An improved particle swarm optimization method to optimal reactive power flow problems

Baharozu, Eren; Soykan, Gürkan; Altay, Özkan; Kalenderli, Özcan

doi:10.1109/eleco.2015.7394600

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…Notably, Non-gradient techniques of optimization-artificial intelligence methods. Patil et al [18] presented Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA) techniques have been employed in finding optimum losses based on the active and reactive power losses; Monshizadeh et al [19] recommended PSO as best algorithm for minimizing power loss in transmission lines; Baharozu et al [20] improved PSO by choosing the load bus voltages, ge- Notably, the application of the gradient method of optimization using the Corona and Ohms transmission loss model is not feasible as optimum variables of the objective function cannot be derived nor the optimum values possible. Expectantly, the gradient method of optimization guarantees global minimum/ maximum.…”

Section: Introductionmentioning

confidence: 99%

Minimization of Electric Power Losses on 132 kV and 220 kV Uganda Electricity Transmission Lines

Living¹,

Nnamchi²,

Ukagwu³

et al. 2023

EPE

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The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.

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Section: Introductionmentioning

confidence: 99%