MétaCan
Menu
Back to cohort

An Optimum Sizing for a Hybrid Storage System in Solar Water Pumping Using ICA

2022· article· en· W4283204894 on OpenAlexaff
Amirhossein Jahanfar, M. Tariq Iqbal

Bibliographic record

Venue2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSizingReliability (semiconductor)Storage tankHybrid systemComputer data storageComputer scienceProcess engineeringWater storageEnergy storageEnvironmental scienceReliability engineeringEngineeringWaste managementPower (physics)Mechanical engineeringChemistryComputer hardware

Abstract

fetched live from OpenAlex

Solar water pumps must be the most optimum size to work efficiently and be at a reasonable price. The storage system can play a main role in both system reliability and the total cost of a solar water pumping project; thus, it should be designed carefully. Traditionally, only batteries or water tanks are used as primary storage system; each of them has its benefits and drawbacks. In this research, a new approach to a storage system is proposed, consisting of both batteries and water tanks at the same time. Such hybrid storage can decrease project cost and increase system reliability. To find the most optimum size for such a hybrid system an optimization algorithm named "Imperialist Competitive Algorithm (ICA)" is used to minimize the Life-Cycle Cost Analysis (LCCA) of the storage system. In this paper, a hybrid storage configuration for solar water pumping for a site in Iran is proposed, and results of the optimum size for that system using ICA are expressed. It is shown that the configuration is more feasible compared with many other configurations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venue2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)Same topicAdvanced Battery Technologies ResearchFrench-language works237,207