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Record W2545090074 · doi:10.1002/ep.12502

Economic Analysis and Potential Feed‐in Tariff of Grid‐Connected PV Systems in Nigeria

2016· article· en· W2545090074 on OpenAlexaff
Muyiwa S. Adaramola, Samuel S. Paul

Bibliographic record

VenueEnvironmental Progress & Sustainable Energy · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsResearch Manitoba
Fundersnot available
KeywordsTariffCost of electricity by sourcePhotovoltaic systemFeed-in tariffEnvironmental scienceInvestment (military)ElectricityNet present valuePort harcourtPort (circuit theory)IncentiveSolar energyEnvironmental engineeringEnvironmental economicsEngineeringEconomicsRenewable energyElectrical engineeringElectricity generationEnergy policyProduction (economics)PhysicsMicroeconomicsInternational economicsPower (physics)

Abstract

fetched live from OpenAlex

This study presents a feasibility study of grid‐tied PV system in selected locations across the country with focus on cost of energy produced and incentives such as feed‐in tariff and investment support. Based on the study locations and assumptions used in this study, it was estimated that the annual energy generated by the PV system varies between 2885 kWh in Port‐Harcourt in southern region and 4391 kWh in Isa in northern region. The optimal simulation results reveal that the levelized cost of energy varies from one location to another: highest in very low‐energy site (Port‐Harcourt) and lowest in the very high‐energy (Isa). In addition, it is estimated that the feed‐in tariff varies between N76.54/kWh (or US$0.4556/kWh) in Port‐Harcourt and N50.25/kWh (or US$0.2991/kWh) in Isa. It was further observed that the ratio of levelized cost of energy to current electricity tariff is least at Bauchi with a value of 1.22 and highest in Ikeja with a value of 2.95. Consequently, it would easier to sell solar PV idea to individual in Bauchi than those in Ikeja to invest in solar PV. Some of the benefits and potential challenges of implementing feed‐in tariff in Nigeria were also presented. © 2016 American Institute of Chemical Engineers Environ Prog, 36: 305–314, 2017

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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 designObservational
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

Citations6
Published2016
Admission routes1
Has abstractyes

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