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This study presents a hybrid method, namely the marine predator algorithm (MPA) and Aquila optimizer (AO). The proposed algorithm is named MAO. AO duplicated the existence of the Aquila bird in nature while hunting for prey while MPA was inspired by predators in marine animal life. Although AO is widely accepted, it has several disadvantages. This causes various weaknesses such as a weak exploitation phase and slow growth of the convergence curve. Thus, certain exploitation and exploration in conventional AO can be studied to achieve the best balance. The MPA demonstrates the capacity to deliver optimal design and statistically efficient outcomes. The proposed method used AO as the main algorithm. To measure the performance of the proposed method, this study depicted a comparison using the AO, MPA, and whale optimization algorithm (WOA) methods. This paper was evaluated the performance of MAO on twenty-one CEC2017 benchmark functions test and droop control performance on direct current (DC) microgrid. From the simulation, MAO shows superior convergence ability. The proposed method and its application to droop control was successfully implemented and implied a promising performance. [ABSTRACT FROM AUTHOR]

In this research, a modified Osprey optimization algorithm (MOOA) is presented to optimize droop control parameters. MOOA is a modification of the Osprey optimization algorithm by adding levy flight which has the advantage of exploiting a wider space and being adaptive to environmental changes. This research also modifies droop control, Proportional Integral Derivative (PID) is applied to secondary control. PID has flexibility in responding to changes in system conditions and fast response in dealing with system changes. The PID parameters are optimized using MOOA and are called MOOA-PID. The MOOA method is validated using 23 CEC2017 benchmarks-function and performance on DC microgrid systems. This research uses the latest algorithms as a comparison, namely One-to-One Based Optimizer (OOBO), Preschool Educational Optimization Algorithm (PEOA), and the red-tailed hawk (RTH) algorithm in testing 23 CEC2017 benchmark functions. From the simulation of the 23 CEC2017 benchmark function, it is known that the MOOA method has better capabilities. MOOA has advantages in 15 out of 23 benchmark functions. In DC microgrid system testing, MOOAPID is compared with the Proportional Integral (PI) method which is optimized with MOOA and is called MOOA-PI. Testing on the microgrid is aimed at determining the performance of the transient response of power, voltage and current in the system. Tests on DC microgrid systems found that the application of MOOA-PID in secondary control had better capabilities than MOOA-PI. The average value of voltage overshoot from MOOA-PID is 9.828% better than MOOA-PI. The average ITSE MOOA-PID score is 22.3% better than MOOA-PI. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing use of renewable energy sources for energy-saving causes the heavy reliance on DC-DC converters, most prominently the boost converter. However, the standard boost converter limits the resulting voltage and introduces a high current ripple which may draw discontinuous current from the source, further worsening the switching noise that may spread to neighboring circuits. This research proposes a new method, split inductance and bypass capacitance, to suppress the input current ripple and increase voltage gain. The splitting of the two components allows improved filtering between the source and the power stage of the converter and provides a two-way noise limiter. Computer simulations were conducted to compare the performance of the standard with the proposed multiphase boost converters. Results show that the input current ripple was 2.42% for the 4-phase standard boost converter and 0.049% for the proposed multiphase interleaved boost converter. Furthermore, the voltage gain is 1.35 for the standard multiphase boost and 1.61 for the proposed multiphase interleaved boost converter. [ABSTRACT FROM AUTHOR]

Photovoltaic and wind are renewable energy resources that widely used and grow rapidly in fulfilling electricity demand. Powers from both technologies depend on sunlight intensity and wind speed. For small scale power generation, DC voltage from both technologies is low and requires step-up converter to raise DC voltage ratio before converted into AC voltage. To optimize this system, step-up converter must have high ratio and efficiency to a distance of wide voltage input. This paper proposed an operation simulation and arrangement of DC-DC converter along with DC-AC from hybrid source PV-Wind which integrated to grid utilities without using storage device. High Gain Integrated Cascade Boost (HGICB) is DC-DC converter that has quadratic voltage ratio and used in this research. Then DC link connected to Voltage Source Inverter (VSI) which interconnected with utility grid and controlled by current control method. The total installed capacity of hybrid source is 4.4 kW. Wind turbine uses PMSG along with full bridge rectifier. To maximize and stabilize the generated power, MPPT fuzzy is used. Result from the simulation shows that converter capable to maintain maximum power whether from PV and wind turbine which canalized to utility grid in various irradiation condition, wind speed, and grid load alteration.

