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Binary subtractor 1

DG gate 1

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design and optimization 1

diesel generator (DG) 1

distributed generation (DG) 1

dry eye disease 1

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glycolytic reprogramming 1

hybrid renewable energy systems (HRESs) 1

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Reversible binary subtractor design using quantumdot-cellular automata Article

Jadav Chandra DAS, Debashis DE

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9, Pages 1416-1429 doi: 10.1631/FITEE.1600999

Abstract: In this paper we describethe design and implementation of a DG gate in QCA.The universal natureof the DG gate has been established.

Keywords： Quantum dot-cellular automata (QCA) Reversible logic DG gate Binary subtractor Quantum cost

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Hyperosmolarity promotes macrophage pyroptosis by driving the glycolytic reprogramming of corneal epithelial cells in dry eye disease

Frontiers of Medicine 2023, Volume 17, Issue 4, Pages 781-795 doi: 10.1007/s11684-023-0986-x

Abstract: in macrophages upon the activation of the related gene and protein expression. 2-Deoxy-d-glucose (2-DGIn vivo, 2-DG showed potential efficacy in relieving DED activity and could significantly reduce

Keywords： dry eye disease glycolytic reprogramming pyroptosis inflammation 2-DG

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State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (HRESs)

Maurizio FACCIO, Mauro GAMBERI, Marco BORTOLINI, Mojtaba NEDAEI

Frontiers in Energy 2018, Volume 12, Issue 4, Pages 591-622 doi: 10.1007/s11708-018-0567-x

Abstract: The current research aims to present an inclusive review of latest research works performed with the aim of improving the efficiency of the hybrid renewable energy systems (HRESs) by employing diverse ranges of the optimization techniques, which aid the designers to achieve the minimum expected total cost, while satisfying the power demand and the reliability. For this purpose, a detailed analysis of the different classification drivers considering the design factors such as the optimization goals, utilized optimization methods, grid type as well as the investigated technology has been conducted. Initial results have indicated that of all optimization goals, load demand parameters including loss of power supply probability (LPSP) and loss of load probability (LLP), cost, sizing (configuration), energy production, and environmental emissions are the most frequent design variables which have been cited the most. Another result of this paper indicates that almost 70% of the research projects have been dedicated toward the optimization of the off-grid applications of the HRESs. Furthermore, it has been demonstrated that, integration of the PV, wind and battery is the most frequent configuration. In the next stage of the paper, a review concerning the sizing methods has also been carried out to outline the most common techniques which are used to configure the components of the HRESs. In this regard, an analysis covering the optimized indicators such as the cost drivers, energy index parameters, load indicators, battery’s state of charge, PV generator area, design parameters such as the LPSP, and the wind power generation to load ratio, has also been performed.

Keywords： design and optimization environmental pollutions PV array wind turbines (WTs) inverter diesel generator (DG

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A new technique for islanding operation of distribution network connected with mini hydro

J. A. LAGHARI,H. MOKHLIS,M. KARIMI,A. H. A. BAKAR,Hasmaini MOHAMAD

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 5, Pages 418-427 doi: 10.1631/FITEE.1400309

Abstract: distribution network is a topic of interest due to the significant penetration of distributed generation (DG

Keywords： Islanding operation Mini hydro Distributed generation (DG) Islanding detection Load shedding

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intelligent water drop bundled wavelet neural network to solve the islanding detection by inverter-based DG

Mehrdad TARAFDAR HAGH,Homayoun EBRAHIMIAN,Noradin GHADIMI

Frontiers in Energy 2015, Volume 9, Issue 1, Pages 75-90 doi: 10.1007/s11708-014-0337-3

Abstract: In this paper, a passive neuro-wavelet based islanding detection technique for grid-connected inverter-based distributed generation was developed. The weight parameters of the neural network were optimized by intelligent water drop (IWD) to improve the capability of the proposed technique in the proposed problem. The proposed method utilizes and combines wavelet analysis and artificial neural network (ANN) to detect islanding. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Discrete wavelet transform (DWT) is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. In passive schemes with a large non-detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The simulation results from Matlab/Simulink shows that the proposed method has a small non-detection zone, and is capable of detecting islanding accurately within the minimum standard time.

Keywords： detection neuro-wavelet intelligent water drop (IWD) non-detection zone (NDZ) distributed generation (DG