Enhanced maximum power point tracking using hybrid GA and PSO algorithms for solar PV systems

• Hybrid MPPT Techniques Introduced : Four novel hybrid algorithms (GA + PO, GA + IC, PSO + PO, and PSO + IC) are developed by integrating Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) with conventional Perturb & Observe (PO) and Incremental Conductance (IC) methods. • Adaptive Step Size Optimization : The hybrid methods dynamically adjust the step size based on weather variations, significantly improving tracking speed and reducing power oscillations under changing irradiance and temperature conditions. • Superior Tracking Performance : Simulations in MATLAB/SIMULINK show that the hybrid techniques outperform traditional MPPT methods in terms of power efficiency, tracking accuracy, and response time. • High Efficiency and Fast Response : GA + IC achieved an impressive tracking efficiency of 98.8 %, while GA + PO reached 98.7 %, with both methods demonstrating fast settling times of 10.3 ms under standard test conditions. • Practical Relevance for Renewable Systems : The proposed hybrid algorithms enhance the robustness and effectiveness of solar PV systems in real-world environments, making them suitable for high-efficiency energy harvesting under fluctuating weather conditions. In uncertain weather, a proficient maximum power point tracking (MPPT) approach is essential for maximizing PV output power. Conventional methods like incremental conductance (IC) and perturb & observe (PO), find it challenging to slow response and steady-state oscillations in changing weather. To overcome these restrictions, this paper introduces four novel hybrid MPPT algorithms, fusing the genetic algorithm (GA) and particle swarm optimization (PSO) with standard PO and IC methods in a single comparative study. The key innovation lies in an adaptive step-size scheme driven by metaheuristic tuning, which reduces steady-state oscillations while preserving fast tracking mechanism The proposed methods—GA + PO, GA + IC, PSO + PO, and PSO + IC—validated in MATLAB/Simulink under varying irradiance and temperature. Evaluating both GA and PSO paired with both PO and IC in a single comparative framework that is not common in the literature; this is the main novelty of the work. The focus was on efficiency, settling time, and tracking time. Results showed hybrid methods outperformed traditional methods. Under standard test conditions (1000 W/m², 25 °C), GA + PO achieved an efficiency of 98.7 %, while GA + IC reached 98.8 % and settling time of 10.3 ms. The hybrid approaches consistently maintained improved tracking accuracy and declined steady-state fluctuations across temperature ranges of 22–38 °C and irradiance ranges of 750–1000 W/m². Future work will target hardware-in-the-loop (HIL) validation and real time microcontroller implementation for real world deployment.