混合动力系统电能质量扰动分析及治理
Research on Power Quality Improvement of Hybrid Power System
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摘要: 基于并联有源滤波器(shunt active power filter, SAPF)和动态电压调节器(dynamic voltage restorer, DVR),首先,搭建了包含光伏和风机的混合动力系统,用以模拟分布式电源接入配电网中产生的电能质量(power quality, PQ)扰动。其次,利用模糊逻辑、神经网络和自适应神经模糊推理系统控制算法对SAPF的动态性能进行优化,对电能质量扰动进行治理,使用人工智能技术进行管理,使光伏和风能系统均实现最大功率点跟踪(maximum power point tracking, MPPT)。最后,在搭建的仿真系统中进行验证,线性负载和非线性负载输出侧谐波畸变率分别降至0.20%和2.05%,满足配电系统对于电能质量的要求。Abstract: Applying shunt active power filter（SAPF） and dynamic voltage restorer（DVR）, a hybrid power system including photovoltaic and wind turbine is built in this paper to observe power quality（PQ） disturbances caused by the distributed generation connecting to the distribution network. In addition, control algorithms such as fuzzy logic, neural network and adaptive neural fuzzy inference system are employed to optimize the dynamic performance of SAPF, to control power quality disturbances, to achieve maximum power point tracking（MPPT） in both photovoltaic and wind energy systems by adopting artificial intelligence technology. Finally, the harmonic distortion rates of the linear and nonlinear loads on the output side are reduced to 0.20% and 2.05% in the simulation system, respectively, which meet the power quality requirements in power distribution system.
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