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Record W4406732690 · doi:10.1016/j.renene.2025.122456

Techno-economic evaluation of electricity pricing structures on photovoltaic and photovoltaic-battery hybrid systems in Canada

2025· article· en· W4406732690 on OpenAlexafffundabout
Seyyed Ali Sadat, Joshua M. Pearce

Bibliographic record

VenueRenewable Energy · 2025
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemBattery (electricity)ElectricityStand-alone power systemPhotovoltaicsAutomotive engineeringRooftop photovoltaic power stationEnvironmental economicsElectricity pricingEnvironmental sciencePhotovoltaic mounting systemEngineeringElectrical engineeringBusinessRenewable energyEconomicsElectricity marketDistributed generationPower (physics)Maximum power point trackingPhysics

Abstract

fetched live from OpenAlex

There is limited understanding of how electricity market fluctuations and dynamics, such as changes in electricity pricing schemes and rate structures impact the profitability of hybrid battery and solar photovoltaic (PV) systems. This study provides a techno-economic evaluation of PV and hybrid PV-battery systems using the Solar Alone Multi-objective Advisor (SAMA), an open-source tool used for optimally sizing PV-based systems. The study focuses on the economic implications of time of use (ToU) and tiered rate (TR) pricing structures in Ontario, Canada and examines the potential impact of an investment tax credit. Furthermore, a sensitivity analysis is completed, which evaluates fluctuating battery costs and grid escalation rates, provides new insights into the financial viability of hybrid systems under various economic conditions. The results show the substantial influence of these rate structures, with ToU pricing generally proving more economically advantageous compared to TR pricing. While net-metered PV systems are increasingly attractive due to favorable economic metrics, the addition of battery storage under current cost conditions in Ontario remains less viable. The results support the importance of rate structures to enhance the economic viability of distributed PV systems to help achieve sustainable development goals.

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 score0.299
Threshold uncertainty score0.733

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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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

Citations19
Published2025
Admission routes3
Has abstractyes

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