Power Quality Enhancement of Integration Photovoltaic Generator to Grid under Variable Solar Irradiance Level  using MPPT-Fuzzy

This paper presents modeling and simulation of maximum power point tracking (MPPT) used in solar PV power systems. The Fuzzy logic algorithm is used to minimize the error between the actual power and the estimated maximum power. The simulation model was developed and tested to investigate the effectiveness of the proposed MPPT controller. MATLAB Simulink was employed for simulation studies. The proposed system was simulated and tested successfully on a photovoltaic solar panel model. The Fuzzy logic algorithm succesfully tracking the MPPs and performs precise control under rapidly changing atmospheric conditions. Simulation results indicate the feasibility and improved functionality of the system. Keyword:Fuzzy logic algorithm Maximum power point tracking MPPT Photovoltaic Simulink Copyright © 2018 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Ahmad Saudi Samosir, Departement of Electrical Engineering, University of Lampung, No. 1, Jln. Prof. Soemantri Brojonegoro, Bandar Lampung, 35152, Indonesia. Email: ahmad.saudi@eng.unila.ac.id INTRODUCTIONThe growing energy demand of the world and the tremendous risk of climate change associated with the use of fossil fuels have driven research and development of alternative energy sources that are clean, efficient, renewable and environmentally friendly. Among all renewable energy sources, solar power systems attract more attention because they have several advantages such as pollution-free, low maintenance costs and low operating costs. Their sources of energy, which is derived from solar energy, are also widely available and it is free [1]- [4].In solar power system, the solar energy is directly converted into electrical energy by solar PV module. The main components of solar PV systems are solar cells made from semiconductor materials that have a photovoltaic effect, which serves to convert solar energy into direct current electricity. When exposed to sunlight; the solar panels will generate the direct current electricity, which is ready to supply power to the load. Solar Panels do not need much maintenance and have no moving parts. The unfavorable issue with solar PV systems is the high installing cost and the variation of energy form the solar panel with environmental conditions. In order to attain the maximum efficiency from the solar panel, it is important to obtain the maximum available power at any operating condition [5]. Also, the power distribution across the system has to be managed. Storage devices are used so that the energy is stored or supplied according to the availability of sufficient power and the load requirements [6].The efficiency of solar cells depends on many factors such as temperature, irradiance, spectral characteristics of sunlight, dirt, shadow, and so on. Changes in insolation on panels due to fast climatic changes such as cloudy weather and increase in ambient temperature can reduce the photovoltaic (PV) array

Section: Solar Photovoltaic Modelmentioning

confidence: 99%

Modeling and Simulation of Fuzzy Logic based Maximum Power Point Tracking (MPPT) for PV Application

Samosir

Gusmedi

Purwiyanti

et al. 2018

“…In general, current and voltage wave form of pure sinusoidal waves. One problem that occurs is non sinusoida or distorted current and voltage waves generated by harmonics in the power system [11]. Harmonic is distorted periodic steady state wave caused by the interaction between the shape of a sine wave at the fundamental frequency system with another wave component which is an integer multiples frequency of fundamental frequency.…”

Section: Voltage/current and Unbalance Harmonicsmentioning

confidence: 99%

“…For most applications, it is sufficient to consider the harmonic range from the 2 nd to 25 th , but most standards specify up to the 50 th . Second harmonic index is current THD means the ratio of rms harmonic current value to rms fundamental current which expressed in (7) [11]. Where V n and I n (the rms voltage and current at harmonic n), V 1 and I 1 (the fundamental rms voltage and current), N (the maximum harmonic order to be considered).…”

Section: Voltage/current and Unbalance Harmonicsmentioning

confidence: 99%

Multi Units of Three Phase Photovoltaic using Band Pass Filter to Enhance Power Quality in Distribution Network under Variable Temperature and Solar Irradiance Level

