基于佳点集-量子粒子群算法的交直流系统无功优化方法研究

Reactive power optimization of AC/DC power system based on the good-point set quantum particle swarm algorithm

随着高压直流输电工程和区域电网互联建设的不断推进,交直流互联电网的规模越来越大,其对电网的无功平衡也提出了新的要求。提出一种基于佳点集量子粒子群的交直流系统无功优化方法。该方法建立交直流系统及其潮流计算模型;以系统网损为目标函数,建立交直流输电无功优化模型,并考虑系统节点电压以及发电机无功出现越界的情况;通过引入佳点集并对量子粒子群算法进行改进,给出了使用佳点集量子粒子群优化算法的求解步骤。通过采用IEEE30节点算例进行验证,并与量子粒子群算法比较,结果表明:该文方法具有快速的收敛能力、良好的稳定性,优化性能也有较明显的提高。

Along with the development of high voltage direct current transmission project and the sustainable advance of regional power grid interconnection, the scale of the AC/DC inter-connected power grid is getting larger and larger, which puts forward new requirements to the reactive power balance of the power grid. Based on the best point set of quantum particle swarm optimization,a new reactive power optimization method was proposed in this paper. Firstly, the AC/ DC power system and its improved power flow calculation model were established. Secondly, the AC/DC reactive power optimization model was established, which considered the network loss and voltage quality. Then the quantum particle swarm optimization algorithm was improved through the introduction of the good point set. And the solving steps of the quantum particle swarm optimization algorithm were given. At last, IEEE30 node model was used to verify the validity of the improved algorithm, and then the improved algorithm was compared with the quantum particle swarm optimization algorithm. The simulation results show that the improved algo-rithm has good stability, fast convergence ability and the more significant performance in optimizing reactive power.