摘要
为解决传统扰动观测法由于步长固定引起功率点的较大扰动的问题,将电导增量法与扰动观测法技术相结合应用到光伏发电最大功率点跟踪中。开展光伏电池输出模型的分析,建立了以电导增量为判断依据的变步长选择关系;同时为了解决在较大光照强度变化下可能导致最大功率点跟踪失效的问题,结合自适应神经模糊推理系统(ANFIS)建立变步长因子与光照强度的逻辑关系,提出一种基于电导增量的扰动观测法的改进算法。仿真结果表明,该算法能有效提高系统的动态响应速度和稳态精度。
In order to solve the problems of power point large disturbance caused by fixed step of traditional perturbation & observation method, the combination of conductance increment and perturbation & observation method applied into the maximum power point tracking of photovoltaic power was investigated. After the analysis of PV cells output model, the relationships of variable step selection judged by incremental conductance was established. A method was presented to solve problem of MPPT fail which may be led by the large change of light intensity, the adaptive neuro-fuzzy inference system was combined, the logical relationship of variable step size factor and light intensity was established, and an improved algorithm of perturbation and observation method based on incremental conductance was presented. The simulation shows the algorithm can effectively improve the dynamic response speed and steady-state accuracy.
出处
《电源技术》
CAS
CSCD
北大核心
2013年第5期781-784,共4页
Chinese Journal of Power Sources
基金
浙江省自然科学基金项目(Y1110557)
衢州市科技计划项目(20111056)
关键词
光伏发电
最大功率点跟踪
扰动观测法
电导增量
photovoltaic(PV) power generation
maximum power point tracking(MPPT)
perturbation and observation method
incremental conductance