Abstract
A novel methodology based on the recent metaheuristic optimization algorithm Salp Swarm Algorithm (SSA) for locating and optimal sizing of renewable distributed generators (RDGs) and shunt capacitor banks (SCBs) on radial distribution networks (RDNs) is proposed. A multi-objective function index (MOFI) approach is used for assuring the power quality (PQ) through enhancing the voltage level in addition to minimizing the power losses of the system and the whole operating cost of the grid. The proposed methodology is tested via 33-Bus standard radial distribution networks at different scenarios to prove their validity and performance. The obtained results are compared with the Grasshopper Optimization Algorithm (GOA), and the hybrid Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (PSOGSA). The SSA optimizer proved its superiority with high attitude and accuracy for solving the problems of RDGs’ and SCBs’ locations and capacities simultaneously. An Egyptian practical case study at different load levels via different scenarios including the control operation within 24 h is considered.
Highlights
Electric power networks, especially distribution systems, commonly suffer from two main issues: high power losses and poor voltage profile [1,2]
The cost-index ∆OCDGSCB is equal to the proportion of TOCT,DGSCB via the locations of the renewable distributed generators (RDGs) and shunt capacitor banks (SCBs) to TOCbase in a basic situation, and it can be minimized based on (19):
The simulation results were investigated in two basic parts.InIn the MATLAB software (2015a, USA)
Summary
Electrical Power Systems Department, Moscow Power Engineering Institute, 111250 Moscow, Russia.
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