Moving from New and Renewable Energy to Renewable and Carbon-Free Energy

Ekadewi, Putty

doi:10.55981/brin.562.c4

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…On the other hand, there has been a notable shift in electricity utilization towards renewable energy sources such as solar, wind, hydropower, biomass, and geothermal energy (Ekadewi, 2022) (Citraningrum, 2019). Among these, solar energy is one of the most widely adopted options (Mayasari et al, 2022) (Mammadov et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Datasheet-Based Efficiency Comparison Analysis of Alternating Current (AC) And Direct Current (DC) Electrical Systems

Halim,

Cevin Hutabarat,

Sucianti Adam

et al. 2023

JWS

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In today's electrical infrastructure, a significant portion continues to depend on the AC (alternating current) system, necessitating energy conversion from DC (direct current) to AC during power generation and vice versa when reaching consumers. Nonetheless, as renewable energy sources and DC-based electronic devices gain popularity, the DC electrical system presents an attractive alternative. This research compares the energy efficiency between AC and DC electrical systems in school buildings. Through literature review and energy analysis in school buildings, the study found that the DC electrical system is significantly more efficient, achieving an efficiency rate of 89%. In contrast, the AC system only reaches 84%. The implications of this research provide valuable insights for implementing more efficient and sustainable electrical systems in buildings in the future.

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Section: Introductionmentioning

confidence: 99%

Datasheet-Based Efficiency Comparison Analysis of Alternating Current (AC) And Direct Current (DC) Electrical Systems

Halim,

Cevin Hutabarat,

Sucianti Adam

et al. 2023

JWS

View full text Add to dashboard Cite

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Hybrid optimisation and machine learning models for wind and solar data prediction

Amoura

Torres

Lima

et al. 2023

HIS

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The exponential growth in energy demand is leading to massive energy consumption from fossil resources causing a negative effects for the environment. It is essential to promote sustainable solutions based on renewable energies infrastructures such as microgrids integrated to the existing network or as stand alone solution. Moreover, the major focus of today is being able to integrate a higher percentages of renewable electricity into the energy mix. The variability of wind and solar energy requires knowing the relevant long-term patterns for developing better procedures and capabilities to facilitate integration to the network. Precise prediction is essential for an adequate use of these renewable sources. This article proposes machine learning approaches compared to an hybrid method, based on the combination of machine learning with optimisation approaches. The results show the improvement in the accuracy of the machine learning models results once the optimisation approach is used.

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Moving from New and Renewable Energy to Renewable and Carbon-Free Energy

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Cited by 2 publications

References 9 publications

Datasheet-Based Efficiency Comparison Analysis of Alternating Current (AC) And Direct Current (DC) Electrical Systems

Datasheet-Based Efficiency Comparison Analysis of Alternating Current (AC) And Direct Current (DC) Electrical Systems

Hybrid optimisation and machine learning models for wind and solar data prediction

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