MétaCan
Menu
Back to cohort

Smart Microgrid Architecture For Home Energy Management System

2021· article· en· W3217719870 on OpenAlexaff
Majed Shakir, Yevgen Biletskiy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMicrogridEnergy management systemSmart gridEnergy managementComputer scienceArchitectureEmbedded systemSoftware architectureHome automationField (mathematics)Energy consumptionSystems engineeringSoftwareEngineeringEnergy (signal processing)Control (management)Operating systemElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The present paper is devoted to adaptation of the achievements in the general research field of smart grid to the small power utilization systems, or microgrids. In particular, the focus of the present research is the architectural solution for a smart microgrid for automated home energy management systems. The proposed system architecture includes three main subsystems: load identification, forecasting and optimization. An automated home energy management system design requires general understanding of regulations and the ethics in collecting the building appliances data. The system design requires power data from the appliances be handled carefully when the data is stored. This is implemented to track the algorithm accuracy and data integrity. The software developed based on the present smart microgrid architecture delivers the lowest energy consumption price without sacrificing users comfort. One of the important features of the present architecture is adjustability because any of the three subsystems can be easily replaced by another subsystem with a more effective method in background.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.165
Teacher spread0.161 · 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 teacher head, not a consensus.

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

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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicSmart Grid Energy ManagementFrench-language works237,207