A new multi-objective particle swarm optimization for reactive power dispatch

The optimal reactive power dispatch (ORPD) problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. This paper presents a new hybridization technique for solving the ORPD problem based on the integration of particle swarm optimization (PSO) with artificial physics optimization (APO). This hybridized algorithm is tested and verified on the IEEE 30, IEEE 57, and IEEE 118 bus test systems to solve both single and multiobjective ORPD problems, considering three main aspects. These aspects include active power loss minimization, voltage deviation minimization, and voltage stability improvement. The results prove that the algorithm is effective and displays great consistency and robustness in solving both the single and multiobjective functions while improving the convergence performance of the PSO. It also shows superiority when compared with results obtained from previously reported literature for solving the ORPD problem.

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An Improved Solution for Reactive Power Dispatch Problem Using Diversity-Enhanced Particle Swarm Optimization

Energies ◽

10.3390/en13112862 ◽

2020 ◽

Vol 13 (11) ◽

pp. 2862 ◽

Cited By ~ 2

Author(s):

Mini Vishnu ◽

Sunil Kumar T. K.

Keyword(s):

Particle Swarm Optimization ◽

Reactive Power ◽

Particle Swarm ◽

Load Condition ◽

Active Power ◽

Mixed Integer ◽

Swarm Optimization ◽

Power Dispatch ◽

Reactive Power Dispatch ◽

Enhanced Particle Swarm Optimization

Well-structured reactive power policies and dispatch are major concerns of operation and control technicians of any power system. Obtaining a suitable reactive power dispatch for any given load condition of the system is a prime duty of the system operator. It reduces loss of active power occurring during transmission by regulating reactive power control variables, thus boosting the voltage profile, enhancing the system security and power transfer capability, thereby attaining an improvement in overall system operation. The reactive power dispatch (RPD) problem being a mixed-integer discrete continuous (MIDC) problem demands the solution to contain all these variable types. This paper proposes a methodology to achieve an optimal and practically feasible solution to the RPD problem through the diversity-enhanced particle swarm optimization (DEPSO) technique. The suggested method is characterized by the calculation of the diversity of each particle from its mean position after every iteration. The movement of the particles is decided based on the calculated diversity, thereby preventing both local optima stagnation and haphazard unguided wandering. DEPSO accounts for the accuracy of the variables used in the RPD problem by providing discrete values and integer values compared to other algorithms, which provide all continuous values. The competency of the proposed method is tested on IEEE 14-, 30-, and 118-bus test systems. Simulation outcomes show that the proposed approach is feasible and efficient in attaining minimum active power losses and minimum voltage deviation from the reference. The results are compared to conventional particle swarm optimization (PSO) and JAYA algorithms.

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