Reactive Power Optimization for Power System with Distributed Generations Using PSO Hybrid SCA Algorithm

As more and more distributed generations (DGs) are introduced into the power system, the original power flow distribution and voltage quality are changed. Particle swarm optimization (PSO) has been attested to be an effective way to solve reactive power optimization in electrical power system, but it is prone to fall into the local optimization solution and premature convergence. Aiming at these weaknesses, an improved PSO which hybrid sine cosine algorithm (SCA) is proposed. SCA can attract and reject the particles because of the character of sine and cosine functions. This can guarantee the diversity of PSO, and the convergence speed and accuracy are improved effectively. The effectiveness of algorithm is verified by simulations on IEEE 14-bus system including a DG. The results show that the proposed algorithm can obtain a better optimization effect and faster convergence speed.