Analysis of Shading Effects in Solar PV System

Bernadette, Dushengere; Twizerimana, Maurice; Bakundukize, Alexis; Pierre, Bizabakoraho Jean; Theoneste, Nsekambabaye

doi:10.11648/j.ijrse.20211002.13

Cited by 13 publications

(3 citation statements)

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“…In the photovoltaic current equation, Isc is the short-circuit current informed by the photovoltaic module manufacturer and λcoll is the incident solar radiation on the collector's plane given as kW/m². Considering the transposition factor (tf) [8] [9], the near shading factor (fnear) [10], the soiling factor (fsoiling) [11] [12] and the incidence angle modifier factor (fIAM) [13], the incident solar radiation on the (1) collectors plane (λcoll ) is calculated through eq. Erro!…”

Section: Mathematical Modelingmentioning

confidence: 99%

“…to the total power of the plant, in addition to the application of the European efficiency of the inverter [14]. Those losses are composed by degradation [15], heating losses [16], partial or complete shading losses [10] [15], module quality factor [15], light induced degradation [15], mismatch between modules and mismatch by voltage difference between strings [15] [17] and Joule losses in DC circuits [15]. This work proposes to include the effect of saturation in the output power of the inverter [18] to obtain the total output power (PAC) through the logic equation below:…”

Section: Mathematical Modelingmentioning

confidence: 99%

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Validation of Photovoltaic Model for Application in a Distributed Energy Source Using Weather Data

Pignaton¹,

Silva²,

Silva³

et al. 2023

Rev. Contemp.

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This work presents a photovoltaic model for a simulation of the electric energy production of a distributed energy system. The model will be validated through measured weather data and energy produced by an 88.04 kWp power plant installed on the Federal University of Espírito Santo (UFES) in Vitória. The validation consists of comparing the real power data acquired by the photovoltaic plant and the power data calculated from the model using weather data, specifications of the panels and inverters and the constructive characteristics of the system. The proposed model is based on the paper “Management of an island and grid-connected microgrid using hybrid economic model predictive control with weather data”, Applied Energy, v. 278, 2020, https://doi.org/10.1016/j.apenergy.2020.115581. In addition, the model has been improved with the inclusion of new intrinsic parameters of the material, the calculation of losses and the adjustments for different tilt angles and azimuth orientations. Results of this method reveal that the model was able to reproduce the behavior of the real photovoltaic plant, presenting a mean absolute percentage error of 8.8% between real and simulated data.

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Section: Mathematical Modelingmentioning

confidence: 99%

Section: Mathematical Modelingmentioning

confidence: 99%

Validation of Photovoltaic Model for Application in a Distributed Energy Source Using Weather Data

Pignaton¹,

Silva²,

Silva³

et al. 2023

Rev. Contemp.

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“…Hotspots occur due to junction diode failure; fires may even happen. Finally, an annual near shading loss of up to | 2 | % is an acceptable limit [40].…”

mentioning

confidence: 99%

Why Does the PV Solar Power Plant Operate Ineffectively?

Alhmoud

2023

Energies

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Quality, reliability, and durability are the key features of photovoltaic (PV) solar system design, production, and operation. They are considered when manufacturing every cell and designing the entire system. Achieving these key features ensures that the PV solar system performs satisfactorily and offers years of trouble-free operation, even in adverse conditions. In each cell, the quality of the raw material should meet the quality standards. The fulfillment of the quality management system requires every part that goes into the PV solar system to undergo extensive testing in laboratories and environments to ensure it meets expectations. Hence, every MWh of electricity generated by the PV solar system is counted, the losses should be examined, and the PV system’s returns should be maximized. There are many types of losses in the PV solar system; these losses are identified and quantified based on knowledge and experience. They can be classified into two major blocks: optical and electrical losses. The optical losses include, but are not limited to, partial shading losses, far shading losses, near shading losses, incident angle modifier (IAM) losses, soiling losses, potential induced degradation (PID) losses, temperature losses, light-induced degradation (LID) losses, PV yearly degradation losses, array mismatch losses, and module quality losses. In addition, there are cable losses inside the PV solar power system, inverter losses, transformer losses, and transmission line losses. Thus, this work reviews the losses in the PV solar system in general and the 103 MWp grid-tied Al Quweira PV power plant/Aqaba, mainly using PVsyst software. The annual performance ratio (PR) is 79.5%, and the efficiency (η) under standard test conditions (STC) is 16.49%. The normalized production is 4.64 kWh/kWp/day, the array loss is 1.69 kWh/kWp/day, and the system loss is 0.18 kWh/kWp/day. Understanding factors that impact the PV system production losses is the key to obtaining an accurate production estimation. It enhances the annual energy and yield generated from the power plant. This review benefits investors, energy professionals, manufacturers, installers, and project developers by allowing them to maximize energy generation from PV solar systems and increase the number of solar irradiation incidents on PV modules.

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