Myopic loss aversion in the response of electric vehicle owners to the scheduling and pricing of vehicle charging

Fetene, Gebeyehu Manie; Kaplan, Sigal; Sebald, Alexander; Prato, Carlo Giacomo

doi:10.1016/j.trd.2016.11.020

Cited by 16 publications

(4 citation statements)

References 48 publications

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“…Additionally, the EV-related behavioural aspects are of particular importance to improve the HC in addition to mitigating the technical violations of the network. In this context, charging time scheduling dictates the range anxiety of EV owners due to EV mobility constraints and EV owners' comfort [108][109][110]. Thus, the implementation of DR programs is a function of consumer acceptance and substantially varies with EV owner's choice.…”

Section: Ev Charging Characteristicsmentioning

confidence: 99%

A review of electric vehicle hosting capacity quantification and improvement techniques for distribution networks

Fatima,

Püvi,

Lehtonen

et al. 2023

IET Generation Trans & Dist

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The electrification of the transport sector to control the carbon footprint has been gaining momentum over the last decade with electric vehicles (EVs) seen as the replacement for conventional internal combustion engines. Economic incentives, subsidies, and tax exemptions are also paving the way for rising EV penetration in the power distribution networks. However, the exponential EV adoption requires careful technical and regulatory analysis of traditional networks to satisfy the network reliability constraints. Therefore, it would be vital to find EV hosting capacity (HC) limits of networks from a multifaceted approach involving various market players, mainly distribution system operators and EV owners. This review provides a systematic categorization of EV hosting capacity evaluation and improvement methods, thus enabling researchers and industry personnel to navigate the advancing landscape of EVs. This novel framework extends beyond the theoretical implication of diverse objective functions and HC improvement methods to the actual numerical values of EV HC across varying geographical settings. Therefore, this unique synthesis of varying aspects of EV HC facilitates the in‐depth understanding of the integration of sustainable energy and transport sector.

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Section: Ev Charging Characteristicsmentioning

confidence: 99%

A review of electric vehicle hosting capacity quantification and improvement techniques for distribution networks

Fatima,

Püvi,

Lehtonen

et al. 2023

IET Generation Trans & Dist

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“…Others proposed behaviour models by incorporating the notion of LAM and aimed at investigating some useful relationships between human choices and various factors. Fetene et al [29] found charging decisions of electric vehicle owners are influenced by electricity price using the behaviour models based on LAM. However, the literature on transportation applying LAM is still poor, especially the maritime sector.…”

Section: Slow Steaming Objectives Based On Lammentioning

confidence: 99%

Sailing Speed Optimization Model for Slow Steaming Considering Loss Aversion Mechanism

Zhao

Zhou

Yu-jun

et al. 2020

Journal of Advanced Transportation

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This paper analyses loss aversion mechanism (LAM) of the shipping company’s decision-makers about the risk-based decision (RBD) for slow steaming and generalizes a novel optimization model for the sailing speed through the trade-off between fuel consumption, SOx emissions and delivery delay. The value functions against the benchmark speed were constructed based on physiological expected utility (PEU) to reveal the features of loss aversion, and the objective function was derived from these value functions with the aim to optimize the sailing speed. After that, a Genetic Algorithm (GA) solution with fitness function and special operators was built to solve the proposed model. Finally, the model was applied to pinpoint the PEU for the optimal sailing speed against the benchmark speed, and the sensitivity of the model was discussed with different benchmark speeds, value function weights and input parameters. The analysis shows that the proposed model can assist the slow steaming RBD based on the inner feelings of the shipping company’s decision-makers, offering a novel tool for sailing speed optimization.

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“…It can be expressed as δ S ≥ δ D ≥ 0. Behavioral financiers use the myopia loss aversion (MLA) to explain the phenomenon of such different benefits [56]- [58].…”

Section: B Benchmark Model Based On Rdt In Different Traffic Policiesmentioning

confidence: 99%

Which is More Effective in Guiding Households to Choose Bus Travel–A Transit Subsidy Policy or Discount Policy?

Guan

2019

IEEE Access

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The continuous increase in the number of private cars has caused an imbalance in the travel of cars and buses. This phenomenon has become a bottleneck restricting urban transportation economy and sustainable development. This paper examines the effectiveness of policy options in motivating travelers to choose buses instead of cars. Using of reference dependence describes mode choice behaviors with two attributes under different public transit policies in uncertain conditions. At the same time, we also consider using the bus fare concession strategy to guide the traveler to reasonably choose the bus travel, and establish a bi-level programming model to optimize the bus fare proportions. Among them, the lower-level planning considers the two attributes impact of traffic policy on travelers' decision to bus travel. Using the upperlevel planning, the optimal fare preferential proportion for different policy decisions is decided considering the lowest total system cost. The study highlights that the transit subsidy policy can be employed to guide travelers to choose bus travel preferentially. Model effectiveness is verified using numerical examples. The model is indispensable for the implementation of future traffic demand management strategies.

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Myopic loss aversion in the response of electric vehicle owners to the scheduling and pricing of vehicle charging

Cited by 16 publications

References 48 publications

A review of electric vehicle hosting capacity quantification and improvement techniques for distribution networks

A review of electric vehicle hosting capacity quantification and improvement techniques for distribution networks

Sailing Speed Optimization Model for Slow Steaming Considering Loss Aversion Mechanism

Which is More Effective in Guiding Households to Choose Bus Travel–A Transit Subsidy Policy or Discount Policy?

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