Low Voltage Direct Current Supplies Concept for Residential Applications

Alsaedi, Ammar; Alharbi, Fahad M.; Alahdal, Abdulrahman; Alahmadi, Ahmed N. M.; Ammous, Anis; Ammous, Kaiçar

doi:10.1177/01445987211072893

Cited by 4 publications

(2 citation statements)

References 16 publications

(23 reference statements)

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“…Research in the field of AC power quality has reached a level of maturity, while the corresponding aspect related to DC power quality remains an area that requires further investigation [3]. A DC microgrid does not involve the synchronization, harmonic, reactive power control, and frequency control of a traditional AC power grid, and it has higher power quality [4]. However, the relevant system has not been established, and the definition of DC energy quality is not uniform [5].…”

Section: Introductionmentioning

confidence: 99%

Classification Algorithm for DC Power Quality Disturbances Based on SABO-BP

Duan,

Cen,

et al. 2024

Energies

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To better address and improve the issues related to DC power quality, this paper proposes an identification method tailored for DC power quality disturbances. First, it explores the underlying mechanisms and waveform characteristics of common DC power disturbances. By integrating the results of time–frequency analysis obtained through the S-transform, five distinct features are designed and extracted to serve as classification indicators. The SABO algorithm is subsequently employed to optimize the BP neural network, assisting in determining the optimal input weights and hidden layer thresholds. This optimization technique helps prevent the network from becoming stuck in local minima, thereby enhancing its robustness and generalization capabilities. This paper presents a simulation system for AC/DC power systems to conduct experimental verification. The system simulates various DC power quality issues and monitors abnormal waveforms. According to the designated classification index, the features of simulated disturbance signals are extracted. The SABO-BP classification prediction model is then used to automatically classify and identify the samples. The experimental results demonstrate high accuracy in classification and identification using the proposed method. In comparison to the BP neural network method, the SABO-BP method demonstrates an 8.207% improvement in accurately identifying disturbance signals. It is capable of accurately identifying direct current power quality signals, thereby assisting in the evaluation and control of power quality issues.

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Section: Introductionmentioning

confidence: 99%

Classification Algorithm for DC Power Quality Disturbances Based on SABO-BP

Duan,

Cen,

et al. 2024

Energies

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“…They have the distinct advantages of reducing the need for power converters and shortening energy transmission distances. They are considered to be one of the primary solutions for energy savings according to several studies [7][8][9][10][11][12][13][14][15][16][17]. There are even communities, such as those in the USA, that live comfortably and daily on 100% DC microgrids [18].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Energy Consumption: A Case Study of LVDC Nanogrid Implementation in Tertiary Buildings on La Réunion Island

Graillet,

Genon-Catalot,

Lucas de Peslouan

et al. 2024

Energies

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In the context of an insulated area with a subtropical climate, such as La Réunion island, it is crucial to reduce the energy consumption of buildings and develop local renewable energy sources to achieve energy autonomy. Direct current (DC) nanogrids could facilitate this by reducing the energy conversion steps, especially for solar energy. This article presents the deployment and efficiency evaluation of a 48 VDC low-voltage direct current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a lithium–iron–phosphate (LFP) battery, and DC end-use equipment, such as LED lighting and DC fans, for two individual offices. For identical test conditions, which are at an equivalent cabling distance and with the same final power demand, the total power consumed by the installation is measured for several stages from 50 to 400 W, according to a 100% DC configuration or a conventional DC/AC/DC PV configuration incorporating an inverter and AC/DC converter. The methodology used enables a critical view to be taken of the installation, assessing both its efficiency and its limitations. Energy savings of between 23% and 40% are measured in DC for a power limit identified at 150 W for a distance of 25 m. These results show that it is possible to supply 48 VDC in an innovative way to terminal equipment consuming no more than 100 W, such as lighting and air fans, using the IEEE 802.3 bt power over ethernet (PoE) protocol, while at the same time saving energy. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification, and the measurement results are described in the paper.

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A Study on LVDC Systems for Commercial Building Applications

Chacko

Eapen

et al. 2022

2022 IEEE 19th India Council International Conference (INDICON)

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Low Voltage Direct Current Supplies Concept for Residential Applications

Cited by 4 publications

References 16 publications

Classification Algorithm for DC Power Quality Disturbances Based on SABO-BP

Classification Algorithm for DC Power Quality Disturbances Based on SABO-BP

Optimizing Energy Consumption: A Case Study of LVDC Nanogrid Implementation in Tertiary Buildings on La Réunion Island

A Study on LVDC Systems for Commercial Building Applications

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