Performance analysis of a grid connected photovoltaic system in northeastern Brazil

Lima, Lutero Carmo de; Ferreira, Luiz Alves; Morais, Francisco Hedler Barreto de Lima

doi:10.1016/j.esd.2017.01.004

Cited by 168 publications

(84 citation statements)

References 22 publications

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“…Energy Generated by the Solar PV System. The total daily, monthly, and yearly alternating current (AC) energy generated by the solar PV system over a given period can be obtained as [22,31]…”

Section: Performance Parametersmentioning

confidence: 99%

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Comparative Performance Analysis of Grid-Connected PV Power Systems with Different PV Technologies in the Hot Summer and Cold Winter Zone

2018

International Journal of Photoenergy

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The objective of this paper is to establish the performance of 8 kWp grid-connected photovoltaic (PV) power systems based on different PV module technologies in Nanjing, China. Nanjing has a hot summer and a cold winter which are considered based on monthly average solar irradiation and ambient temperature specifically for the deployment of grid-connected PV systems. The study focuses on performance assessment of grid-connected PV systems using typical PV modules made of monocrystalline silicon (m-Si), polycrystalline silicon (p-Si), edge-defined film-fed growth silicon (EFG-Si), cadmium telluride (CdTe) thin film, copper indium selenide (CIS) thin film, heterojunction with intrinsic thin layer (HIT), and hydrogenated amorphous silicon single-junction (a-Si:H single-PV) installed on location. The yearly average energy output, PV module and system efficiency, array yield, final yield, reference yield, performance ratio, monthly average array capture losses, and system losses of seven PV module technologies are all analyzed. The results show that grid-connected PV power system performance depends on geographical location, PV module types, and climate conditions such as solar radiation and ambient temperature. In addition, based on energy output and efficiency, the HIT PV power technology can be considered as the best option and CdTe and p-Si as the least suitable options for this area. The monthly average performance ratio of the CdTe technology was higher than those of other technologies over the monitoring period in Nanjing.

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Section: Performance Parametersmentioning

confidence: 99%

“…They found that 49% of total on-farm electricity consumption came from renewable energy. Lima et al [22] carried out a performance analysis of a 2.2 kW p PV system installed at the State University of Ceará, Fortaleza, Brazil. The results showed that the PV systems performed well.…”

Section: Introductionmentioning

confidence: 99%

Comparative Performance Analysis of Grid-Connected PV Power Systems with Different PV Technologies in the Hot Summer and Cold Winter Zone

2018

International Journal of Photoenergy

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“…In the literature, many studies have investigated, evaluated, and analyzed PV grid-connected systems in different locations, such as India [1], Italy [2], Ireland [3], Ghana [4], Iran [5], Brazil [6], Mauritania [7], Korea [8], Greece [9], and Morocco [10].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of a 20 MW Grid-Connected Photovoltaic Installation in Adrar, South of Algeria

Aoun¹

2020

Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems

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This chapter presents the performance of a 20 MWp grid-connected PV system installed in a harsh environment, Adrar in the South of Algeria. The results were monitored over a period of 1 year, from January 2018 to December 2018. The PV system assessment includes final and reference yields, system efficiency, performance ratio, capacity factor, and total system losses. The total yearly energy delivered to the grid was 35892.22 MWh, and the monthly average reference and final yields of the system are in the range 5.92-8.1 (h/day) and 4.39-5.56 (h/day), respectively. Furthermore, the annual average daily PV system efficiency, performance ratio, capacity factor, and total losses were 10.82%, 71.71%, 20.76%, and 2.04 h/day, respectively.

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“…Some of the recent research on PV fault detection algorithms is based on the irradiance-power linear regression method. This method improves the low recognition rate problem for small irradiation values [8,9]. Additionally, a temperature correction output formula can compensate for the fluctuation value of the output power and will improve variability problems when calculating the output power value.…”

Section: Introductionmentioning

confidence: 99%

On-Line Diagnosis and Fault State Classification Method of Photovoltaic Plant

Shin¹,

Kim²

2020

Energies

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This paper presents an on-line diagnosis method for large photovoltaic (PV) power plants by using a machine learning algorithm. Most renewable energy output power is decreased due to the lack of management tools and the skills of maintenance engineers. Additionally, many photovoltaic power plants have a long down-time due to the absence of a monitoring system and their distance from the city. The IEC 61724-1 standard is a Performance Ratio (PR) index that evaluates the PV power plant performance and reliability. However, the PR index has a low recognition rate of the fault state in conditions of low irradiation and bad weather. This paper presents a weather-corrected index, linear regression method, temperature correction equation, estimation error matrix, clearness index and proposed variable index, as well as a one-class Support Vector Machine (SVM) method and a kernel technique to classify the fault state and anomaly output power of PV plants.

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Performance analysis of a grid connected photovoltaic system in northeastern Brazil

Cited by 168 publications

References 22 publications

Comparative Performance Analysis of Grid-Connected PV Power Systems with Different PV Technologies in the Hot Summer and Cold Winter Zone

Comparative Performance Analysis of Grid-Connected PV Power Systems with Different PV Technologies in the Hot Summer and Cold Winter Zone

Performance Analysis of a 20 MW Grid-Connected Photovoltaic Installation in Adrar, South of Algeria

On-Line Diagnosis and Fault State Classification Method of Photovoltaic Plant

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