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Record W4390930602 · doi:10.30574/wjarr.2024.21.1.0112

Microgrid systems in U.S. energy infrastructure: A comprehensive review: Exploring decentralized energy solutions, their benefits, and challenges in regional implementation

2024· article· en· W4390930602 on OpenAlexaff
Kenneth Ifeanyi Ibekwe, Peter Efosa Ohenhen, Onyinyechukwu Chidolue, Aniekan Akpan Umoh, Bright Ngozichukwu, Valentine Ikenna Ilojianya, Adetomilola Victoria Fafure

Bibliographic record

VenueWorld Journal of Advanced Research and Reviews · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMicrogridInteroperabilityRenewable energyEnergy securityEnvironmental economicsSustainabilityRisk analysis (engineering)BusinessComputer scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

This study presents a comprehensive review of microgrid systems within the U.S. energy infrastructure, focusing on decentralized energy solutions and their regional implementation. The primary objective is to explore the evolution, current state, and future prospects of microgrid technologies, assessing their technological, economic, and environmental impacts on regional energy infrastructures. Employing a systematic literature review methodology, the study synthesizes data from peer-reviewed journals, industry reports, and government publications. The search strategy involved keyword searches and manual screening, adhering to strict inclusion and exclusion criteria to ensure relevance and contemporary significance. Key findings reveal that microgrids are instrumental in enhancing energy security, integrating renewable energy sources, and providing economic benefits through decentralized solutions. Technological advancements in microgrid components and control systems have significantly improved efficiency and adaptability. However, challenges such as regulatory hurdles, technological integration, and financial constraints persist. The study concludes that microgrids represent a transformative solution for the future of energy systems, balancing reliability, sustainability, and economic viability. Strategic recommendations for industry and policymakers include developing clear regulatory frameworks, investing in advanced storage solutions, and incentivizing renewable energy integration. Future research directions emphasize enhancing microgrid interoperability with traditional grids, developing robust cybersecurity measures, and exploring innovative business models. In summary, microgrids stand at the forefront of revolutionizing the energy sector, offering a path towards a more resilient, sustainable, and equitable energy future, with ongoing advancements shaping the energy systems of tomorrow.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.324
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations43
Published2024
Admission routes1
Has abstractyes

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