MétaCan
Menu
Back to cohort
Record W4393554173 · doi:10.1007/s12667-024-00654-y

Long-term equilibrium in electricity markets with renewables and energy storage only

2024· article· en· W4393554173 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsHydro-Québec
FundersSt. Olavs Hospital Universitetssykehuset i TrondheimNorges Teknisk-Naturvitenskapelige Universitet
KeywordsTerm (time)Renewable energyElectricityElectricity systemEconomicsEnergy storageElectricity marketNatural resource economicsElectricity generationPhysicsEngineeringPower (physics)ThermodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract In this paper, we study the optimal generation mix in power systems where only two technologies are available: variable renewable energy (VRE) and electric energy storage (EES). By using a net load duration curve approach, we formulate a least-cost optimization model in which EES is only limited by its power capacity. We solve this problem analytically and find least-cost and market equilibrium conditions that lead to the optimal capacities of VRE and EES. We show that, mathematically, an electricity price structure that depends on the period of the year (i.e. EES charging or discharging, VRE curtailment, load shedding) and on investments costs leads to cost recovery for VRE and EES. We show that when EES is the marginal technology (either charging or discharging) the price must be non-zero. More specifically, the equilibrium prices during EES charge or discharge are functions of the EES and VRE fixed costs. We confirm our analytical findings using a numerical model. We argue that, although the system we study is hypothetical and simplified, our findings provide insights and research directions for how to recover fixed costs in a future electricity market based on VRE and EES only.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.179
Teacher spread0.175 · 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