Improved Multi-Point Estimate Probabilistic Harmonic Power Flow Algorithm Based On Dynamic Harmonic Model

With the widespread application of distributed photovoltaic(PV) power electronic converters, its inherent intermittency and randomness caused high harmonic content and a broad range of harmonic frequencies covered of the distribution network. A data-driven probabilistic harmonic power flow(PHPF) calculation method is proposed to effectively evaluate the uncertain harmonic state of the system and fully explore the actual operating characteristics of distributed PV. Firstly, the dynamic harmonic coupling matrix model(DHCMM) of distributed PV is established to reveal the mutual coupling relationship between harmonic voltage and harmonic current in different periods based on the actually measured data. Secondly, a PHPF algorithm based on an improved multi-point estimation method(IMPEM) is proposed to accurately grasp the statistical characteristics of output random variables such as harmonic voltage. According to the analysis results, the IMPEM-PHPF method based on the dynamic harmonic model can effectively analyze the time-varying characteristics of distributed PV harmonic sources and the harmonics are evaluated accurately in the power system.