An investigation of solar energy potential towards improving agriculture using angstrom and newly developed analytical models: In case of The Gambia

Abstract

Cleaner and affordable energy demand in The Gambia has gained a lot of prominence in recent years, with many people shifting towards solar PV installation. However, the interest in utilizing solar energy has continued to witness a remarkable setback in developing countries due to economic factors and the limitations of in situ measurements. The latter has steered researchers to explore empirical models to predict global solar radiation with the aid of available meteorological data. This study estimates monthly global solar radiation (HG) using the modified Angstrom models and a newly developed model at two locations in The Gambia using secondary data collected from the Yundum and Basse meteorological stations for twenty years (2000–2019) to evaluate the prospects for the siting and implementing of solar projects. The results ranged from 9.0-27.0 MJm−2day−1 or 2.5–7.5 kWh/m2/day for Yundum and 8.0–28.0 MJm−2day−1 or 2.2–7.8 kWh/m2/day for Basse. The models’ results were also compared with the solar resource maps and GIS data for The Gambia locations and tested with the statistical tools of Root mean square error, Correlation coefficient, Normalized mean square error, and Mean percentage error to validate their performances and found to show a good agreement on monthly basis. However, the success of these models drastically declined when estimated on daily or hourly basis. The potential of utilizing the outcome in the agriculture sector of the economy was also x-rayed and justified. Even the lowest value of 8.0 MJm−2day−1which occurred in December has the potential of generating solar energy. This signifies that solar energy can be explored to make up for the energy shortfall in The Gambia's agriculture and other sectors of the economy. The modified Angstrom equations for Yundum and Basse and our new model used in estimating the HG and the regression parameters can be applied to estimate the HG for the subsequent years at the same locations. We recommend that similar studies be conducted at other locations using our newly developed model for comparison and generality of the result.