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Record W4411534960 · doi:10.3390/en18133265

A Review of Phase-Change Material-Based Thermal Batteries for Sustainable Energy Storage of Solar Photovoltaic Systems Coupled to Heat Pumps in the Building Sector

2025· review· en· W4411534960 on OpenAlexafffund
Shafquat Rana, Joshua M. Pearce

Bibliographic record

VenueEnergies · 2025
Typereview
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemThermal energy storagePhase-change materialProcess engineeringEnergy storageEnvironmental scienceRenewable energyFossil fuelSolar energyAutomotive engineeringEngineeringEngineering physicsPower (physics)Phase changeElectrical engineeringWaste management

Abstract

fetched live from OpenAlex

Buildings account for about a third of global energy and it is thus imperative to eliminate the use of fossil fuels to power and provide for their thermal needs. Solar photovoltaic (PV) technology can provide power and with electrification, heating/cooling, but there is often a load mismatch with the intermittent solar supply. Electric batteries can overcome this challenge at high solar penetration rates but are still capital-intensive. A promising solution is thermal energy storage (TES), which has a low cost per unit of energy. This review provides an in-depth analysis of TES but specifically focuses on phase change material (PCM)-based TES, and its significance in the building sector. The classification, characterization, properties, applications, challenges, and modeling of PCM-TES are detailed. Finally, the potential for integrating TES with PV and heat pump (HP) technologies to decarbonize the residential sector is detailed. Although many studies show proof of carbon reduction for the individual and coupled systems, the integration of PV+HP+PCM-TES systems as a whole unit has not been developed to achieve carbon neutrality and facilitate net zero emission goals. Overall, there is still a lack of available literature and experimental datasets for these complex systems which are needed to develop models for global implementation as well as studies to quantify their economic and environmental performance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.058
GPT teacher head0.337
Teacher spread0.279 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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