An Adaptive Droop Control Strategy for Islanded Microgrid Based on Improved Particle Swarm Optimization
An Adaptive Droop Control Strategy for Islanded Microgrid Based on Improved Particle Swarm Optimization
复制标题
基于改进粒子群优化的孤岛微电网自适应下垂控制策略
DOI：
10.1109/access.2019.2960871
复制
发表时间：
2020-01-01
期刊：
影响因子：
3.9
通讯作者：
Lyu, Ling
中科院分区：
文献类型：
--
作者：
Zhang, Liang;Zheng, Hao;Lyu, Ling
在具有多个分布式电源的孤岛微电网中，线路阻抗的差异会引起局部电压偏差，从而导致传统下垂控制下功率分配精度降低、母线电压下降等一系列问题。在这方面，提出了一种使用改进的粒子群优化算法（IPSO）优化下垂控制的方法。首先，分析了微电网的结构和线路参数对传统下垂控制策略的影响。在此基础上，提出了一种改进的粒子群优化算法。在基本粒子群优化算法的基础上，引入模糊推理系统对粒子群优化算法进行动态调整，有效提高了算法的全局搜索能力和局部搜索能力。然后将改进后的算法应用于下垂控制器，同时通过小信号分析确定系统稳定运行的范围。仿真和实验结果表明，所提出的改进下垂控制策略能够在保持母线电压和系统频率稳定的同时，有效实现有功和无功功率的精确分配，提高微网系统的动态性能和暂态稳定性。
In an islanded microgrid with multiple distributed generations (DGs), the difference in line impedance may cause local voltage deviation, which leads to a series of problems such as lower power allocation accuracy and bus voltage drop under traditional droop control. In this respect, a method for optimizing the droop control using an improved particle swarm optimization (IPSO) is proposed. Firstly, the microgrid structure and influence of line parameters on traditional droop control strategy is analyzed. Then, an improved particle swarm optimization is proposed. Based on the basic particle swarm optimization (PSO) algorithm, a fuzzy inference system (FIS) is introduced to dynamically adjust the particle swarm optimization, which can effectively improve the global search ability and local search ability of the algorithm. After that, the improved algorithm is applied to the droop controller, simultaneously, the range of stable operation of the system is determined by small signal analysis. Finally, the simulation and experiment results show that the proposed improved droop control strategy can achieve accurate allocation of active and reactive power effectively while maintaining bus voltage and system frequency stability, enhance the dynamic performance and transient stability of the microgrid system.