Assessment of Two Load Flow Methods in Distribution Network with Optimal Reactive Compensation

The electrical distribution system is the interface between the power system and customers. Because of its compact architecture and low expense, the radial configuration is favored for distribution systems. Reactive Power Compensation (RPC) that is dependent on the optimal option of location and capacitor size in the network is one of the essential settlements for reducing network losses and adjusting the device voltage profile. Various load models, including constants of impedance (Z), current (I), power (P), and composite (ZIP), are used with contrasts between them to define the highest productive kind of load, which provides the optimum settlement for loss minimization, improving cost and voltage profile reductions. In this paper, a study of optimal Reactive Compensation (RC) with a comparison and assessment between two load flow methods Newton Raphson and Backward- Forward load flow methods (DBFSM), considering miscellaneous models of the load, is present for a distribution power system. The optimization algorithm based on Teaching- Learning (TLBO) is applied to refine the voltage values of buses and losses reduction. This algorithm has been tested for the IEEE-33 standard distribution power system. Comprehensive comparison and assessment have been accomplished among the optimization performances for four diverse load models in order to decide the model of load that provides the most betterment in the voltage profile and loss detraction using MATLAB program.The results demonstrate that ZIP model is the most suitable to generate the optimum settlements for capacitor positions and sizes .