Design of battery charging system on solar tracker based PV system and its application has been presented in this paper. To improve the system performance, a solar tracking system as an innovative device of PV has been developed with an intelligent controller. PV equipped by solar tracker can significantly enhace its performance up to 40% of conventional system. In this research solar tracker designed has active tracking mode with double axis. In order to keep the PV performance optimum, a smart battery charging system has been developed and provided to store the electricity generated by PV system. A novel algorithm was implemented to the system which allows the battery charging process to operate quickly and safely. Besides, the components involved in the system are DC-DC converter, sensor, actuator and battery. DC-DC Converter used is Single Ended Primary Inductance Mode (SEPIM) with MOSFET as its actuator. Battery charging system has used intelligent control based on fuzzy-PSO algorithm. In this case, PSO functions to optimize and modify fuzzy parameters to obtain the best model. Optimized fuzzy controller has then been implemented and programmed in an Arduino microcontroller module to generate control signal which commands actuator element to control the voltage of battery through duty cycle manipulation variable. This algorithm has been able to improve the solar charging controller significantly and more convincingly increase PV performance.

Design and implementation of battery charging system on solar tracker based stand alone PV using fuzzy modified particle swarm optimization

World energy consumption increases with time, so that occur an energy imbalance. Many breakthroughs have developed to utilize renewable energy. The photovoltaic system is one of the easy-to-use renewable energies. The power conversion from PV fixed is still low, so the PV system is designed using the active dual-axis solar tracker. The PV tracker position can be adjusted to change the sun position to get maximum efficiency. The active dual-axis solar tracker system is integrated with the maximum power point tracking (MPPT) algorithm to keep PV operating at a maximum power point even though input variations change. The active dual-axis solar tracker system integrated with the maximum power point tracking (MPPT) algorithm to keep PV operating at a maximum power point even though input variations change. Tracking test simulation had done by comparing the output power of a fixed PV system with the active dual-axis solar tracker. Type-2 fuzzy logic based MPPT successfully increased the average output power by 10.48 % with the highest increase of 17.48 % obtained at 15:00 West Indonesia Time (GMT+7). The difference in power from a fixed PV system with the active dual-axis solar tracker of 36.08 W is from the output power worth 206.3 to 242.4 W.

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Performance Study of Maximum Power Point Tracking (MPPT) Based on Type-2 Fuzzy Logic Controller on Active Dual Axis Solar Tracker

The location of Indonesia which, is crossed by the equator, makes it rich in sunlight. Photovoltaic (PV) can convert solar energy into electrical energy. The Solar Tracker system can maximize the absorption of solar energy that enters the PV. The condition of the Indonesian archipelago also has the potential for ocean wave energy. The Hydrostatic transmission-based Wave Energy Converter system can convert ocean wave energy into electrical energy. This research combines two energies, namely solar energy and ocean waves. The importance of combining these two renewable energies is due to the non-continuous nature of solar energy, therefore combined with the ocean wave energy to maximize the energy produced. A type-2 fuzzy logic control system based on Bacterial Foraging Optimization (BFO) is applied to each converter, summing each converter that has been optimizing. Optimize error and delta error on the solar tracker system and fuzzy logic waveform-based sea-wave type-2 system. The fuzzy boundaries are then optimized using the BFO optimization method. Fuzzy type-2 based on BFO in solar tracking system can increase energy by 67.9% with the best performance at FOU ±0.1. BFO-based type-2 fuzzy control can stabilize the output of the ocean wave conversion system and produce average energy of 34.48 Wh. This research can increase the energy in the system after being optimized using BFO by 19.3%.

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Design of Bacterial Foraging Interval Fuzzy Logic Controller on Hybrid Solar Tracker-Ocean Wave Energy Converter

Design of data transmission system on solar energy station based on Internet of Things (IoT) using a wireless network

The proposed system is a hybrid charging system between a solar tracker and an electric grid using two converter types. The photovoltaic (PV)-based solar tracker has powerful tools, but its weakness is when the absence of sunlight. With a combination of two resources, the weakness can overcome. The control so good is needed so that it can overcome those weaknesses too. This study uses the flower pollination algorithm optimization-fuzzy logic controller (FPAO-FLC). Results of control using FPAO-FLC has a value of a rising time of 0.0123 seconds, settling time of 2.1099 seconds, maximum overshoot of 6.08%, a peak time of 0.9246 seconds, and steady-state error of 3.43%. The efficiency of the ZETA converter using FPAO-FLC control in the tracking condition PV compared to the fixed condition has increased 43, 24%, and the state of charge (SOC) of the battery reaches 39.08%. The advantage of this hybrid system is that it has two modes of operation, which are automatic, including simultaneous and individual operating modes. The data collection results show that the energy obtained by the individual grid mode dan the individually solar tracker mode is 92.62 Wh and 310.38 Wh. The total energy obtained was 479.81 Wh.

Design and building of a battery charging system using hybrid solar tracker and electric trip based on FPAO-FLC

The renewable energy currently becomes a research topic that is constantly being improved. Efforts to find alternative energy sources as a substitute for fossil fuels still continue to be discussed. Indonesia is geographically located on the equator has a big potential for solar energy. It can’t be utilized optimally because still constrained conversion of PV modules that still relatively low. One of the solutions offered is to fit up solar panels with solar tracking system and Maximum Power Point Tracking (MPPT) algorithm. The method of solar tracking system seeks PV panels always perpendicular to the direction of sunlight, whereas MPPT serves to trace the maximum power PV may produce in various climatic conditions. In this study, MPPT-based Fuzzy-Particle Swarm Optimization (PSO) which integrates with fixed and tracking PV panel system to increase PV module power conversion. PSO plays a role in the search for the best fuzzy membership function parameters designed based on the defined objective function that is Mean Square Error (MSE). The result shows that MPPT Fuzzy-PSO solar tracker can increase the power output from PV by 28.84% for 10 hours of operation compared with MPPT Fuzzy-PSO fixed system.The renewable energy currently becomes a research topic that is constantly being improved. Efforts to find alternative energy sources as a substitute for fossil fuels still continue to be discussed. Indonesia is geographically located on the equator has a big potential for solar energy. It can’t be utilized optimally because still constrained conversion of PV modules that still relatively low. One of the solutions offered is to fit up solar panels with solar tracking system and Maximum Power Point Tracking (MPPT) algorithm. The method of solar tracking system seeks PV panels always perpendicular to the direction of sunlight, whereas MPPT serves to trace the maximum power PV may produce in various climatic conditions. In this study, MPPT-based Fuzzy-Particle Swarm Optimization (PSO) which integrates with fixed and tracking PV panel system to increase PV module power conversion. PSO plays a role in the search for the best fuzzy membership function parameters designed based on the defined objective function ...

Arfa Ul Umam

Papers

Design of maximum power point tracking (MPPT) on two axes solar tracker based on particle swarm fuzzy