Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 31 min ago
Peer-reviewedCC BY 3.0Ees Solar

Validating and comparing reported indoor photovoltaic performance

  1. 1Centre for Integrative Semiconductor Materials (CISM) and Department of Physics, Swansea University Bay Campus Swansea SA1 8EN UK

Abstract

Indoor photovoltaics (PVs) have garnered significant attention in recent years as promising power sources for wireless Internet-of-Things devices. However, the use of unstandardised testing practices makes it difficult to compare reported performance metrics. Discrepancies between experimental apparatus and methodologies can arise in a number of ways, including non-standard light sources with varying spectral irradiance (irrespective of the colour temperature or the colour-rendering index), spectral deviations induced during light attenuation, spatial non-uniformities, and temporal instability and an angular distribution of the light source. Unstandardised practices lead to variations in the spectral shape and light power impinging on a PV device, resulting in variations in the output current and power conversion efficiency. In this contribution, we explore the imprecision that arises when comparing previously reported unstandardised measurements. By quantifying and combining different sources of measurement imprecision, retrospective thermodynamic analyses are used to validate reported measurements for a variety of established and next-generation PV systems. These retrospective analyses allow each measurement to be categorised as either thermodynamically valid, plausible, or implausible. Ultimately, our investigations clarify the current upper bounds of state-of-the-art indoor PV performance, with the maximum validated power conversion efficiencies of the indoor PVs we consider being 40.3%, 29.2%, and 40.9% for perovskite, organic, and inorganic semiconductor-based systems, respectively.

Related

  1. Charge-Transfer-State Descriptors from Donor–Acceptor Interfaces Enable Improved Prediction of Indoor Organic Photovoltaic Efficiency
    Anagh Mukherjee
    ChemRxivPreprintCC BYFull textGeneral chemistryChemRxiv
  2. Discovery of germanium-based hybrid perovskites with high photovoltaic performance with machine-learning
    Carrie Song, R. X. Lian, H. Zhang +1
    RSC advancesPeer-reviewedCC BY-NCFull textMaterials & polymersEurope PMCPMC
  3. Validating Spectral Quality Measures as Proxies for Task Performance: A Controlled-Perturbation Framework for Raman Spectroscopy
    Xiuyi Qin
    arXivPreprintCC BY 4.0Full textPhysical chemistryComputational physicsarXiv
  4. Effect of Ga Doping on Microwave-Assisted Synthesized TiO2 Nanoparticles and their Photovoltaic Performance as DSSC Photoanodes
    J. Arriola-Oliva, E. Regalado-Pérez, U. Pal +1
    ACS OmegaPeer-reviewedCC BY 4.0Full textGeneral chemistryCrossref
  5. Developing a Quantum Physics-Inspired Machine Learning Model for Partition Coefficient Prediction and Comparing Its Performance with Empirical Descriptors and Molecular Graph-Based Models
    Abhishek Tripathi, Riya Rajput, Mohammad Seraj +2
    ACS OmegaPeer-reviewedCC BY-NC-ND 4.0Full textGeneral chemistryCrossref
BibTeX
@article{kay2026validating,
  title = {{Validating and comparing reported indoor photovoltaic performance}},
  author = {Austin M. Kay and Gregory Burwell and Drew B. Riley and Paul Meredith},
  journal = {Ees Solar},
  year = {2026},
  month = oct,
  doi = {10.1039/d6el00150e},
  url = {https://doi.org/10.1039/d6el00150e},
  note = {CC BY 3.0},
}
RIS
TY  - JOUR
TI  - Validating and comparing reported indoor photovoltaic performance
AU  - Austin M. Kay
AU  - Gregory Burwell
AU  - Drew B. Riley
AU  - Paul Meredith
PY  - 2026
DA  - 2026/10/27
JO  - Ees Solar
DO  - 10.1039/d6el00150e
UR  - https://doi.org/10.1039/d6el00150e
AB  - Indoor photovoltaics (PVs) have garnered significant attention in recent years as promising power sources for wireless Internet-of-Things devices. However, the use of unstandardised testing practices makes it difficult to compare reported performance metrics. Discrepancies between experimental apparatus and methodologies can arise in a number of ways, including non-standard light sources with varying spectral irradiance (irrespective of the colour temperature or the colour-rendering index), spectral deviations induced during light attenuation, spatial non-uniformities, and temporal instability and an angular distribution of the light source. Unstandardised practices lead to variations in the spectral shape and light power impinging on a PV device, resulting in variations in the output current and power conversion efficiency. In this contribution, we explore the imprecision that arises when comparing previously reported unstandardised measurements. By quantifying and combining different sources of measurement imprecision, retrospective thermodynamic analyses are used to validate reported measurements for a variety of established and next-generation PV systems. These retrospective analyses allow each measurement to be categorised as either thermodynamically valid, plausible, or implausible. Ultimately, our investigations clarify the current upper bounds of state-of-the-art indoor PV performance, with the maximum validated power conversion efficiencies of the indoor PVs we consider being 40.3%, 29.2%, and 40.9% for perovskite, organic, and inorganic semiconductor-based systems, respectively.
SN  - 3033-4063
ER  -