Performance analysis of the first photovoltaic grid-connected system in Algeria

Bouacha, Saida; Malek, A.; Benkraouda, O.; Arab, A. Hadj; Razagui, Abdelhak; Boulahchiche, Saliha; Semaoui, Smail

doi:10.1016/j.esd.2020.04.002

Cited by 33 publications

(19 citation statements)

References 30 publications

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“…Performance ratio (PR) is calculated by dividing the system's final yield to the system's reference yield. It can be calculated also by the ratio of energy fed into the utility grid to the rated power of solar panel [9,16] and it is given as:…”

Section: Performance Ratiomentioning

confidence: 99%

“…Capacity factor (C f ) is also known as load factor it is defined by dividing the actual AC energy produced by the energy that would have been produced if the plant operated at maximum rating for 24 hours per day. It is given as [12,16,17].…”

Section: Capacity Factormentioning

confidence: 99%

“…The system losses denoted by (Ls) is the inverter losses [9,16,17]. It is calculated as…”

Section: System Lossesmentioning

confidence: 99%

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Performance Investigation of On-Grid Solar Photovoltaic System in Eskişehir/Turkey

Adan¹,

Filik²

2021

Deu Muhendislik Fakultesi Fen Ve Muhendislik

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The paper presents a performance investigation of a 3-kW grid interactive photovoltaic system located at Eskişehir Technical University using PVSYST program. The system has 260 , 12 PV modules and is connected to a 3-kW inverter. Parameters like the energy from PV panels, energy fed to the utility grid, performance ratio and final yield per installed is presented. The system produces 4839 kWh/year and injects 4648 kWh/year into the utility grid. It has a performance ratio of 84.8% and the specific production of 4.08 kWh/ /day. The specific production is compared to other systems in the literature review around the world. The paper concludes that Eskişehir region has a better solar energy potential than most places in Europe but not as good as the solar PV systems located in Africa or Asia.

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Section: Performance Ratiomentioning

confidence: 99%

Section: Capacity Factormentioning

confidence: 99%

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Performance Investigation of On-Grid Solar Photovoltaic System in Eskişehir/Turkey

Adan¹,

Filik²

2021

Deu Muhendislik Fakultesi Fen Ve Muhendislik

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“…Kymakis et al (2009) evaluated the performance of a grid-connected PV park on the island of Crete, with a peak power of 171.36 kWp; the study showed that the Park supplied 229 MWh to the grid during 2007, and the energy supplied ranged from 335.48-869.68 kWh. Bouacha et al (2020) presented an experimental performance analysis based on results attained from monitoring a 9.5 kWp PV grid-connected solar system for three years. Their results showed that the annual average final yield for the system was 3.37 h/day.…”

Section: Introductionmentioning

confidence: 99%

The electrical energy impact of small-scale onsite generation: A case study of a 75 kWp grid-tied PV system

Mhundwa

Simon

Yongoua

2020

J. energy South. Afr.

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This study presents an analysis of a 75 kWp grid-tied solar photovoltaic (PV) system with a grid tie limiter to provide energy requirements for an aquaculture centre in the Eastern Cape province of South Africa. A data acquisition system, comprising power and energy consumption meters, was deployed to measure solar PV generation, demand for the facility, and energy drawn from the utility grid. Statistical analysis was conducted on the data to determine the impact of the solar PV plant in reducing demand from the utility grid throughout the day, and this was extrapolated into monthly and annual contributions by the PV system to meeting the energy requirements. Findings reveal that the annual energy yield for the system was 1 864.29 kWh/kWp. The solar contribution to the total load requirement on a 24 hour cycle was 28% (139.82 MWh) from July 2018 to June 2019. Summer and winter average contributions by the PV system were 62% and 57% respectively for the period of 05:30–18:30. The mean monthly solar fraction for operating the farm between sunrise and sunset was 0.44. Furthermore, a total of 141.07 tCO2 has been avoided due to the operation of the PV system.

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“…For renewable energy supply assessment, it is important that analysis does not simply report peak demand, as increasingly, the variation in demand and its relationship to production becomes more important [16]. To this end, a method is required to estimate time series demand that is unconstrained by suppressed demand data.…”

Section: Introductionmentioning

confidence: 99%

A bottom-up weather-sensitive residential demand model for developing countries. A case study of Abuja, Nigeria

Oluwole

Collin

Weijde

et al. 2020

Energy for Sustainable Development

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The frequency of power outages being experienced in Sub-Saharan Africa mean that traditional methods of electricity demand forecasting which rely on directly observed demand data are inadequate for use in projections. Nevertheless, accurate forecasting methods are urgently required to ensure efficient power system operations and expansion planning. To address this gap, we develop a novel method to estimate unsuppressed electricity demand for developing countries. This follows a bottom-up approach based on socioeconomic data and a time-use database developed from a householder survey, which are used to generate household profiles using a Markov Chain approach. These profiles are then converted into electrical load time series by a series of appliance models, using reanalysis weather data to accurately represent ambient conditions for the generation of cooling demand profiles. We apply our method to a Nigerian case study, obtaining the first time series of unsuppressed residential electricity demand for the country using the first Time-of-Use Survey (TUS) for Nigerian households. We validate our model outputs using the results of a small-scale residential metering trial, which yielded a correlation coefficient of 0.97, RMSE of 0.04, and percentage error of 6% between measured and model data. This evidences that our method is a credible and practical tool for electrical demand studies in developing countries. Using the model, the forecasted domestic demand for Abuja Electricity Distribution Company ranges between 345 and 575 MW, while that of Nigeria ranges between 3,829 and 6,605 MW

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Performance analysis of the first photovoltaic grid-connected system in Algeria

Cited by 33 publications

References 30 publications

Performance Investigation of On-Grid Solar Photovoltaic System in Eskişehir/Turkey

Performance Investigation of On-Grid Solar Photovoltaic System in Eskişehir/Turkey

The electrical energy impact of small-scale onsite generation: A case study of a 75 kWp grid-tied PV system

A bottom-up weather-sensitive residential demand model for developing countries. A case study of Abuja, Nigeria

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