Development of typical meteorological year for massive renewable energy deployment in Togo

Amega, Kokou; Lare, Yendoubé; Moumouni, Yacouba; Bhandari, Ramchandra; Madougou, Saïdou

doi:10.1080/14786451.2022.2109026

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…This section presents people's demand for electricity whether in residential, commercial, public services and industry and the provision made to satisfy that need. The assessment reveals that Togo lacks enough electrical energy to meet its growing demand, as access to electricity is still limited [ 68 ]. Notably, Fig.…”

Section: Resultsmentioning

confidence: 99%

Power system transformation in emerging countries: A SWOT/PESTLE analysis approach towards resiliency and reliability

Amega,

Moumouni,

Laré

et al. 2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

Power system transformation in emerging countries: A SWOT/PESTLE analysis approach towards resiliency and reliability

Amega,

Moumouni,

Laré

et al. 2024

Heliyon

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Typical meteorological year data analysis for optimal usage of energy systems at six selected locations in Nigeria

Kilanko

Sunday

Joseph

et al. 2023

International Journal of Low-Carbon Technologies

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In this study, the Typical Meteorological Year (TMY) data for six locations representing the 6 geo-political zones in Nigeria were generated and analyzed using the Sandia Method. The analysis shows that seasonal variations exist in all the selected locations indicating two distinct seasons: the dry and wet seasons with varying lengths from north to south of the country. Due to its high global radiation levels (21–25 MJ/m2/day), the North is a desirable location for solar-thermal systems. Also, the high monthly mean temperature variations (about 18°C), low relative humidity (15%) and constant wind speeds (4m/s) experienced in the first three months of the year aid the installation of wind energy systems and the application of evaporative cooling techniques that reduce the thermal load and energy consumption of buildings. On the other side, the high relative humidity (80%) and mediocre radiation values derived almost throughout the year in the South-west, South-east and South-south regions discourages the extensive application of evaporative cooling and solar energy based systems in such locations, but the moderate wind speeds (2.9 m/s) and monthly mean temperature variations associated with these regions between the first three months of the year allow for the application of natural ventilation and some passive cooling systems so as to reduce the thermal load of buildings in the regions. The information presented in this work can serve as a guide for design and selection of energy systems and application of energy-related projects in Nigeria.

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On the Summarization of Meteorological Data for Solar Thermal Power Generation Forecast

2023

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The establishment of the typical weather conditions of a given locality is of fundamental importance to determine the optimal configurations for solar thermal power plants and to calculate feasibility indicators in the power plant design phase. Therefore, this work proposes a summarization method to statistically represent historical weather data using typical meteorological days (TMDs) based on the cumulative distribution function (CDF) and hourly normalized root mean square difference (nRMSD). The proposed approach is compared with regular Sandia selection in forecasting the electricity produced by a solar thermal power plant in ten different Brazilian cities. Considering the determination of the annual generation of electricity, the results obtained show that when considering an overall average of weather characteristics, commonly used for analyzing solar thermal power plant designs, the normalized mean average error (nMAE) is 20.8 ± 4.8% relative to the use of historical data of 20 years established at hourly intervals. On the other hand, a typical meteorological year (TMY) is the most accurate approach (nMAE = 1.0 ± 1.1%), but the costliest in computational time (CT = 381.6 ± 56.3 s). Some TMD cases, in turn, present a reasonable trade-off between computational time and accuracy. The case using 4 TMD, for example, increased the error by about 11 percentual points while the computational time was reduced by about 81 times, which is quite significant for the simulation and optimization of complex heliothermic systems.

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Development of typical meteorological year for massive renewable energy deployment in Togo

Cited by 3 publications

References 28 publications

Power system transformation in emerging countries: A SWOT/PESTLE analysis approach towards resiliency and reliability

Power system transformation in emerging countries: A SWOT/PESTLE analysis approach towards resiliency and reliability

Typical meteorological year data analysis for optimal usage of energy systems at six selected locations in Nigeria

On the Summarization of Meteorological Data for Solar Thermal Power Generation Forecast

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