In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. The HFPSO algorithm is a hybridization of the Firefly Optimization (FFO) and the Particle Swarm Optimization (PSO) technique, to enhance the exploration, exploitation strategies, and to speed up the convergence rate. In this work, five objective functions of OPF problems are studied to prove the strength of the proposed method: total generation cost minimization, voltage profile improvement, voltage stability enhancement, the transmission lines active power loss reductions, and the transmission lines reactive power loss reductions. The particular fitness function is chosen as a single objective based on control parameters. The proposed HFPSO technique is coded using MATLAB software and its effectiveness is tested on the standard IEEE 30-bus test system. The obtained results of the proposed algorithm are compared to simulated results of the original Particle Swarm Optimization (PSO) method and the present state-of-the-art optimization techniques. The comparison of optimum solutions reveals that the recommended method can generate optimum, feasible, global solutions with fast convergence and can also deal with the challenges and complexities of various OPF problems.
In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.
Miniaturized optical spectrometers can be implemented by an array of Fabry-Pérot (FP) filters. FP filters are composed of two highly reflecting parallel mirrors and a resonance cavity. Each filter transmits a small spectral band (filter line) depending on its individual cavity height. The optical nanospectrometer, a miniaturized FPbased spectrometer, implements 3D NanoImprint technology for the fabrication of multiple FP filter cavities in a single process step. However, it is challenging to avoid the dependency of residual layer (RL) thickness on the shape of the printed patterns in NanoImprint. Since in a nanospectrometer the filter cavities vary in height between neighboring FP filters and, thus, the volume of each cavity varies causing that the RL varies slightly or noticeably between different filters. This is one of the few disadvantages of NanoImprint using soft templates such as substrate conformal imprint lithography which is used in this paper. The advantages of large area soft templates can be revealed substantially if the problem of laterally inhomogeneous RLs can be avoided or reduced considerably. In the case of the nanospectrometer, non-uniform RLs lead to random variations in the designed cavity heights resulting in the shift of desired filter lines. To achieve highly uniform RLs, we report a volume-equalized template design with the lateral distribution of 64 different cavity heights into several units with each unit comprising four cavity heights. The average volume of each unit is kept constant to obtain uniform filling of imprint material per unit area. The imprint results, based on the volume-equalized template, demonstrate highly uniform RLs of 110 nm thickness.
Software piracy is globally a major issue of using software without proper permission as enforced by the software license and agreement. Currently, software industries and organizations face a huge loss of money due to software piracy. Most of the educational institutions/organizations have also been affected from software piracy. To facilitate educational institutions regarding software piracy, it would be ideal to have a detailed study of the awareness of piracy level in education institutions for future development and to help academia to get rid of problems occur from pirated software. The present research aims to study and determine the awareness of piracy level in educational institutions. This study will eventually help academia in determination of level of piracy and awareness of pirated software.
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