Renewable energy has become of utmost importance in the current wake of decreasing levels of fossil fuels and also because of the high percentages of CO2 build-up in the environment. Nowadays there is an increasing trend in the use of solar energy by using photovoltaic (PV). In this paper Artificial Bee Colony algorithm is used for Maximum Power Point Tracking and its performance is compared with Perturb and Observe algorithm.
Abstract. Solar radiation data plays an important role in pre-feasibility studies of solar electricity and/or thermal system installations. Measured solar radiation data is scarcely available due to the high cost of installing and maintaining high quality solar radiation sensors (pyranometers). Indirect measured radiation data received from geostationary satellites is unreliable at latitudes above 60 degrees due to the resulting flat viewing angle. In this paper, an empirical method to estimate solar radiation based on minimum climatological data is proposed. Eight sites in Norway are investigated, all of which lie above 60 N. The estimations by the model are compared to the ground measured values and a correlation coefficient of 0.88 was found while over all percentage error was −1.1%. The proposed models is 0.2% efficient on diurnal and 10.8% better in annual estimations than previous models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.