey, the more investors will increase their profits at the expense of drivers. The inclusion of price choice and extraneous competition reinforces the existence of pure strategy Nash equilibria in capacity choice, and SPE solutions are highly efficient compared to optimal firm allocations when it comes to system-wide social welfare. Last, this thesis examines subsidies to stations as incentives to expanding rapid charging stations. Results show that subsidising the purchase of charging units for stations can have a significant beneficial effect for both EV drivers and station investors. In contrast, subsidies on the energy price for stations could provide incentive to investors to reduce capacities and increase prices. Finally, it is shown how the proposed model can be used to calculate the monetary gain or loss for drivers and investors due to subsidies, and to determine optimal subsidy levels according to certain requirements.
University of Southampton
Zavvos, Efstathios
6d8f7292-47db-464b-8787-7ee854e66682
Zavvos, Efstathios
6d8f7292-47db-464b-8787-7ee854e66682
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362

Zavvos, Efstathios (2019) Planning and analysing competing en-route charging stations for electric vehicles: A game-theoretic approach. University of Southampton, Doctoral Thesis, 168pp.

Record type: Thesis (Doctoral)

Abstract

En-route charging stations are required to ensure the adoption of Electric Vehicles. However, careful planning is necessary due to high cost in infrastructure and potential queues, and literature on charging station competition is scarce. To address this and similar problems, this thesis proposes a versatile game-theoretic model for investor competition, where competing firm investors aim to maximise individual net profit by choosing locations, capacities, prices and the speed of service at their firms. On the other hand, self-interested customers aim to minimise the expected cost of acquiring the service firms sell. This includes a cost to access each firm, the fee for the service and an expected cost due to congestion at the firm. In addition, extraneous competition outside the investor system is considered as an option for customers. The solution combines analytical and algorithmic techniques to obtain subgame-perfect equilibria, and enables to assess both qualitative and quantitative aspects of firm competition. The model is applied to building charging stations for Electric Vehicles, and it is shown theoretically and empirically that equilibrium charging prices deviate upward of the marginal charging cost due to the inability to satisfy charging demand immediately, even with vast improvements in charging technology. Further results show that private investors will prefer to compete on the same route, because stations on longer routes have to set lower prices at their stations and this consists a significant disadvantage. Moreover, the more drivers are willing to pay in order to save time from their journey, the more investors will increase their profits at the expense of drivers. The inclusion of price choice and extraneous competition reinforces the existence of pure strategy Nash equilibria in capacity choice, and SPE solutions are highly efficient compared to optimal firm allocations when it comes to system-wide social welfare. Last, this thesis examines subsidies to stations as incentives to expanding rapid charging stations. Results show that subsidising the purchase of charging units for stations can have a significant beneficial effect for both EV drivers and station investors. In contrast, subsidies on the energy price for stations could provide incentive to investors to reduce capacities and increase prices. Finally, it is shown how the proposed model can be used to calculate the monetary gain or loss for drivers and investors due to subsidies, and to determine optimal subsidy levels according to certain requirements.

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Published date: June 2019

Identifiers

Local EPrints ID: 433533
URI: http://eprints.soton.ac.uk/id/eprint/433533
PURE UUID: 6ba0d424-257d-4e60-9a27-c7d51e27f3da
ORCID for Enrico Gerding: ORCID iD orcid.org/0000-0001-7200-552X

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Date deposited: 27 Aug 2019 16:30
Last modified: 28 Aug 2019 00:34

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