Dwi Nur Fitriyanah

Bio: Dwi Nur Fitriyanah is an academic researcher from Sepuluh Nopember Institute of Technology. The author has contributed to research in topics: Solar tracker & Photovoltaic system. The author has an hindex of 3, co-authored 10 publications receiving 17 citations.

Design and Implementation of Mobile Active Two-Axis Solar Tracker with Reflector Based on Particle Swarm Fuzzy Controller

Abstract: Sun tracking system, or solar tracker, is an electronic device consisting of several electrical and mechanical elements, which serves to guide the solar panels in order to make them follow the sun position accurately and to generate the maximum solar energy reception. Sun tracking system is a solution offered in order to use solar energy optimally. The two-axis solar tracking system can absorb solar energy better than a single axis solar tracking or PV fixed system. The two-axis active sun tracking system uses an LDR (Light Dependent Resistor) sensor in order to capture the powerful solar lighting to be received by PV (photovoltaic). Four LDR sensors are used to represent the position of the sun that is north, south, west, and east. This research applies a modified particle swarm fuzzy-based control to be used in the system so that the solar panel system is more effective and responsive to sunlight position changes. The results show that the control method is capable of applying well with a 70-degree reflector. This can be noticed from the results of the steady-state error performance index in the pitch and the yaw tests that are 0.638% and 0.312%, whereas for the other performance indexes including rise time, settling time and Maximum Overshoot (MOV) for both tests are 7 seconds, 9 seconds, 0% and 4 seconds, 6 seconds and 0% respectively. The mobile active solar tracker built can increase energy gain of 43.01% compared to fixed system.

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

Abstract: 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 ...

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

Abstract: 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.

Fuzzy Logic Control Design of Mobile PV Using Bacterial Foraging Optimization

Abstract: One of the new renewable energy types is solar energy. Solar energy can be converted into electrical energy through photovoltaic. In order for the intensity of sunlight is received by the photovoltaic more leverage, so that made the solar tracker system with two axes. Solar tracking system control the pitch and yaw angle that can drive a DC motor. Optimize error and delta error on sun tracking system based on fuzzy logic. The boundaries of fuzzy are optimized using the Bacterial Foraging Optimization (BFO) method. Mobile PV using fuzzy control and BFO has better performance than Fuzzy Logic Controller with an efficiency increase by 0.4%.

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

Abstract: 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.

Two Decades of Condition Monitoring Methods for Power Devices

Abstract: Condition monitoring (CM) of power semiconductor devices enhances converter reliability and customer service. Many studies have investigated the semiconductor devices failure modes, the sensor technologies, and the signal processing techniques to optimize the CM. Furthermore, the improvement of power devices’ CM thanks to the use of the Internet of Things and artificial intelligence technologies is rising in smart grids, transportation electrification, and so on. These technologies will be widespread in the future, where more and more smart techniques and smart sensors will enable a better estimation of the state of the health (SOH) of the devices. Considering the increasing use of power converters, CM is essential as the analysis of the data obtained from multiple sensors enables the prediction of the SOH, which, in turn, enables to properly schedule the maintenance, i.e., accounting for the trade-off between the maintenance cost and the cost and issues due to the device failure. From this perspective, this review paper summarizes past developments and recent advances of the various methods with the aim of describing the current state-of-the-art in CM research.

A New Maximum Power Point Tracking Framework for Photovoltaic Energy Systems Based on Remora Optimization Algorithm in Partial Shading Conditions

Abstract: In this paper, a new maximum power point tracking (MPPT) framework for photovoltaic (PV) systems is presented based on the remora optimization algorithm (ROA) subjected to standard and partial shading conditions. The studied system includes a PV array, a DC/DC converter, and a load and MPPT control system. The control variable is the voltage, and the optimization variable is the converter duty cycle, which is optimally determined using the ROA that is inspired based on the parasitic behavior of remora for achieving the maximum power of the PV system. In this study, the ability of the ROA is compared with manta ray foraging optimization (MRFO) and particle swarm optimization (PSO) methods for the MPPT solving of different shading patterns in view of extracted power, efficiency, and tracking rate. The results show that the ROA is a competitive method with higher efficiency in maximum power tracking and convergence accuracy than the MRFO and PSO for the MPPT solving of different patterns with higher exploration power. Moreover, an examination of the two partial shading patterns also showed that the power extracted using the ROA is higher than the MRFO and PSO while also reaching the global power value more quickly. The ROA achieved a tracking efficiency of 99.97% in a partial shading condition, with faster tracking in comparison with the MRFO and PSO methods. Therefore, the ROA is a high-speed tracking optimization method for enhancing the PV system’s efficiency in standard and especially in shading conditions.

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

Abstract: 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.

Numerical Simulation for Optimization of ZnTe-Based Thin-Film Heterojunction Solar Cells with Different Metal Chalcogenide Buffer Layers Replacements: SCAPS-1D Simulation Program

Abstract: In this study, Zinc Telluride (ZnTe)-based solar cells, which are metallic dichalcogenide materials, are used as a solar cell absorbent with the formation appropriate for solar cell use. The data has been analyzed by SCAPS-1D structures software. The replacement of Cadmium Sulfide CdS (buffer) layer by other green and save suitable materials has been investigated. The substituted buffer layers have been ZnSe, ZnS, CdSe, and In2S3. The higher device performance efficiency parameters have been found out when using CdS and ZnSe as buffer layers. SCAPS-1D shows that the optimal p-n junction device eff]iciency parameters have been achieved when the ZnTe (absorber) layer thickness is between 1200-1500 nm, while the ZnSe (buffer) layer thickness is between 20-60 nm, and the thickness of ZnO:Al (window) layer is 25 nm. The results of the simulation provide important hints that may enhance the performance of the cell with empirical studies useful in practical implementation.

Optimal Phase Arrangement of Distribution Transformers for System Unbalance Improvement and Loss Reduction

Abstract: This paper presents an efficient strategy for transformer planning to reduce the system losses by means of transformer rearrangement. The customer connected to the distribution transformer are first investigated by the field survey, and the loads of the various customers are collected from the customer information system (CIS) and distribution database system (DAS) to derive their load patterns. The objective function is to minimize the total line loss in the 24 intervals. An improved bacterial foraging algorithm (IBFO) is proposed herein to find the optimal phase combination of distribution transformers to minimize the total line loss by considering operating constraints. A three-phase load flow program with Eeuivalent current injection (ECT) is used to solve the total line loss and system unbalance factor on a Taipower distribution system. The results can help operators not only perform the proper installation phase selection of distribution transformers, but also reduce the system losses, decrease the system unbalance factor, and improve the voltage profiles of the buses.