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research attempted to control a Four-Leg Inverter (FLI) on microgrid rooftop solar (MGRS), which connects to a distribution network (grid) via a distribution transformer. The connected load on an MGRS system comprises two loads: nonlinear load and unbalanced linear load. Rooftop Solar (RS) injection current on each grid phase fluctuated depending on irradiation value. Load and irradiation fluctuations and RS capacity differences on every phase caused the transformer’s current unbalance and harmonic. Since the pulled current load varied between grid phases, the current load’s instantaneous fundamental power demand (active and reactive) also differs for each phase. Optimized Constructive Neural Network (OCNN) with single-phase PQ theory was utilized to independently control FLI in every phase determined by fundamental power demand. Therefore, a transformer would perceive load and RS injection as balanced despite varied and unbalanced conditions. OCNN builds networks by self-constructive methods. Each training session enables the addition of new hidden layers and neurons inside each layer. The OCNN network compares the error value associated with the training results to the error value associated with the temporary best network (TBN). Throughout each training session, this comparison is made to determine the network with the lowest error value or the global best network (GBN). The frequent irradiation fluctuation indicated that the system often stayed in a transient rather than a steady-state. In high transient conditions, the performance of the proposed controlling method had been tested in simulations. The result revealed that the OCNN controller obtains the lowest peak values under high transient conditions, namely 2.62% for PCU and 6.73%, 7.33%, and 6.63% for THDi, respectively, at phases A, B, and C. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Boost rectifiers are commonly used as the input for power inverters. The output voltage of the boost rectifiers should have high quality and precise value to enable the power inverters to achieve maximum performance. However, the grid occasionally supplied unbalanced voltage and current to the boost rectifiers so that the performance of the rectifiers is impaired. When unbalanced AC voltages occurred, the frequency of DC voltage ripples may become two times higher than the AC voltage frequency. The unbalance voltage and current may occur when the grid is supplied by several single-phase Distribution Generators (DGs) with varied capacities. This condition becomes more complicated if the DG is renewable energy in which the output power is intermittent. This study proposes a novel three-phase pulse-width modulated (PWM) boost rectifier control using Voltage Oriented Control (VOC) with a Combined error adaptive fuzzy-PI (CEAF). CEAF is a combination of the Delta error adaptive fuzzy (DEAF) and the Absolute error adaptive fuzzy (AEAF). DEAF is a self-tuning fuzzy-PI method that is generally used as an adaptive fuzzy controller with inputs of errors e(t) and delta error de(t). As for AEAF, it is a modified DEAF of which the inputs are the absolute values of e(t) and de(t). This adaptive Fuzzy-PI is used to determine Kp and Ki values that suit the needs, especially when the sources are fluctuating or unbalanced. The performance of the proposed controller is then compared with a conventional DEAF and with a well-adjusted PI controller. Based on the simulation in Matlab/Simulink, the proposed method would result in a significant reduction in DC voltage ripples and DC steadystate error when fluctuating, unbalanced voltages occur. The resulted ripple voltage decreases from 0.16% to become 0.12%. The steady-state error decreases from 0.27% to become 0.19%. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposed a Hybrid PI-Fuzzy based Static Var Compensator for minimizing voltage deviations as the integration of wind power generation to the distribution network. Hybrid PI-Fuzzy Logic controller constructed by the cascade-connected conventional PI controller and Fuzzy Logic controller. This algorithm combined the advantages and minimized the disadvantages of each conventional controller. The control method applied to the Static Var Compensator, which functioned as a dynamic reactive power source. The controlled dynamic reactive power source influenced the system with proper reactive power value, which resulted in the voltage regulation. Two scenarios were carried out to investigate the efficacy of the proposed method. The first scenario demonstrates the performance of the proposed system in wind speed variations and the second scenario in load variation conditions. Finally, the comparisons with Fuzzy Logic Controller-based self-tuning PI control were made to investigate the performance of the proposed control method. Simulation results verified that the proposed control algorithm outperformed the FLCbased self-tuning PI controller, in terms of the steady-state voltage deviation minimization by 1.47% and the settling time of the voltage respond decrement by 92.78%. [ABSTRACT FROM AUTHOR]

