Optimal allocation of renewable energy sources and power filters in unbalanced distribution systems with nonlinear loads under load growth condition - Arubolu, Lavanya; Kollu, Ravindra; Manyala, Ramalinga Raju (Frontiers in Energy Research, 2025)
In recent years, the world’s energy needs have increased significantly. In order to meet this demand and mitigate the environmental issues brought on by the use of conventional power plants, numerous studies were offered to develop renewable energy sources (RES) as green energy distributed generators. This study uses probability distribution functions to simulate the fluctuating nature of RES and load. A novel approach to minimize Power Loss, Total Harmonic Distortion, and Cost is proposed which employs Pareto front-based Multi Objective Backtracking Search Algorithm (PMBSA) to optimally distribute RES and Power Filters in an Unbalanced Distribution System (UDS). The proposed approach takes into account load growth and multiple non-linear loads in addition to linear loads while optimally allocating RES, Passive power filters (PPFs) and Active power filters (APFs) in UDS. The results of simultaneous placement of RES and PPFs are compared with simultaneous placement of RES and APFs by testing on a 123-bus UDS to demonstrate which combination performs better in reducing THD along with other objectives. Automatic Voltage Regulators (AVRs) and Shunt Capacitor Banks (SCBs) are also installed in UDS in the event of voltage limit violations. Furthermore, results comparison is carried out with results obtained using Non-dominated Sorting Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Weighted Sum technique (WSA) to demonstrate the effectiveness of the proposed approach employing PMBSA in improving UDS performance.