We examine carbon-policy design for a power system with energy storage as well as renewable and fossil-fuelled generation. A central-planning solution internalises the environmental externality of CO2 emissions and cu...
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Security of substations is important to ensure reliability and integrity of the power grid. In this paper, we provide a complete vulnerability assessment framework for a SAS substation. The framework uses CVE database...
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The integration of the Internet of Things (IoT) into smart city frameworks ushers in new opportunities for merging and enhancing diverse services, enabling seamless connectivity across multiple application domains. Th...
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The electromagnetic interference (EMI) problem caused by power electronic switching devices and pulse width modulation (PWM) affects the normal operation of the motor drive system. In this paper, a random PWM based on...
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The conventional differential boost inverters have limited voltage gain due to the inductor's parasitic resistance, which limits the output voltage ranges as the duty cycle approaches unity and causes a narrow inp...
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To provide flexibility for the operation of smart electricity networks,a large number of scattered demand response resources are managed by a demand response aggregator(DRA).Increasing the economic viability of this n...
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To provide flexibility for the operation of smart electricity networks,a large number of scattered demand response resources are managed by a demand response aggregator(DRA).Increasing the economic viability of this new entity,i.e.,DRA,has attracted a great deal of attention in recent *** this direction,this paper proposes stochastic model of multiple large-scale energy storage system(LESS)investments from the perspective of a DRA.A LESS directly connects to smart distribution networks and provides the possibility to save energy costs and thereafter increase the energy efficiency of the *** this paper,a novel mixed-integer model is proposed to determine the optimal capacity and operation of a LESS in coordination with a DR *** model,as a main contribution to literature,comprises novel managerial options,such as the number of allowed DR actions,the number of allowed charging and ***,the model is designed to be capable enough to exclude the hours in which the demand side is not allowed to participate in *** proposed model is tested through a numerical example with various case *** simulation results show the substantial economic impacts of considering the introduced managerial options in the coordination of a LESS operation with DR.
An accurate classification method is highly required in the development of a fault detection system. Various deep-learning techniques have recently been used for fault classification. However, optimally training deepe...
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Triboelectric nanogenerators (TENGs) are efficient, sustainable, low-maintenance, and environment-friendly power sources that are suitable for wireless, portable, and wearable devices. This study, for the first time, ...
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Triboelectric nanogenerators (TENGs) are efficient, sustainable, low-maintenance, and environment-friendly power sources that are suitable for wireless, portable, and wearable devices. This study, for the first time, presents a vertical contact mode TENG utilizing a thin film of silk and copper film as the triboelectric pair. This contact separation mode TENG is highly flexible, cost-effective, and biocompatible. The silk triboelectric layer is spin-coated on a PET sheet which serves as the flexible substrate of the TENG. The response was maximized by enhancing the surface roughness of the copper film, which in turn increases the contact area during triboelectrification, leading to an increase in charge generation. The optimized TENG yielded a maximum output voltage of 350 $V_{pp}$ and a power density of 4 $W/m^{2}$ and was able to power up commercially available LEDs. Repeatability analysis and TENG performance at different forces yielded satisfactory results. IEEE
Bilevel optimization has been recently applied to many machine learning tasks. However, their applications have been restricted to the supervised learning setting, where static objective functions with benign structur...
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Bilevel optimization has been recently applied to many machine learning tasks. However, their applications have been restricted to the supervised learning setting, where static objective functions with benign structures are considered. But bilevel problems such as incentive design, inverse reinforcement learning (RL), and RL from human feedback (RLHF) are often modeled as dynamic objective functions that go beyond the simple static objective structures, which pose significant challenges of using existing bilevel solutions. To tackle this new class of bilevel problems, we introduce the first principled algorithmic framework for solving bilevel RL problems through the lens of penalty formulation. We provide theoretical studies of the problem landscape and its penalty-based (policy) gradient algorithms. We demonstrate the effectiveness of our algorithms via simulations in the Stackelberg game and RLHF. Copyright 2024 by the author(s)
We propose a perturbative design method for engineering quasi-isospectrality in multidimensional photonic systems. Our study provides platform-transparency alleviating mathematical strictness of supersymmetric transfo...
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