In order to solve more serious harmonic problems of the grid, hybrid active power filters (HAPF) have been proposed earlier. The HAPF is the combination of active and passive power filters. The aim in the HAPF design is to complement or enhance the performance of the active power filter or passive power filter by adding passive or active components to its structure. HAPF is categorized in parallel hybrid active power filters (PHAPFs) and series hybrid active power filters (SHAPFs) based on the used active filter type. A series of PHAPFs was proposed after the 1990s. Cheng et al. proposed a new hybrid active power filter to achieve the power-rating reduction of the active filter. But the active power filter still bears the fundamental voltage in this design. In this project a novel HAPF with injection circuit was proposed. The novel topology has great promise in reducing harmonics with a relatively low capacity APF. For harmonic current tracking controls, there are two schemes: One is the linear current control, such as ramp comparison control, deadbeat control, sinusoidal internal model control, generalized integrators control, etc.; the other is nonlinear current control, such as hysteresis control, predictive control, etc.
This project deals with a hybrid active power filter with injection circuit (IHAPF). It shows great promise in reducing harmonics and improving the power factor with a relatively low capacity active power filter. An adaptive fuzzy dividing frequency-control method composed of a generalized PI control unit and fuzzy adjustor unit was proposed. In the new control scheme, the generalized PI control unit is used to achieve dividing frequency control; the fuzzy adjustor unit is used to adjusted parameters of the PI control unit to produce better adaptive ability and dynamic response. At the same time, the control strategy is generally useful and applicable to other active filters. This project concluded that the stability of the IHAPF based on detection supply current is superior to that of others. To minimize the capacity of IHAPF, an adaptive fuzzy dividing frequency-control method is proposed by analyzing the bode diagram, which consists of two control units: a generalized integrator control unit and fuzzy adjustor unit. The generalized integrator is used for dividing frequency integral control, while fuzzy arithmetic is used for adjusting proportional-integral coefficients timely. And the control method is generally useful and applicable to any other active filters. Compared to other IHAPF control methods, the adaptive fuzzy dividing frequency control shows the advantages of shorter response time and higher control precision. The simulation and experimental results show in marine and offshore industry. that the new control method is not only easy to be calculated and implemented, but also very effective in reducing harmonics.
INDRANIL SAAKI (2020). Hybrid Active Power Filter Based on the Adaptive Fuzzy controller for marine & offshore industry (https://www.mathworks.com/matlabcentral/fileexchange/57720-hybrid-active-power-filter-based-on-the-adaptive-fuzzy-controller-for-marine-offshore-industry), MATLAB Central File Exchange. Retrieved .
Dear Indranil,I have checked your project it is running, but the harmonic elimination is not happening as per the IEEE-519-2014.
Dear indranil, Please send the design calculations and a brief report on this project.
your model is not eliminating harmonics. Kindly check it and update
Hello Andrzej tobola
All my models developed in matlab 2009(b) version .so change ur matlab software version and run the simulation.
With R2016a/b I have:
Failed to load library 'powerlib_models' referenced by 'hapfgipifuzzy/Subsystem1/Three-Phase Source/Source'
any clue ?
hello kumar reddy
.fis file updated so import the file run the sumulation.
please send .fis file to firstname.lastname@example.org so that i can run the model.
you can use some of nonlinear dynamic loads at the load side.
fuzzy .fis files are updated
UPQC device also proposed for marine and offshore industry
Noval HAPF can also be control by neural network predictive controller.