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Analysis of an Off-grid PV System for Disaster Mitigation Scheme in Remote Areas Pinto Anugrah; Putty Yunesti; Guna Bangun Persada
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 1 No. 1 (2021): May 2021
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v1i1.10

Abstract

The main objective of this paper is to present the techno-economic analysis of an off-grid Photovoltaic system, which prepared to support disaster mitigation scheme in remote areas. As a case study, a regency in Mentawai Island, Sumatera Barat is chosen to represent a remote area in a disaster-prone location. The proposed system capacity is 20 kWp PV system as a single electricity source for medical facility in the island. As a tool in this study, RETScreen software was used to analyze the technical, environmental, and economical feasibility analysis. As a base case scenario, the medical facility was supported by a diesel-fueled generator and the PV system can deliver 10.14 MWh of electricity to load annually. Net annual GHG emission reduction of the system is 19.4 ton of CO2 equivalent. With the total initial cost for the whole PV system at USD 41,380, RETScreen simulation result showed that the equity payback of the project is 6.0 years with IRR of 11.9% hence the project is financially viable.
Path Planning for Mobile Robots on Dynamic Environmental Obstacles Using PSO Optimization Fahmizal Fahmizal; Innes Danarastri; Muhammad Arrofiq; Hari Maghfiroh; Henry Probo Santoso; Pinto Anugrah; Atinkut Molla
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i1.28513

Abstract

The increasing integration of mobile robots in various industries necessitates efficient navigation strategies amidst dynamic environments. Path planning plays a crucial role in guiding mobile robots from their starting points to target destinations, contributing to automation and enhancing human-robot collaboration. This study focuses on devising a tailored path-planning approach for a fleet of mobile robots to navigate through dynamic obstacles and reach designated trajectories efficiently. Leveraging particle swarm optimization (PSO), our methodology optimizes the path while considering real-time environmental changes. We present a simulation-based implementation of the algorithm, where each robot maintains position, velocity, cost, and personal best information to converge towards the global optimal solution. Different obstacles consist of circles, squares, rectangles, and triangles with various colors and five handle-points used. Our findings demonstrate that PSO achieves a global best cost of 5.1017, indicative of the most efficient path, minimizing overall distance traveled.
Control and Navigation of Differential Drive Mobile Robot with PID and Hector SLAM: Simulation and Implementation Fahmizal Fahmizal; Matthew Sebastian Pratikno; Hidayat Nur Isnianto; Afrizal Mayub; Hari Maghfiroh; Pinto Anugrah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29428

Abstract

Navigation technology is essential in fields like transportation and logistics, where precise mapping and localization are critical. Simultaneous Localization and Mapping (SLAM) technologies, such as Hector SLAM, enable robots to map environments by detecting and predicting object locations using sensors like LiDAR. Unlike other SLAM methods, Hector SLAM operates without odometry, relying solely on LiDAR data to produce accurate maps. This study investigates the application of Hector SLAM in a differential drive mobile robot controlled via the Robot Operating System (ROS), with PID control managing the motor speeds. The research contribution is the integration of Hector SLAM with PID control to enhance mapping accuracy in environments without odometry data. The method involves testing the robot's mapping performance in an indoor environment, focusing on the impact of varying linear and angular velocities on the quality of the generated maps. The PID control was tuned to ensure stable speed values for the robot's differential drive motors. Results show that Hector SLAM, when combined with well-tuned PID control, generates highly accurate maps that closely match the actual environment dimensions, with minimal errors. Specifically, the mapping error was found to be within 0.10 meters, validating the effectiveness of this approach in non-odometric systems. In conclusion, the study demonstrates that Hector SLAM, supported by PID-controlled motor stability, is an effective solution for mapping in differential drive mobile robots, particularly in scenarios where odometry is unavailable.