OPTIMAL RADIAL DISTRIBUTION NETWORK RECONFIGURATION USING MODIFIED SHARK SMELL OPTIMIZATION

Abstract

With the increasing penetration of renewable energies in the power systems, a mix of energy resources from small scale to large scale improves the system reliability. However, radial distribution network encounters many technical challenges associated with enormous power losses as compared to the rest of the network, which normally leads to poor performance and degradation of the system components. Distributed generation (DG) units are normally integrated into the distribution network system to help improve and support the power voltage profile as well as the performance of system components through power loss mitigation. Network reconfiguration is one of the effective methods for power loss reduction when simultaneously applied with the DG units. The reconfiguration in network topology alters the current flowing through the lines and also minimizes power losses while maintaining the operating constraints. In this study, a metaheuristic nature inspired Modified Shark Smell Optimization (MSSO) algorithm was proposed to identify the optimal network reconfiguration in IEEE 33-bus radial distribution system (RDS). The proposed MSSO algorithm and the load flow analysis (Fast Decoupled Load Flow method) was developed and simulated using MATLAB. The objective was to minimize real power losses while improving the voltage profile. There were four different cases considered and the MSSO algorithm performance was assessed on two scenarios (with and without the presence of distributed generation) in the IEEE 33-bus RDS. The results were compared with other metaheuristic algorithms from the literature for validation. The DG integration to the network reduced power losses by 59.82% from the initial network losses. When optimal switching sequence using the xiv MSSO algorithm was applied to the network in the presence of DG units, further power loss reduction from 83.76 kW to 64.92 kW was noted. There was a significant improvement in voltage profile from 0.91075 p.u to 0.97002 p.u. Clearly, optimal network reconfiguration in the presence of DG units lead to reduced power losses and an improved voltage profile.