Single axis trackers have their application in the efficiency improvement process of photovoltaic systems. In spite of large investment costs, their application is necessary in the areas with a low amount of available solar irradiation. This is applicable only if it is required to exploit all available energy sources at any cost. With optimization and improvement of these systems it is possible to increase their efficiency, reduce energy usage for their movement and improve system reliability. Motion parameters are significant for the optimization of the system. It is necessary to set and monitor the right parameters as a prerequisite for system optimization. The process of calibration of single axis tracker prototype is shown in this paper. It is shown that proper calibration and system adjustment could improve efficiency of the system.

This paper presents a method for distributed generation (DG) allocation in low voltage distribution network based on the total annual energy loss reduction and Artificial Neural Network (ANN). The proposed method is applied to the PV solar based DG allocation problem in the low voltage distribution network using realistic network data and measurements. This research is motivated by numerous realistic issues faced by the Distribution System Operator in the area of DG planning. The main objective of this work is to develop, test and validate a robust method for DG allocation which can be used in practical problems without the need for extensive system modelling and load flow analysis. The results confirm the importance of appropriate DG planning and show that the proposed method can be used as a promising tool for efficient and effective DG allocation in low voltage distribution network.