A Distributed Coordination Method for Coupled Traffic-Power Network Equilibrium Incorporating Behavioral Theory

Qiao, Wenjie; Zhao, Qiang; Si, Fangyuan; Han, Yinghua

doi:10.1109/tvt.2022.3206095

Cited by 14 publications

(4 citation statements)

References 33 publications

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“…Consequently, the driving routes finally chosen by the same type of vehicle with the same starting point and end point are expected to have the same cost. Reference (Qiao et al, 2022) expands the UE model to a stochastic UE model, accounting for the challenge of travelers obtaining complete information and their cognitive bias. For EV users, their driving costs include charging fees, with EVs typically being charging price takers.…”

Section: Introductionmentioning

confidence: 99%

“…In the context of CPTS, numerous studies have delved into the pursuit of social welfare maximization (Wei et al, 2016;Wei et al, 2017;Liu et al, 2022;Lv et al, 2019;Lu et al, 2018;He et al, 2016) or CPTS's revenue maximization (Shao et al, 2023;Qiao et al, 2022). There are some other works considering alternative objectives, such as reducing carbon emissions (Yuan et al, 2023) and fostering the utilization of renewable energy sources (Zhou et al, 2019;Lv et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Optimal pricing strategies for distribution system operator in coupled power-transportation system

Lu,

Yang,

Cui

et al. 2024

Front. Energy Res.

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The power grid and transportation network are coupled by the charging behavior of electric vehicles. Based on the coupled power-transportation network model, this paper first analyzes the effect of the distribution system operator’s (DSO) electricity selling price on guiding the charging behavior of electric vehicles in the transportation network and then builds the DSO’s optimal pricing formulation. Considering the competition between multiple charging network operators (CNOs), this paper establishes a game model between CNOs and solves it iteratively through the best response dynamic method. An approximation method using the elasticity matrix is proposed to speed up the solution by reducing the multi-layer optimization to a single layer one in each iteration, with its effectiveness validated through numerical tests. Furthermore, the paper discusses the issue of the prisoner’s dilemma that arises among CNOs and explores the potential impact of their cooperative strategies on the overall system.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal pricing strategies for distribution system operator in coupled power-transportation system

Lu,

Yang,

Cui

et al. 2024

Front. Energy Res.

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“…In their study, the authors of [36] investigate social optimal welfare by examining the charging fees and the interactions between cooperative Charging Network Operators, mobile EVs, and bulk power infrastructures. In addition, the authors of [37] suggest a framework that integrates pricing for charging and scheduling of power.…”

Section: Introductionmentioning

confidence: 99%

Non-Iterative Coordinated Optimisation of Power–Traffic Networks Based on Equivalent Projection

Dai,

Zeng,

Wang

et al. 2024

Energies

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The exchange of sensitive information between power distribution networks (PDNs) and urban transport networks (UTNs) presents a difficulty in ensuring privacy protection. This research proposes a new collaborative operation method for a coupled system. The scheme takes into account the schedulable capacity of electric vehicle charging stations (EVCSs) and locational marginal prices (LMPs) to handle the difficulty at hand. The EVCS hosting capacity model is built and expressed as the feasible area of charging power, based on AC power flow. This model is then used to offer information on the real schedulable capacity. By incorporating the charging loads into the coupling nodes between PDNs and UTNs, the issue of coordinated operation is separated and becomes equal to the optimal problem involving charging loads. Based on this premise, the most efficient operational cost of PDNs is transformed into a comparable representation of cost information in PDNs. This representation incorporates LMP information that guides charging decisions in UTNs. The suggested collaborative scheduling methodology in UTNs utilises the collected projection information from the static traffic assignment (STA) to ensure data privacy protection and achieve non-iterative calculation. Numerical experiments are conducted to illustrate that the proposed method, which uses a smaller amount of data, achieves the same level of optimality as the coordinated optimisation.

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“…The coupled problem arising from a transportation network together with a power network load balancing has been analyzed via single-level optimization formulations 22 , exploiting the benefits of EV charging with renewable energy. Some works have explored hierarchical models such as Nash-Stackelberg-Nash game framework in a network-flow based formulation [27][28][29][30][31][32] . Traditional game-theoretic frameworks have analyzed the interaction between EVs and the grid through the regulation of energy prices and EV charging schedules, where the grid acts as a player that sets the cost of the energy, and EVs respond with a charging schedule that optimizes their operation, usually assuming traffic flow models 33 .…”

mentioning

confidence: 99%

Renewable-based charging in green ride-sharing

Perotti,

Ospina,

Bianchin

et al. 2023

Sci Rep

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Governments, regulatory bodies, and manufacturers are proposing plans to accelerate the adoption of electric vehicles (EVs), with the goal of reducing the impact of greenhouse gases and pollutants from internal combustion engines on human health and climate change. In this context, the paper considers a scenario where ride-sharing enterprises utilize a 100%-electrified fleet of vehicles, and seeks responses to the following key question: How can renewable-based EV charging be maximized without disrupting the quality of the ride-sharing services? We propose a new mechanism to promote EV charging during hours of high renewable generation, and we introduce the concept of charge request, which is issued by a power utility company. Our mechanism is inspired by a game-theoretic approach where the power utility company proposes incentives and the ride-sharing platform assigns vehicles to both ride and charge requests; the bargaining mechanism leads to prices and EV assignments that are aligned with the notion of Nash equilibria. Numerical results show that it is possible to shift the EV charging during periods of high renewable generation and adapt to intermittent generation while minimizing the impact on the quality of service. The paper also investigates how the users’ willingness to ride-share affects the charging strategy and the quality of service.

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A Distributed Coordination Method for Coupled Traffic-Power Network Equilibrium Incorporating Behavioral Theory

Cited by 14 publications

References 33 publications

Optimal pricing strategies for distribution system operator in coupled power-transportation system

Optimal pricing strategies for distribution system operator in coupled power-transportation system

Non-Iterative Coordinated Optimisation of Power–Traffic Networks Based on Equivalent Projection

Renewable-based charging in green ride-sharing

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