基于QPSO算法的电力载波通信自适应阻抗匹配

电力载波通信技术是电力系统中的重要通信手段，针对电力载波通信中阻抗失配问题，提出一种基于量子粒子群算法的电力载波通信自适应阻抗匹配模型。采用[∏]型网络结构，有效地消除了匹配禁区问题，能够快速精准地获得匹配结果。针对遗传算法收敛速度慢、优化精度不高的缺陷，对量子粒子群算法在非对称区间进行分层变异改进处理，并将其应用于自适应阻抗匹配元件参数值的优化。测试结果表明此方案在阻抗匹配的精度和时间方面都有很大的提高，解决了电力线阻抗变化的问题，满足了电力载波通信在精准性、高效性和实时性的要求，在工程实践中具有一定的理论意义和应用价值。

Adaptive impedance matching for power line communication based on quantum particle swarm optimization

 Power Line Communication（PLC） technology is an important communication method which has been extensively used in power system. In order to solve the impedance mismatch of PLC system, an adaptive impedance matching model for power line communication based on Quantum Particle Swarm Optimization（QPSO） has been proposed. With the help of [∏] type matching network, PLC system can effectively eliminate matching restricted areas and get very accuracy matching results and fast matching speed. Dealing with the asymmetrical region by the variation, an improved quantum particle swarm optimization algorithm is proposed. Compared with GA（Genetic Algorithm）, QPSO is employed in the impedance match because of fast convergence and satisfactory solutions. Test results indicate that the accuracy and the velocity of impedance match for PLC have been greatly improved, which effectively overcome the impedance mismatch of PLC system. Therefore, it will provide a perfect significance and application value in the engineering practice.