An effective control technique for automatic solar tracking

Abstract

Due to global climate change as a result of pollution caused by the burning of fossil fuels, the world has changed its view when it comes to power generation. The focus is now more on natural and clean energy, such as solar photovoltaic (PV) systems. An effective solar PV system is not a simple system, as the sun is not a stationery object. The sun moves from east to west daily, which makes the design and installation of an effective solar PV system challenging for optimal power harvesting. Harvesting of solar energy from a PV module efficiently is affected not only by varying environmental conditions, but also by the installation angles, load profile, latitude of the location of interest and energy management system. An energy management system may include a maximum power point tracker (MPPT) that is required to adjust a PV module’s output voltage to a value, which enables the maximum energy to be transferred to a given load. PV module energy conversion can further be increased by using solar tracking technologies. Tracking the sun to enable maximum output power from a PV module varies in complexity. However, it is essential to deliver the highest possible power to the load continuously when variations in the insolation and temperature occur, to maintain a high overall system efficiency. The purpose of this research study was to develop an effective control technique for an automatic solar tracking system in order to maximise the output power yield that may be obtained from a dual-axes tracking-type system. Three fixed-type PV modules (installed at tilt angles of latitude plus 10° (36°), latitude (26°) and latitude minus 10° (16°)) and the direct-tracking system (controlled by Boolean algorithm) served as the baseline for analysing the simulated power results of two selected algorithms (linear regression and fuzzy logic). These tilt angles are utilised based on the recommendations by Heywood and Chinnery in 1971. The Boolean algorithm is developed and programmed in a National Instruments (NI) LabVIEW user interface software to control three linear actuators to meet the requirements for a dual-axes tracker. The two algorithms (fuzzy logic and linear regression) are developed and simulated using Microsoft Excel. It took 41 functional blocks and four comparison calculations to develop and execute the direct-tracking system. For the direct-tracking system, two comparison calculations per axis of previous and current voltage readings were done to detect if the PV module should move forward or backwards. The direct-tracking system could move the PV module either forward or backward in both axes (X and Y). The LabVIEW user interface was also used to visualise the measured data. It was designed and developed for this research study pertaining to the operating parameters of PV modules and linear actuators. The system was installed on the top of the Euclid building at the University of South Africa (UNISA), Science Campus, Florida, Johannesburg. The global positioning system (GPS) coordinates of the building are 26, 1586° S, 27, 9033° E. It was discovered that the daily performance of the fixed system power (16° PV module) was better than the 26° and 36° fixed systems power by 3.49% and 10.69%, respectively. The direct-tracking system power showed 32% improvement over the fixed system power (16°) due to the fact that it was always aligned to the movement of the sun. The daily simulated power for fuzzy logic was 5.31% better than the direct-tracking system power. The direct- tracking system power was better than the simulated power for linear regression by 2.24%. A key recommendation is to align a PV module perpendicular to the sun from sunrise to sunset, using an effective control technique based on fuzzy logic principles, in order to extract the maximum amount of available energy.