Energy Pricing in Developing Countries

Nada, Sara; Hamed, Mohamad

doi:10.4236/oalib.1100869

Cited by 2 publications

(1 citation statement)

References 1 publication

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“…On the other hand, many developing countries use Inclining Block Rate tariff IBR for electrical power pricing for residential buildings [24]. IBR classi es consumed energy during the month into different categories.…”

Section: Real-time Shemssmentioning

confidence: 99%

Assessing Photovoltaic Power Uncertainty in Low-income Smart Home Energy Management using Geographic Information Systems Data

El-Azab

Saif

Metwally

et al. 2023

Preprint

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Solar-powered homes can be an optimal solution for the lack of continuous power sources problem in initial low-income communities. However, the challenge of PV uncertainty can make it difficult to coordinate this vital solar energy in real-time. This paper proposes a new, low-cost solution for assessing the uncertainty of photovoltaic power generation in smart home energy management systems. The proposed index, inspired by the well-known clearness index, is an adaptive deterministic indicator that only requires free Geographic Information System GIS models and PV power measurement, without the need for expensive high-tech controllers or expert engineers/programmers. The proposed index successfully predicts the daily PV energy with errors of less than 3% for more than 93% of studied days, according to the 2020 measured solar radiation of the studied case.

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Section: Real-time Shemssmentioning

confidence: 99%

Assessing Photovoltaic Power Uncertainty in Low-income Smart Home Energy Management using Geographic Information Systems Data

El-Azab

Saif

Metwally

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Adaptive cloudiness index for enhanced photovoltaic energy prediction and management in low-income smart homes using geographic information system

Elazab,

Saif,

Metwally

et al. 2024

Discov Appl Sci

View full text Add to dashboard Cite

Solar-powered homes can be an optimal solution for the lack of continuous power sources problem in initial low-income communities. However, the challenge of Photovoltaic (PV) uncertainty can make it difficult to coordinate this vital solar energy in real-time. This paper proposes a new, low-cost solution for assessing the uncertainty of photovoltaic power generation in smart home energy management systems. The proposed index, inspired by the well-known clearness index, is an adaptive deterministic indicator that only requires free Geographic Information System (GIS) models and PV power measurement, without the need for expensive high-tech controllers or expert engineers/programmers. The proposed index successfully predicts the daily PV energy with errors of less than 3% for more than 93% of studied days, according to the 2020 measured solar radiation of the studied case in an African developing location, i.e. Cairo. Egypt.

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Energy Pricing in Developing Countries

Cited by 2 publications

References 1 publication

Assessing Photovoltaic Power Uncertainty in Low-income Smart Home Energy Management using Geographic Information Systems Data

Assessing Photovoltaic Power Uncertainty in Low-income Smart Home Energy Management using Geographic Information Systems Data

Adaptive cloudiness index for enhanced photovoltaic energy prediction and management in low-income smart homes using geographic information system

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