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Record W6959161214 · doi:10.7939/r3-jgnr-b764

Economic and Environmental Assessment of Large-scale Electro-chemical and Flywheel Energy Storage Systems for Stationary Applications

2022· dissertation· en· W6959161214 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsLife-cycle assessmentCost of electricity by sourceEnergy storageRenewable energyGreenhouse gasEnvironmental impact assessmentElectricity generationFlywheelEnergy conservationElectricity

Abstract

fetched live from OpenAlex

There are few cost and environmental feasibility assessments of energy storage systems for utility-scale applications. The development of techno-economic and environmental performance indicators is crucial to make an informed decision on future development and deployment of energy storage technologies. This thesis aims to address the knowledge and literature gaps in economic and environmental aspects of energy storage systems for stationary applications. Scientific principles-based techno-economic and life cycle assessment models were developed for seven energy storage technologies: sodium-sulfur (Na-S), lithium-ion (Li-ion), valve-regulated lead-acid (VRLA), nickel-cadmium (Ni-Cd), vanadium redox flow (VRF), steel rotor flywheel, and composite rotor flywheel. Four stationary application scenarios were evaluated. These are bulk energy storage, transmission and distribution investment deferral, frequency regulation, and support of voltage regulation. With the rapidly growing number of electric vehicles, vehicle-to-grid (V2G) technology can play an important role in stabilizing electricity grids. An assessment is necessary to develop performance metrics for the V2G system and compare it with stationary energy storage systems. Therefore, a special case for an electro-chemical energy storage system, V2G, was investigated to evaluate its techno-economic feasibility in Canadian weather conditions. The system components were designed in such a way that the power and energy of each application scenario are met. Then, cost functions were developed, followed by estimation of the life cycle cost and the levelized cost of storage (LCOS). The environmental assessment involves building material and energy inventories and translating them to net energy ratio (NER) and life cycle greenhouse gas (GHG) emissions values. The LCOS ranges from $199-$941/MWh for the Na-S, $180-$1032/MWh for the Li-ion, $410-$1184/MWh for the VRLA, $802-$1991/MWh for the Ni-Cd, and $267-$3794/MWh for the VRF, depending on the application scenario. The life cycle GHG emissions range from 715-784 kg-CO2eq/MWh for Na-S, 625-659 kg-CO2eq/MWh for Li-ion, 749-803 kg-CO2eq/MWh for VRLA, 742-806 kg-CO2eq/MWh for Ni-Cd, and 800-963 kg-CO2eq/MWh for VRF. Because they have a longer cycle life, lower capital cost, and higher energy density, Li-ion and Na-S energy storage systems outperform other battery storage technologies. The composite rotor flywheel has a higher LCOS ($189.94/MWh) than the steel rotor flywheel ($146.41/MWh), mainly due to the higher composite material cost compared to steel. However, with respect to the life cycle GHG emissions, the composite rotor flywheel has a higher performance (48.9-95.0 kg-CO2eq/MWh) than the steel rotor (75.2-121.4 kg-CO2eq/MWh), mainly due to the higher operational energy consumption in the steel rotor flywheel to compensate for the frictional loss. In the techno-economic assessment of the V2G system, the weather conditions in four Canadian provinces were considered. The LCOS values for the V2G system range from $176.97/MWh in Quebec to $233.08/MWh in Ontario when it is used for energy arbitrage. When the V2G system is used for frequency regulation, the LCOS values range from $271.42/MWh in Quebec to $329.93/MWh in Ontario. The LCOS varies by province mainly because of differences in electricity prices and average ambient temperatures. The framework developed in this research can be used for assessment of other energy pathways. Insights from the study will help industry and electric utility companies understand the economic and environmental performances of electro-chemical and flywheel energy storage systems and ultimately help them make informed policy and investment decisions.

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 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 score0.202
Threshold uncertainty score0.592

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 studies0.0000.000
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 head0.001
GPT teacher head0.154
Teacher spread0.153 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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