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Record W3049483022 · doi:10.5829/ijee.2020.11.02.06

Techno-economic Feasibility Study of the Gunde Teklehaymanote Micro-hydropower Plant at Tindwat River, Central Gondar, Ethiopia

2020· article· en· W3049483022 on OpenAlexfundno aff
A. K. Belay, D. Atenafu, S. Birhan, T. Tegengn

Bibliographic record

VenueIranica Journal of Energy and Environment · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersNatural Resources CanadaChina Electronics Technology Group CorporationUniversity of Gondar
KeywordsHydropowerPayback periodHydroelectricityInternal rate of returnElectricity generationEnvironmental scienceGreenhouse gasElectricityRenewable energyEnvironmental engineeringWater resource managementEngineeringProduction (economics)Power (physics)Economics

Abstract

fetched live from OpenAlex

Ethiopia has a high potential for water for hydro-power development. Even though there is untapped potential, the country's electricity coverage is poor. This paper presents a technical-economic feasibility study of gunde micro hydropower at the Tindwat River, Central Gondar, Ethiopia. In the techno-economics study, the analysis was made for energy modeling, economic scenarios, and sensitivity, risk, and emission analyses. The study shows that this mini-hydropower project can be developed with an installed power of 18 kW, where the Kaplan turbine is recommended. The construction of small scale hydropower in the tindwat river is technically and economically feasible with total net present cost of US $ 253537, cost of energy $0.09/kWh, simple payback period of 6.9 years, and internal rate of return 23.9%. Te result also shows that construction of hydropower curtails greenhouse gas emissions of carbon dioxide by 588.65m3 of gasoil per year. It also showed that small hydroelectric power generation from Tindwat River would improve the electricity supply to Gunde Teklehaymanote monstery and off-grid rural communities.

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 categoriesInsufficient 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 score0.407
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 communication0.0000.000
Open science0.0010.001
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 head0.014
GPT teacher head0.202
Teacher spread0.188 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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