Power loss minimization and voltage profile improvement in transmission networks using a network modification algorithm

Abstract

A number of algorithms that aim to reduce power system losses and improve voltage profiles by optimizing distributed generator (DG) location and size have already been proposed, but they are still subject to several limitations. Hence, new algorithms can be developed or existing ones can be improved so that this important issue can be addressed much more appropriately and effectively. In their formulations, the majority of algorithms focused only on real power loss minimization. Power systems operate with reactive power controller installed at various locations, which are essential to their operation. Therefore, the effect of reactive power control must be taken into consideration when optimizing DG allocation for voltage profile improvement. State-of-the-art optimization algorithms can be used to improve the effectiveness of the existing one in taking into account the effect of reactive power control. This study proposed a modification methodology based on a hybrid optimization algorithm, consisting of a combination of the genetic algorithm (GA) and the improved particle swam optimization (IPSO) algorithm m for minimizing active power loss and maintaining the voltage magnitude at about 1 p.u. The buses at which DGs should be injected were identified based on optimal real power loss and reactive power limit. When applying the proposed optimization algorithm for DGs allocation in power systems, the search space or number of iterations was reduced, increasing its convergence rate. The proposed modification methodology was tested in an IEEE-30 bus electrical network system with DGs allocations and the simulations were conducted using MATLAB software. The hybrid GA and IPSO (HGAIPSO) method has less iterations and is more effective at solving optimization issues than other optimization algorithms like GA, PSO, and IPSO. An IEEE-30 bus network system with DGs allocations was used to evaluate the effectiveness of the proposed HGAIPSO, and the test results were compared to those from alternative techniques (i.e. GA, PSO and IPSO). The outcomes of the simulation demonstrate that the suggested HGAIPSO can be an effective and promising optimization technique for issues with transmission network modification. IEEE-30 bus test system with DGs included at various locations, Type 1, Type 2, and Type 3 DGs allocation, respectively, showed decreases in overall real power loss of 40.7040%, 36.2403%, and 42.9406%. For the IEEE-30 bus, the highest bus voltage profiles are up to 1.01pu.