Multiagent-based differential evolution algorithm for loss minimisation in power systems

2013 ◽  
Vol 4 (1) ◽  
pp. 34 ◽  
Author(s):  
S. Sivasubramani ◽  
K.S. Swarup
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Evolution Algorithm

scholarly journals Cost Minimizations and Performance Enhancements of Power Systems Using Spherical Prune Differential Evolution Algorithm Including Modal Analysis

2021 ◽  
Vol 13 (14) ◽  
pp. 8113
Author(s):  
Sherif S.M. Ghoneim ◽  
Mohamed F. Kotb ◽  
Hany M. Hasanien ◽  
Mosleh M. Alharthi ◽  
Attia A. El-Fergany
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Modal Analysis ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Stability Index ◽  
Pareto Solution ◽  
Evolution Algorithm

A novel application of the spherical prune differential evolution algorithm (SpDEA) to solve optimal power flow (OPF) problems in electric power systems is presented. The SpDEA has several merits, such as its high convergence speed, low number of parameters to be designed, and low computational procedures. Four objectives, complete with their relevant operating constraints, are adopted to be optimized simultaneously. Various case studies of multiple objective scenarios are demonstrated under MATLAB environment. Static voltage stability index of lowest/weak bus using modal analysis is incorporated. The results generated by the SpDEA are investigated and compared to standard multi-objective differential evolution (MODE) to prove their viability. The best answer is chosen carefully among trade-off Pareto points by using the technique of fuzzy Pareto solution. Two power system networks such as IEEE 30-bus and 118-bus systems as large-scale optimization problems with 129 design control variables are utilized to point out the effectiveness of the SpDEA. The realized results among many independent runs indicate the robustness of the SpDEA-based approach on OPF methodology in optimizing the defined objectives simultaneously.

scholarly journals A novel differential evolution algorithm for economic power dispatch problem

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Pooja
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Optimization Problem ◽  
Linear Optimization ◽  
Differential Evolution Algorithm ◽  
Economic Power ◽  
Power Dispatch ◽  
Evolution Algorithm ◽  
Economic Power Dispatch

<p style='text-indent:20px;'>In power systems, Economic Power dispatch Problem (EPP) is an influential optimization problem which is a highly non-convex and non-linear optimization problem. In the current study, a novel version of Differential Evolution (NDE) is used to solve this particular problem. NDE algorithm enhances local and global search capability along with efficient utilization of time and space by making use of two elite features: selfadaptive control parameter and single population structure. The combined effect of these concepts improves the performance of Differential Evolution (DE) without compromising on quality of the solution and balances the exploitation and exploration capabilities of DE. The efficiency of NDE is validated by evaluating on three benchmark cases of the power system problem having constraints such as power balance and power generation along with nonsmooth cost function and is compared with other optimization algorithms. The Numerical outcomes uncovered that NDE performed well for all the benchmark cases and maintained a trade-off between convergence rate and efficiency.</p>

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