Optimal planning of reactive power in electrical networks using metaheuristics

Abstract

Reactive power is the component of electrical power that oscillates between the source and load without performing any useful work. While it does not contribute directly to energy consumption, Its Proper dispatch helps of minimizing transmission losses, improving voltage profile and enhance the overall reliability of the electrical grid. The optimal reactive power dispatch (OPRD) Seeks to properly manage the reactive power resources of the system. Traditional methods forsolving the ORPD problem often face challenges in handling the complex, non-linear, and highly constrained nature ofpower systems. In this context, metaheuristic algorithms have emerged as effective tools for finding near-optimal solutions tocomplex optimization problems. In this thesis, firstly, various bio-inspired meta-heuristic optimization techniques have been developed and implemented to deal with the ORPD problem. Then, we have proposed a new hybrid metaheuristic method composed of a population method (Particle Swarm Optimization) and a local search method (Tabu Search) named PSO-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 and improve voltage profile of the electrical network. The bus locations of the shunt capacitors are identified according to sensitive buses approach. In this work, we have also solved the of ORPD problem considering FACTS devices. Simulations is extended to some large-scale power system models like IEEE 57-bus, IEEE 118-bus and a practical Algerian 114-bus power test system. Finally, a mock-up has been built to test the control and command of the SVC devices via a humanmachine interface running under windows and android. An application has been designed to visualize all the simulations carried out in this thesis.