To concentrate the rays to the focal point and stabilize the temperature on the receiver were one of the complex works of the two-stage solar concentrator. This paper offers a new method of Fuzzy cascade controller system based on tuning up the optimization at Genetic Algorithm-simple additive weighting (GA-SAW) on the dual parabolic dish concentrator with Compound Parabolic Concentrator. The model and computation of three degrees of freedom robotic arm movement with the ray tracing method were used as the concentrator position predictor. In this research, the acquired fuzzy controller result had an average settling time 0.497 sec, and average rise time 0.277 sec faster than a conventional PID controller. This research was able to overcome the disturbance which was diffused rays, so there was a better output with the power and heat flux increased up to 62.49%. The monte carlo ray tracing method from Tonatiuh Software was used to investigate and movement validation of the dual parabola concentrator by showed the flux distribution on the receiver’s absorber. In the last stage, an experiment with a prototype had been conducted as a response verification of the controller system which produce a receiver temperature output as high as 121ºC. The final result showed that the controller system managed to optimize the temperature on the receiver’s absorber and generate a stable thermoelectric output with power of 1.01 Watt. [ABSTRACT FROM AUTHOR]

In this paper, we propose design of the boost converter with hybrid transformer ratio for hybrid power source charging station. This converter is addressed as DC step up converter. This converter has high ratio conversion that converter to DC bus 24 Volt to AC system 220Volt. The combination between resonance modes and pulse width modulation (PWM) is used to achieve high voltage ratio conversion. The advantage of proposed method is use only single switching device; therefore it is easy to control. Moreover, voltage stress on diode and switching device is relatively low and independent from input voltage. The experiment result show that the converter is able to operates in wide range input voltage and has good conversion efficiency up to 90%. Based on the operation and conversion characteristic, the converter can be operated in power inverter with duty ratio 0.7-0.8 to synchronizing with AC system. [ABSTRACT FROM AUTHOR]

This paper presents a control called Maximum Power Point Tracking (MPPT) for photovoltaic (PV) system in a solar car. The main purpose of this system is to extracts PV power maximally while keeping small losses using a simple design of converter. Working principle of MPPT based fuzzy logic controller (MPPT-FLC) is to get desirable values of reference current and voltage. MPPT-FLC compares them with the values of the PV's actual current and voltage to control duty cycle value. Then the duty cycle value is used to adjust the angle of ignition switch (MOSFET gate) on the Boost converter. The proposed method was shown through simulation performed using PSIM and MATLAB software. Simulation results show that the system is able to improve the PV power extraction efficiency significantly by approximately 98% of PV's power. [ABSTRACT FROM AUTHOR]

The target of stand-alone hybrid power generation system was to supply the load demand with high reliability and economically as possible. An intelligent optimization technique using Genetic Algorithm is required to design the system. This study utilized Genetic Algorithm method to determine the optimal capacities of hydrogen, wind turbines and micro-hydro unit according to the minimum cost objective functions. The minimum cost values to these two factors. In this study, the cost objective function included the annual capital cost, annual operation maintenance cost, annual replacement cost and annual customer damage cost. The proposed method will be used to optimize the hybrid power generation system located in Leuwijawa village in Central Java of Indonesia. Simulation results showed that the optimum configuration can be achieved using 19.85 ton of hydrogen tanks, 21x100 kW wind turbines and 610 kW of micro-hydro unit respectively. [ABSTRACT FROM AUTHOR]