Cloud Resolution and Solar Location Diversity

The power output of solar farms is affected by meteorological factors such as cloud formation and cloud height. Cloud height influences the incident solar radiation because of the occlusion of incident solar radiation. It is important to be able to classify a solar farm site as having either maximum cloud occlusion or minimum cloud occlusion. This is important to determine the suitability of a site for hosting solar farms. In addition, the classification is important to determine tracker operation in tracker-enabled solar farm systems. The proposed research presents a sensor network integrated with a renewable solar energy power system. The sensor network comprises a ceilometer, photometer, and a test solar panel. In the proposed system, solar panels are connected to an IEEE 802.11 unlicensed network to enable the receipt of data for solar panel configuration. The proposed research presents how tracker enabled solar panel response to the sensor network-based data-driven inferences with benefits resulting in shorter tracker duration and reduced tracker related energy consumption. Performance evaluation shows that the proposed mechanism enhances energy output by 54%- 63% on average. Evaluation also shows that the overhead power consumption is reduced by 49%-63% on average.