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A Comparative Study Of Multi-Objective Optimal Power Flow Based On Particle Swarm, Evolutionary Programming, And Genetic Algorithm
Faculty of Engineering University of Malaya
This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. The unattractive characteristics of the cost-based OPF including loss, voltage profile, and emission justifies the necessity of multi-objective OPF study. This study presents the programming results of the nine essential single-objective and multi-objective functions of OPF problem. The considered objective functions include cost, active power loss, voltage stability index, and emission. The multi-objective optimizations include cost and active power loss, cost and voltage stability index, active power loss and voltage …
Effective Utilization Of Excess Energy In Standalone Hybrid Renewable Energy Systems For Improving Comfort Ability And Reducing Cost Of Energy: A Review And Analysis
Faculty of Engineering University of Malaya
One of the features that characterize renewable energy sources is their variability and intermittency. Intermittency covers both the predictable and unpredictable variations of their power outputs and uncertainty in the power availability. To overcome the drawback of intermittency, special design considerations should be taken into account. These additional design considerations increases the overall cost of the renewable energy systems. Adding storage system and/or backup source to the renewable sources is one of the measures used to guarantee the continuity of power supply to the loads, and therefore improve the reliability of the renewable energy systems. The operation of renewable energy …