Global Positioning System (GPS) has become important and necessary in daily life. It is possible to reach any destination using GPS, which is included in many lands and marine applications. In this work, GPS was applied to a real navigation boat, integrated with the inertial navigation system (INS) device, and installed on the boat. The navigational devices were linked to the (mission planer) program, through which the results of the navigation process were shown. The system can provide better navigation performance accuracy and reliability due to the integration between GPS and INS. The data extracted from the navigation devices are processed using the Gaussian process (GP) prediction algorithm, to perform the GPS synchronization with the INS and predict the GPS cut-off values for specified periods. The prediction results of the GP algorithm are effective for the cut-off GPS data as the apparent error amount of the algorithm is low. In addition the inertial navigation system provides the location, speed, and position of the boat, but it contains a cumulative error that increases over time. On the other hand, the GPS better accuracy with a lower data rate than the INS, so the integration system between INS/GPS is necessary. It must be developed to overcome the negatives in both systems. Two types of integration were introduced and implemented herein: loosely and tightly. From the results obtained, one can see that the tight system is better at improving errors.
Due to increased load demands, distribution systems suffer from high power losses, low voltage levels, high current, and low reliability. To solve these problems, integrate distributed generator units (DG) into the distribution system. DG units are among the most popular methods of improving distribution system reliability, power losses, and bus voltage improvement through the placement and selection of distributed generator units in an optimal location and size. This work proposed Enhanced Particle Swarm Optimization (EPSO) technology to find the optimum location and size of DG units to reduce power losses, improve bus voltage level, and employed the Transient Electricity Analyzer (ETAP) to evaluate the reliability of the distribution system network. ETAP is a programming tool for modeling, analysis, design, optimization, operation, and control of electrical power systems. These findings may be useful in conducting reliability assessments and correctly utilizing dispersed generation sources for future power system growth by power utilities and power producer companies. The proposed method was employed on the Iraqi distribution system (AL-Abasia distribution network (F10 feeder)). After adding three DG units to the distribution system, theer adding three DG units to the distribution system, the obtained simulation results showed a significant reduction in power losses, voltage levels, and reliability enhancement.
This work presents an Energy Management System (EMS) constructed on dissimilar power balance modes and dynamic grid power to activate a DC-link microgrid with a solar (PV-array) generator and battery storage. In addition, the option of requesting adjustable power from the grid to encounter load demand is also presented. Based on the availability of solar sources, battery state, and grid power, energy management offers the appropriate references for all modes. Six power balance options are defined based on power supply, storage system, and grid mobility to match the load requirement. The aims are to reduce energy usage and upsurge the life of the storage device. The microgrid is controlled to maintain a consistent DC-link voltage and manage the battery current depending on the mode of operation. Using MATLAB\SIMULINK software, the anticipated energy management system, which is based on power balancing modes, is tested under various scenarios. The simulation results demonstrated that the microgrid operated admirably, with seamless switching between power balance modes.
The performance of antennas is critical to ensuring reliable wireless communication and robust data transmission. Unfortunately, antennas’ performance gets degraded when loaded with lossy materials. This paper presents the numerical and experimental evaluation of low-profile antennas’ performance when integrated with photovoltaic (PV) solar cells for potential use in smart grid and green power networks. Such integrated antennas can serve as a communication unit and sensors to monitor PV solar cells. For convenience, a microstrip patch antenna was used in this assessment study, where the antenna was designed, numerically simulated, and experimentally tested. After which, it was installed on top of a PV solar cell at different orientations. The antenna is designed to operate within the 2.45 GHz ISM band. Based on the results, the antenna performed well when placed at the middle of the PV solar cell with a peak gain of 2.58 dBi compared to other placements within the PV solar cell. Moreover, creating a small air gap between the antenna and the PV solar cell results in better performance. Based on the findings of this study, the antenna has satisfactory performance when integrated with PV cells, which is promising to deploy in many applications, including smart grid networks.
Inductance – Capacitance – Inductance (LCL) filter is a very attractive candidate for renewable energy system applications due to its high efficiency. High attenuation of the switching frequency harmonics, small size, low fee, and improving the overall harmonic distortion (THD). This paper presents how voltage is affected by increased loads or voltage sag. Therefore it is necessary to control it with certain controllers. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used as an intelligent controller, the voltage constraint as training data for ANFIS obtained from PI. The filter works in a good connection between the inverter and the grid and rewords unwanted harmonics from using the inverter. The mathematical models for the LCL filter are investigated. The proposed approach shows more effective results than previous performance for voltage controlling and harmonic reduction. It gives overshoot (0.5%), steady state error (0.005), settling time (0.03 sec), rise time (0.005 sec), and improving THD 8.67% to 2.33% by comparing these results of ANFIS respectively with the results of PI which gave(3%),(0.01),(0.2sec)and( 0.02sec).