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Record W4402477128 · doi:10.11159/icert24.106

Challenges in the Future Swedish Energy System

2024· article· en· W4402477128 on OpenAlexvenueno aff
Louise Ödlund, Maria Andersson

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2024
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The ongoing switch towards more sustainable energy system is one of the most important challenges that society today is facing.The energy system in Sweden is currently confronted with questions as for example unprecedented electricity prices driven both by geopolitical constrains and supply constrains in the European energy system.Consumers have also experienced significant difference in price within the country, and existing bottlenecks have resulted in substantial income transfer from the consumers to the transmission system operator.This situation is mainly based on the fact that most of the production of electricity occurs in the north of Sweden, whilst the demand is relatively higher in the south of the country.Sweden faces a delicate balance between increasing electricity demand and the need for sustainable, efficient, and resilient energy systems.The energy system in Sweden needs to be resilient and at the same time meet the upcoming significant increased demand of electricity.It is vital that all available energy sources are included in planning of the future energy system.Sweden has a higher use of electricity compared to other European countries, mainly due to historical low electricity prices.This means that there is a potential to reduce the use of electricity in Sweden, which needs to be considered to avoid risk to miss the potential of more efficient use of electricity.There are several studies that are analysing the most optimal mix of electricity production.The aim of this study is to give a review of current research studies dealing with the opportunities and challenges linked to the need for a future resilient Swedish energy system that meets both the today´s and futures need of electricity.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0110.005
Open science0.0010.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0140.003

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractno

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