01994nam a22001457a 4500999001700000100006900017245007500086260003000161500138000191700004201571856003201613942001101645952009001656952010201746  c64617d64614  aShafquat Rasool Tumrania16MPE20aSupervisor -Dr. Suhail Khokhar  aApplication of Artificial Neural Network For Shunt Active Power Filter  aNawabshah:bQuest,c2018,  aABSTRACT

Nowadays Alternating Current (AC) electrical power system is facing  voltage and current harmonics due to non-linear loads present in the power system such as rectifiers. power electronics convertors AC regulators.  battery chargers. Direct Current  (DC) motors drives and adjustable speed drives. These devices generate significant distortions in the electrical networks and cause power quality problems such as harmonics and waveform distortion. Various solutions such as filters are used to eliminate these power quality problems to the level of international standards. One of the solution celebrated as Shunt Active Power Filter (SAPF) based  on Feed forward Multilayer Neural Network (MNN) is the most common and appropriate used technique to compensate the harmonic components in the power system. The purpose  of this research is to provide  an in-depth  understanding  on  realizing multilayer perceptron neural  network-based control algorithms for SAPF. In  this
thesis a procedure to  implement  the  MNN  based  technique using MATLAB/Simulink environment. Moreover, provides the detailed analysis on the performance. limitations, and advantages of the MNN based SAPF. The performance of  SAPF based on Multi layer Neural Network (MNN) compensation algorithms is
found to be effective and satisfactory to compensate harmonics and reactive power factor.  aDepartment of Electrical Engineering   uhttp://tinyurl.com/mryazut2  cTHESIS  00104070aRESEARCHbRESEARCHd2019-02-27l0pMP/40-435r2019-02-27 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2023-12-18l0pMP/51-620r2023-12-18 00:00:00w2023-12-18yTHESIS