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Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS.

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The low on-current and direct source-to-drain tunneling (DSDT) issues are the main drawbacks in the ultrascaled tunneling field-effect transistors based on carbon nanotube and ribbons. In this article, the performance of nanoscale junctionless carbon nanotube tunneling field-effect transistors (JL CNTTFETs) is greatly improved by using the synergy of electrostatic and chemical doping engineering. The computational investigation is conducted via a quantum simulation approach, which solves self-consistently the Poisson equation and the non-equilibrium Green’s function (NEGF) formalism in the ballistic limit. The proposed high-performance JL CNTTFET is endowed with a particular doping approach in the aim of shrinking the band-to-band tunneling (BTBT) window and dilating the direct source-to-drain tunneling window, while keeping the junctionless paradigm. The obtained improvements include the on-current, off-current, ambipolar behavior, leakage current, I60 metric, subthreshold swing, current ratio, intrinsic delay, and power-delay product. The scaling capability of the proposed design was also assessed, where greatly improved switching performance and sub-thermionic subthreshold swing were recorded by using JL CNTTFET with 5 nm gate length. Moreover, a ferroelectric-based gating approach was employed for more enhancements, where further improvements in terms of switching performance were recorded. The obtained results and the conducted quantum transport analyses indicate that the proposed improvement approach can be followed to improve similar cutting-edge ultrascaled junctionless tunnel field-effect transistors based on emerging atomically thin nanomaterials.

In this article, ultrascaled junctionless (JL) field-effect phototransistors based on carbon nanotube/nanoribbons with sub-10 nm photogate lengths were computationally assessed using a rigorous quantum simulation. This latter self-consistently solves the Poisson equation with the mode space (MS) non-equilibrium Green’s function (NEGF) formalism in the ballistic limit. The adopted photosensing principle is based on the light-induced photovoltage, which alters the electrostatics of the carbon-based junctionless nano-phototransistors. The investigations included the photovoltage behavior, the I-V characteristics, the potential profile, the energy-position-resolved electron density, and the photosensitivity. In addition, the subthreshold swing–photosensitivity dependence as a function of change in carbon nanotube (graphene nanoribbon) diameter (width) was thoroughly analyzed while considering the electronic proprieties and the quantum physics in carbon nanotube/nanoribbon-based channels. As a result, the junctionless paradigm substantially boosted the photosensitivity and improved the scaling capability of both carbon phototransistors. Moreover, from the point of view of comparison, it was found that the junctionless graphene nanoribbon field-effect phototransistors exhibited higher photosensitivity and better scaling capability than the junctionless carbon nanotube field-effect phototransistors. The obtained results are promising for modern nano-optoelectronic devices, which are in dire need of high-performance ultra-miniature phototransistors.