Abstract
This paper presents the design and application of an efficient hybrid algorithm for solving the Optimal Reactive Power Flow (ORPF) problem. The ORPF is formulated as a nonlinear constrained optimization problem where the active power losses must be minimized. The proposed approach is based on the hybridization of Particle Swarm Optimization (PSO) and Tabu-Search (TS) technique. The proposed PSO-TS approach is used to find the settings of the control variables (i.e. generation bus voltages, transformer taps, and shunt capacitor sizes) which minimize transmission active power losses. The bus locations of the shunt capacitors are identified according to sensitive buses. To show the effectiveness of the proposed method, it is applied to the IEEE 30 bus benchmark test system and is compared with PSO and TS without hybridization, along with some other published approaches. The obtained results reveal the effectiveness of the proposed method in dealing with the highly nonlinear constrained nature of the ORPF problem.
Highlights
Due to their complex construction and operation, electrical power networks encounter several challenges
The proposed Particle Swarm Optimization (PSO)-TS based reactive power optimization approach was applied to the IEEE 30-bus power system shown in Figure 3 with 12 control variables
To identify this type of buses and their number, we removed the load from each load bus and calculated the active power losses (PLoss) each time
Summary
Due to their complex construction and operation, electrical power networks encounter several challenges. Many classical approaches for solving the ORPF problem have been reported such as the gradient based approach [5, 6], linear programming [7], non-linear programming [8, 9], quadratic programming [10], and interior point [11]. PSO in particular has received increased attention from researchers because of its searching capability It was developed through simulations of a simplified social system, and has been found to be robust in solving continuous non-linear optimization problems. The novelty of this paper is that an efficient hybrid PSO with Tabu Search (PSO-TS) method is implemented to solve the ORPF problem by minimizing active power losses. Simulations were performed with MATLAB using the IEEE 30-Bus benchmark system
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