“…Jellyfish move about their positions in passive motion, and the fresh update of their positions is described by using (17). The active motion, on the other hand, is determined according to the formula shown in (18).…”
Section: A Proposed Compensation Technique Using the Improved Jelly Fish Algorithm (Ijfa)mentioning
confidence: 99%
“…The SHEPWM and Selective Harmonic Mitigation PWM (SHMPWM) based three-level NPC converters were employed, applying the harmonic suppression algorithm [17]. In [18], an Artificial Bee Colony (ABC) and filter compensation modules were used to minimise harmonics in microgrids [19].…”
A two-step methodology was used to address the power quality concerns for the PV integrated microgrid system. In the first step, partial shading was included to deal with the real-time issues. The Improved Jelly Fish Algorithm integrated Perturb and Obserb (IJFA-PO) has been proposed to track the Global Maximum Power Point (GMPP). In the second step, the main unit powered by a DC-AC converter is synchronised with the grid. To cope with the wide voltage variation, an auxiliary unit is connected to the main unit in the opposite phase. This study evaluates various switching approaches to determine the optimal solution for achieving the stated goals. It was found that the IJFA-based SHE in 120 օ conduction gives improved results. A novel series compensation technique has been employed to further eliminate harmonics before grid integration. The proposed IJFA has been used to determine the switching angles for the SHEPWM converter. The objective function and novel series compensation work together to determine the harmonics that should be decreased and kept to a minimum. Three switching angles' performance was equivalent to that of nine switching angles. As a result, higher-order harmonics can be minimised with fewer switches, and switching losses can be lowered without compromising efficiency. The THD of the proposed system was 1.32 percent, which is very much within the tolerable limit of IEEE 1547, IEC, and CIGRE WG 36-05 standards. In terms of efficiency, metaheuristics, and convergence, the proposed system outperformed the existing ones. The model was developed in MATLAB/Simulink 2016b. To verify the simulation results, an experimental prototype of grid synchronised PV capacity of 260W was tested under various loading conditions. The present model is reliable and features a simple controller that provides more convenient and adequate performance for practical reasons.
“…Jellyfish move about their positions in passive motion, and the fresh update of their positions is described by using (17). The active motion, on the other hand, is determined according to the formula shown in (18).…”
Section: A Proposed Compensation Technique Using the Improved Jelly Fish Algorithm (Ijfa)mentioning
confidence: 99%
“…The SHEPWM and Selective Harmonic Mitigation PWM (SHMPWM) based three-level NPC converters were employed, applying the harmonic suppression algorithm [17]. In [18], an Artificial Bee Colony (ABC) and filter compensation modules were used to minimise harmonics in microgrids [19].…”
A two-step methodology was used to address the power quality concerns for the PV integrated microgrid system. In the first step, partial shading was included to deal with the real-time issues. The Improved Jelly Fish Algorithm integrated Perturb and Obserb (IJFA-PO) has been proposed to track the Global Maximum Power Point (GMPP). In the second step, the main unit powered by a DC-AC converter is synchronised with the grid. To cope with the wide voltage variation, an auxiliary unit is connected to the main unit in the opposite phase. This study evaluates various switching approaches to determine the optimal solution for achieving the stated goals. It was found that the IJFA-based SHE in 120 օ conduction gives improved results. A novel series compensation technique has been employed to further eliminate harmonics before grid integration. The proposed IJFA has been used to determine the switching angles for the SHEPWM converter. The objective function and novel series compensation work together to determine the harmonics that should be decreased and kept to a minimum. Three switching angles' performance was equivalent to that of nine switching angles. As a result, higher-order harmonics can be minimised with fewer switches, and switching losses can be lowered without compromising efficiency. The THD of the proposed system was 1.32 percent, which is very much within the tolerable limit of IEEE 1547, IEC, and CIGRE WG 36-05 standards. In terms of efficiency, metaheuristics, and convergence, the proposed system outperformed the existing ones. The model was developed in MATLAB/Simulink 2016b. To verify the simulation results, an experimental prototype of grid synchronised PV capacity of 260W was tested under various loading conditions. The present model is reliable and features a simple controller that provides more convenient and adequate performance for practical reasons.
“…Hence, through the unstable environmental circumstances, the introduction of hybrid wind-solar energy conversion system offers unique power production with permanent output power [13]. The utilization of hybrid solar and wind system connected with grid is increased considerably by the sudden development of power electronic devices and the organization approaches [14]. To achieve the effective power conversion based on HRES, the rectifier, boost converters and inverters play an important role [15].…”
A hybrid approach is proposed in this paper to achieve the load power requirement for grid connected hybrid photovoltaic wind system. The proposed approach is the combined execution of both the Modified Dragonfly Algorithm (MDA) and Adaptive Neuro-Fuzzy Interference System (ANFIS), hence it is called MDA-ANFIS. ANFIS approach is improved by the MDA approach to minimize the error functions. The main aim of the proposed approach is satisfying the load power requirement and obtains the maximum energy from the hybrid wind solar system. Through the modelling of operating modes of generation units, the proposed approach determines the switching states of the inverter. The MDA approach is utilized to generate the dataset and the data set is processed by ANFIS, which creates the control signal. By using the proposed approach, it was possible to minimize the system parameter radiation, external disturbances as well as optimally fulfill the load demand. The proposed method is activated in MATLAB/Simulink platform, and its performance is compared with existing methods.
“…[41][42][43][44] For the case in which EV chargers are used as APFs, [45][46][47][48] they success in reducing harmonic content but they also involve a high development cost, even more if they are designed for both reducing harmonics and giving grid support. 49,50 Many control strategies focus on selective harmonic elimination (SHE) algorithms, [51][52][53][54] but most are based on multilevel converters, which despite their better harmonic response are more expensive in cost, and require more volume and weight as they consist of more elements. 55 In this scenario, analyzing the above mentioned methods, it can be said that they are either too complicated to implement or require additional devices that make the installation more expensive, larger and heavier.…”
This paper presents the design and implementation of a control for an electric vehicle charger to provide vehicle to grid (V2G) services while reducing the current total harmonic distortion (THD). The control is composed of two current loops. The main one controls the active and reactive powers in a decoupled way, and the second one, focuses on the reduction of the fifth order harmonic component. After explaining the mathematical modelling, the meth-
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