Abstract
Transportation electrification has become a prominent area of research and investment, especially in the last decades, regarding the increasing concerns for environmental sustainability. In this manner, there are different studies realized on electric vehicles (EVs), especially from the power system integration point of view to enable a more extensive penetration without causing adverse impacts on system operation. Different approaches for the direct and indirect management of EVs based charging demand in power systems have already been proposed in the literature as well as employed in the industry. In this study, from an indirect management point of view, a smart dynamic pricing approach based on a fuzzy logic controller based decision-making structure is proposed for EV charging in a distribution system. The proposed new decision-making method considers dynamically varying as well as static operational issues together with the social welfare of EV owners to provide real-time decisions compared to existing studies considering the wider EV charging service pricing topic from a different perspective. © 2020 IEEE.

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Large horsepower induction motors play a critical role in the operation of industrial facilities. In this respect, the distribution network operators dedicate a high priority to the operational safety of these motor loads. In this paper, the induction motor starting is modeled analytically and in a semi-static fashion. This model is imbedded in a convex distribution system restoration problem. In this optimization problem, it is aimed to determine the optimal status of static loads and the optimal dispatch of distributed generators such that: a) the induction motors can be reaccelerated in a safe way and, b) the total power of static loads that cannot be supplied before the motor energization, is minimized. The proposed optimization problem is applied in the case of a distribution network under different simulation scenarios. The feasibility and accuracy of the obtained results are validated using a) off-line time-domain simulations, and b) Power Hardware-In-the-Loop experiments.

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This paper shows that the platforms' private information on demand may explain the empirical observation that platforms like Amazon resell high-demand products, while acting as marketplace for low-demand goods. More precisely, the paper examines the strategic interaction between a seller and a better informed platform within a signalling game. We consider that the platform may choose between two distinct business models: act as a reseller or work as a pure marketplace between the buyers and the seller. The marketplace mode, which allows to internalize the spillover between the platform's sales and the seller's direct sales is always preferred for a low-value good. The reselling mode, which allows the platform to take advantage of its private information, may be selected in the case of high-value goods provided that (i) the externalities between direct sales and platform sales are not too strong and (ii) the difference between consumers' willingness to pay for the high and the low-value goods is large enough. Under these conditions, the game displays a Least-Cost Separating Equilibrium in which the platform works as a marketplace for low-demand goods, while it acts as a reseller in the case of high-demand goods.

Abstract
Radio-Frequency IDentification (RFID) technologies have been widely used in physical ID cards in educational institutions due to its low-cost, simple integration and convenience. In a university campus, the RFID technology can be used for proximity-based authentication for services such as access control, student/employee attendance record, or in-campus payments. These RFID-based technologies present vulnerabilities that, if exploited, can compromise the university campus authentications systems. RFID skimming and tag killing are examples of attacks that are simple to execute and have a high impact on their victims. This paper exploits a tag-related vulnerability of an ID Card based on RFID technology for proximity-based authentication inside a university campus. The proof of concept presented shows that, by using low-cost commercial-off-the-shelf hardware and open-source software, it is simple to clone an ID card and perform RFID skimming, harming the real ID card users. Possible countermeasures are later introduced and discussed.