Laith Abualigah
Al al-Bayt University

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An intelligent converter and controller for electric vehicle drives utilizing grid and stand-alone solar photovoltaic power generation systems G. Saikiran Reddy; M. Premkumar; Suraj Ravi; Laith Abualigah
International Journal of Applied Power Engineering (IJAPE) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v12.i3.pp255-276

Abstract

In this study, a battery energy management system for electric vehicle (EV) applications is proposed with a standalone photovoltaic (PV) source and controlled based on the availability of grid, PV source, load consumption, and energy stored in the battery. This paper proposes a single-ended primary-inductance converter (SEPIC) DC-DC converter for charging the battery through the utility and PV source that provides good load regulation. The bidirectional nature of the proposed DC-DC converter provides the charging and discharging of the EV battery in the succeeding modes of operation, i) grid-tied charging, ii) PV-tied charging, iii) discharging to the load in the absence of utility and PV source, and iv) regenerative braking. An improved perturb and observe-based maximum power point tracking (MPPT) algorithm is proposed to track the maximum power from the PV source. In addition, to handle the four modes of operation, a dedicated controller is also proposed. Firstly, the proposed system is validated using MATLAB/Simulink software by considering different operating conditions, and the performance is compared with the traditional MPPT algorithms. Finally, the effectiveness of the suggested system is validated through an experimental prototype. The result proved the superiority of the converter and controller over the traditional systems. 
Power sharing based on starfish optimization algorithm in DC microgrid Widi Aribowo; Laith Abualigah; Diego Oliva; Abubakar Umar; Aliyu Sabo; Hisham A. Shehadeh
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.9784

Abstract

This paper presents a starfish optimization algorithm (SFOA) method for optimizing control parameters in DC microgrids. SFOA is a new metaheuristic inspired by biology to solve optimization problems, which simulates the behavior of starfish, including exploration, preying, and regeneration. SFOA consists of two main phases of exploration and exploitation. This paper evaluates the performance of SFAO on droop control of DC microgrids by comparing with walrus optimizer (WO) and grasshopper optimization algorithm (GOA). From the simulation, SFOA shows superior capability. Validation on DC microgrid control using integral of time-weighted absolute error (ITAE) and integral of time-weighted squared error (ITSE). Simulation results demonstrate that the proposed technique exhibits a superior ITAE relative to WO and GOA, which are 6.88% and 8%, respectively. The performance validation results demonstrate that the SFOA approach exhibits potential and effective performance. The proposed method on DC microgrid control has been successfully applied and shows promising performance. The proposed methodology is particularly suitable for renewable energy integration in isolated or resource-constrained regions.