Adiananda¹,

Kiswantono²,

Amirullah³

2018

Self Cite

The paper proposed power quality enhancement on three phase grid of point common coupling (PCC) bus due to integration of multi units of photovoltaic (PV) to 380 volt (phase-phase) 50 Hz low voltage distribution network under variable temperature and irradiance level. The band pass filter models (single tuned and double tuned) were installed to improvement power quality on the conditions i.e. without filter, with single tuned filter, and with double tuned filter. Multi units of PV generator without filter, with single tuned, and with double tuned filter at all temperatures and irradiance levels resulted in relatively stable phase voltage (308 and 310 volt), so able to generate an unbalanced voltage of 0%. The maximum phase current for the system without filter at all temperatures and radiation levels of 9.8, 12.5, and 10 ampere respectively, resulted in an unbalanced current of 16.10% . Under the same condition, single tuned and double tuned filters were able to balance phase current to 10.45 A and 10.44 ampere respectively, resulting in an unbalanced current of 0%. Implementation of single tuned and double tuned filters was able to reduce unbalance current according to ANSI/IEEE 241-1990. At constant temperature and irradiance increased, both average voltage and current harmonics also increased. Double tuned active filter was the most effective to suppress the 11th and 13th harmonics so that capable to migitate average voltage and current harmonics better than system using single tuned filter which could only reduce 5th harmonic within IEEE 519-1992.

“…The spreading of intelligent control exists on some fields such as: Electrical and electronic engineering, and computer science such as: Fuzzy controller is used to enhance photovoltaic generator power quality by maintaining the MPPT tracking on low voltage side of DC/DC boost converter. The MPPT-fuzzy controller is able to maintain voltage profile and current total harmonic distortion (THD) [1]. The performance of fuzzy controller is compared to the PI controller on two inverter fed to control six-phase permanent magnet synchronous machine (PMSM) operated as a motor.…”

Section: Introductionmentioning

confidence: 99%

Coordination of Adaptive Neuro Fuzzy Inference System (ANFIS) and Type-2 Fuzzy Logic System-Power System Stabilizer (T2FLS-PSS) to Improve a Large-scale Power System Stability

Muljono¹,

Ginarsa²,

Nrartha³

et al. 2018

Intelligent control included ANFIS and type-2 fuzzy (T2FLS) controllers grown-up rapidly and these controllers are applied successfully in power system control. Meanwhile, small signal stability problem appear in a largescale power system (LSPS) due to load fluctuation. If this problem persists, and can not be solved, it will develop blackout on the LSPS. How to improve the LSPS stability due to load fluctuation is done in this research by coordinating of PSS based on ANFIS and T2FLS. The ANFIS parameters are obtained automatically by training process. Meanwhile, the T2FLS parameters are determined based on the knowledge that obtained from the ANFIS parameters. Input membership function (MF) of the ANFIS is 5 Gaussian MFs. On the other hand, input MF of the T2FLS is 3 Gaussian MFs. Results show that the T2FLS-PSS is able to maintain the stability by decreasing peak overshoot for rotor speed and angle. The T2FLS-PSS makes the settling time is shorter for rotor speed and angle on local mode oscillation as well as on inter-area oscillation than conventional/ ANFIS-PSS. Also, the T2FLS-PSS gives better performance than the other PSS when tested on single disturbance and multiple disturbances. Keyword: ANFIS INTRODUCTIONController based on artificial intelligent is the research topic interest in recent year. Because the intelligent control has learning ability to improve its performance from the environment where the controller is applied. The spreading of intelligent control exists on some fields such as: Electrical and electronic engineering, and computer science such as: Fuzzy controller is used to enhance photovoltaic generator power quality by maintaining the MPPT tracking on low voltage side of DC/DC boost converter. The MPPT-fuzzy controller is able to maintain voltage profile and current total harmonic distortion (THD) [1]. The performance of fuzzy controller is compared to the PI controller on two inverter fed to control six-phase permanent magnet synchronous machine (PMSM) operated as a motor. The simulation results show that the fuzzy controller are more robust, quick response on high starting torque and more effective the PI controller [2]. Support vector machine (SVM) method is used to classify a large-scale power system transient stability. The SVM method gives a better result than multi-layer perceptron-neural network (MLP-NN)