A Typical Meteorological Year Generation Based on NASA Satellite Imagery (GEOS-I) for Sokoto, Nigeria

Abstract

Computer simulation of buildings and solar energy systems are being used increasingly in energy assessments and design. This paper evaluates the typical meteorological year (TMY) for Sokoto, northwest region, Nigeria, using 23-year hourly weather data including global solar radiation, dew point temperature, mean temperature, maximum temperature, minimum temperature, relative humidity, and wind speed. Filkenstein-Schafer statistical method was utilized for the creation of a TMY for the site. The persistence of mean dry bulb temperature and daily global horizontal radiation on the five candidate months were evaluated. TMY predictions were compared with the 23-year long-term average values and are found to have close agreement and can be used in building energy simulation for comparative energy efficiency study.

A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China

“…The assigned weighting factors are shown in Table 2. In the second stage, among various methods [10,25] for selecting TMMs from the five candidate months, a simpler selection process [26,42], starting with calculation of the root mean square difference (RMSD), is adopted. The RMSD is defined as follows:…”

The Generation of Typical Meteorological Year for Tripoli, Libya

“…It consists of the months selected from the individual years and concatenated to form a complete year. Many methods have been made to produce such weather databases for different locations around the world [1, 4,5,6,7] Center for Solar Energy Research and Studies (CSERS) is the main renewable energy R&D organization in Libya. It was founded in 1978.…”

“…In the past, several methodologies for generating TMYs have been reported, such as Sandia method, Festa-Ratto method, Danish method and others [6], all targeted at selecting single months or years from a long-term typical weather condition. Among the different TMY generation methods, the Sandia method is widely adopted [1, [3][4][5][6][7][8][9][10][11][12][13][14] generated TMYs for different locations with different weather parameters and assigned weighting factors. This methodology has been adopted by different countries: for example, by date of publication, for Latvia [9], Athens, Greece [12], Oman [11], Damascus, Syria [6], Nigeria [3,[7][8], Chile [10], Istanbul, Turkey [14], and Armidale NSW, Australia [14].…”

“…Among the different TMY generation methods, the Sandia method is widely adopted [1, [3][4][5][6][7][8][9][10][11][12][13][14] generated TMYs for different locations with different weather parameters and assigned weighting factors. This methodology has been adopted by different countries: for example, by date of publication, for Latvia [9], Athens, Greece [12], Oman [11], Damascus, Syria [6], Nigeria [3,[7][8], Chile [10], Istanbul, Turkey [14], and Armidale NSW, Australia [14]. Methods in above literatures are in fact similar, the main differences lie in the numbers of daily indices (weather indices) to be included and their assigned weightings [3,13].…”

Proposal and evaluation of typical illuminance year (TIY) generation procedures from illuminance or irradiance data for daylight assessment in the long term

“…Petrakis et al (1998) used it for the generation of a TMY for Nicosia (Cyprus),Sawaqed et al (2005) for the development of TMYs for 7 locations in Oman andOhunakin et al (2014) to obtain a TMY for Sokoto (Nigeria).…”