Photovoltaic Temperature Estimation Model for Rapid Irradiance Change Conditions in Tropical Regions Using Heuristic Algorithms

Srivatsan, R.; Jiang, Lijing; Maskell, Douglas L.

doi:10.1109/pvsc.2017.8521510

Cited by 1 publication

(2 citation statements)

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“…In ( 8), 𝐋𝐛𝐞𝐬𝐭 𝒋,𝒊 𝒌 represents personal or local best ith component of jth individual; 𝐆𝐛𝐞𝐬𝐭 𝒃 𝒌 whereas represents bth component of the best individual of population up to iteration k. Furthermore, in (8), Ir is the inertia weight of the velocity of the population defined in (10). The values of inertial factor Ir used to decrease linearly from Ir,max to Ir,min as iteration advances from starting towards its maximum value set.…”

Section: Parallel Ann-pso Algorithmmentioning

confidence: 99%

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Application of Parallel ANN-PSO to Hourly Solar PV Estimation

Cho¹,

Lee²,

Chang³

2021

Preprint

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Based on collected power generation data associated with solar irradiance, PV system conversion efficiency and cell temperature, an hourly solar PV power estimation model by a parallel artificial neural network (ANN) and particle swarm optimization (PSO) algorithm is proposed. Weight matrices related to different seasons and geographic areas for estimation power generations have been trained by real measured operation data. The parallel PSO algorithm with heuristic global optimization technique assists the ANN training process to get near optimal solutions precisely. The accuracy and reliability of estimation is audited by actual details of photovoltaic power stations in various regions and scales. The results of estimation model can not only assist the electricity dispatcher to explicitly monitor the trend of solar power generation in different areas, but also coordinate with traditional power plants to meet load demand more accurately. The presented model will bring benefits to power dispatching for larger scales of intermittent and unstable solar power generation.

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Section: Parallel Ann-pso Algorithmmentioning

confidence: 99%

“…Much research has been devoted in finding optimum solutions by PSO algorithm associated with solar PV estimations. PSO is used to improve the accuracy of a simple physical dynamic model [8]. The effectiveness of the proposed PSO-based parameter estimation for the RC circuit model is verified using an experimental dataset.…”

Section: Introductionmentioning

confidence: 99%