In the deregulated power market environment, distributed generation (DG) is an effective approach to manage performance, operation and control of the distribution system. Methods available in the literature for DG planning are often not able to simultaneously provide technical and economical benefits. Therefore an effective methodology is developed to improve the technical as well as economical benefits as compared with the existing approaches. This study reports the optimal installation of multi‐DG in the standard 33‐bus, 69‐bus radial distribution systems and 54‐bus practical radial distribution system. Several performance evaluation indices such as active and reactive power loss indices, voltage deviation index, reliability index and shift factor indices are used to develop a novel multi‐objective function (MOF). A new set of equations is developed for representing different practical load models. A novel MOF has been solved to find optimal sizing and placement of DGs using genetic algorithm and particle swarm optimisation technique. The comparative result analysis is also discussed for both techniques. The result analysis reveals that system losses, energy not supplied, system MVA intakes are reduced, whereas available transfer capability, voltage profile, reliability and cost benefits are improved for the case with‐DGs in the distribution system.

Different types of techniques have been used for tracking the MPPT of PV system such as perturb and observe and incremental conductance, etc. The incremental conductance MPPT tracking techniques is complex but more efficient than P&O of PV system under specified atmospheric conditions. Therefore, the aim of this work is to present comparison between P&O and INC maximum power point tracking techniques. This paper presents the implementation and comparison of performances with respect to output parameters for P&O and INC MPPT algorithms. The comparison shows INC technique is more efficient and offers a fast tracking speed for the MPPT of a PV array. The modeling of the system is executed with MATLAB/SIMULINK software.