article · IEEE Access
Accurate parameter estimation in photovoltaic modules is essential to evaluate and optimise the electrical power supplied to electricity grids. The Forensic-Based Investigation Algorithm, an optimisation method inspired by police inquiry and pursuit procedures, can determine the unknown electrical parameters across single-diode, double-diode, and triple-diode solar cell models. Across these configurations, the algorithm identifies five, seven, and nine operational parameters while accounting for system losses. Numerical assessments carried out under fluctuating solar irradiance and temperature conditions demonstrate the technique on commercial Photowatt-PWP 201 and Kyocera KC200GT panels. When benchmarked against alternative contemporary optimisers, the approach delivered standard deviations below 10 to the power of minus six over thirty experimental runs. These results confirm the method delivers highly consistent and competitive performance for photovoltaic parameter extraction.
Solar panels lose energy through internal physical mechanisms that vary with heat and sunlight. Accurately determining internal electrical properties helps engineers model panel behaviour and maximise the electrical power delivered into power grids. A consistent, highly precise algorithm ensures that solar energy systems can be simulated, assessed, and operated reliably across changing real-world environmental conditions.
This algorithm serves computational modelling needs for engineers and system planners seeking to optimise solar generation feeds into electricity networks. The testing used real data from commercially available modules, specifically Photowatt-PWP 201 and Kyocera KC200GT units. However, because the study focuses purely on numerical simulations and algorithmic benchmarking, the technology remains at an applied research stage rather than an integrated commercial tool or deployment-ready software package.
AI-generated from the published abstract. Always read the original work before citing.
The accurate parameter extraction of photovoltaic (PV) module is pivotal for determining and optimizing the energy output of PV systems into electric power networks. Consequently, a Photovoltaic Single-Diode Model (PVSDM), Double Diode Model (PVDDM), and Triple- Diode Model (PVTDM) is demonstrated to consider the PV losses. This article introduces a new application of the Forensic-Based Investigation Algorithm (FBIA), which is a new meta-heuristic optimization technique, to accurately extract the electrical parameters of different PV models. The FBIA is inspired by the suspect investigation, location, and pursuit processes that are used by police officers. The FBIA has two phases, which are the investigation phase applying by the investigators team, and the pursuit phase employing by the police agents team. The validity of the FBIA for PVSDM, PVDDM, and PVTDM is commonly considered by the numerical analysis executing under diverse values of solar irradiations and temperatures. The optimal five, seven, and nine parameters of PVSDM, PVDDM, and PVTDM, respectively, are accomplished using the FBIA and compared with those manifested by various optimization techniques. The numerical results are compared for the marketable Photowatt-PWP 201 polycrystalline and Kyocera KC200GT modules. The efficacy of the FBIA for the three models is properly carried out checking its standard deviation error with that obtained from various recently proposed optimization techniques in 2020 which are Jellyfish search (JFS) optimizer, Manta Ray Foraging optimizer (MRFO), Marine Predators Algorithm(MPA), Equilibrium Optimizer (EO), Heap Based Optimizer (HBO). The standard deviations of the fitness values over 30 runs are developed to be less than $1 \times 10^{-6}$ for the three models, which make the FBIA results are extremely consistent. Therefore, FBIA is foreseen to be a competitive technique for PV module parameter extraction.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1109/access.2020.3046536
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
