An Improved Affine Arithmetic-Based Optimal DG Sizing and Placement Algorithm Using PSO for Radial Distribution Networks with Uncertainty

In the present work, Particle Swarm optimization (PSO) based optimal Distributed Generation (DG) placement and sizing for radial distribution systems using Affine Arithmetic (AA), considering uncertainty in load and generation, is presented to reduce real power losses and improve voltage profile with minimum investment cost. The PSO algorithm incorporates both affine as well as crisp discrete variables for uncertain DG generation and bus locations respectively to arrive at the optimal solution. An affine expression for real power loss is used which has sensitivity coefficients of real power losses in distribution lines corresponding to power injections at different buses. The resulting affine loss intervals are further tightened using an optimization procedure. The proposed method is implemented on IEEE 33 and 119 bus radial distribution systems. The optimal loss intervals obtained by the proposed method are compared with existing AA based optimal DG allocation method. The simulation results show that the proposed AA-PSO method gives more optimal DG size and location, for IEEE 33 and 119 bus radial distribution systems with uncertainty when compared to existing method which uses AA.