Nested multi-objective PSO for optimal allocation and sizing of renewable energy distributed generation

Distribution generation (DG) opened a new era for using renewable energy sources to face the future load expansion and enhance the stability of the power system. A methodology for allocating and sizing and analysis for renewable energy sources as DG sources are introduced. Allocation criteria for weaken bus-bars are introduced in this paper. The selected bus-bars are then supported with optimized DG sources in order to enhance the system capability to withstand any future expansion in load. The voltage weakening index is used to compare the voltage of the post-load increase with the base voltage at normal load. A new proposed nested particle swarm optimization (PSO) technique is introduced to design the optimal size of renewable energy source capacity. Two objective functions have been designed for optimal allocation and sizing of the DG; they are the generation and operation energy cost and the transmission line losses (TLLs). The allocation methodology is performed using multi-objective particle swarm optimization. Different scenarios for the optimal operation under different operating conditions are introduced. The new contribution of this paper is the use of the new nested PSO technique for optimal sizing taking the time variation into consideration which has not been revealed before in the literature. The results obtained using the new proposed optimization program show a great potential of deployment of DG renewable energy sources in terms of reducing the cost of energy and TLLs and improving the system operational conditions. Published by AIP Publishing.