Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Aug 2026, 05:33:22am America, Santiago
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Daily Overview |
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72F: Energy & Water Location: Room 09: Luz | |
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11:36am - 11:48am
Hybrid RBF Neural Network and Multi-Level Genetic Algorithm for MPPT Optimization in Photovoltaic Systems with IHGM-SEPIC Converter: Experimental Validation Universidad de Pamplona - (CO), Colombia Abstract– This paper presents a hybrid Maximum Power Point Tracking (MPPT) system that combines Radial Basis Function (RBF) neural networks with a multi-level Genetic Algorithm (GA) for photovoltaic (PV) system optimization. The proposed approach is implemented on embedded hardware (ESP32-S3 and Raspberry Pi 5) coupled with an Interleaved High-Gain Modified SEPIC (IHGM-SEPIC) converter, achieving a measured efficiency of 98.87%. A complete mathematical model of the IHGM-SEPIC topology is derived, comprising 16 state equations. The GA simultaneously optimizes converter parameters, MPPT control parameters, and RBF network weights using BLX-α crossover, adaptive mutation, and tournament selection with a multi-objective fitness function. Experimental validation was conducted using a 100W monocrystalline panel under real Andean highland conditions (Pamplona, Colombia, 2340 (m.a.s.l.) over a dataset of 5,629 records. Results demonstrate 4.67% improvement over conventional P&O and 7.37% over commercial controllers in tracking efficiency, with a response time of 0.8 seconds versus 3.5 seconds for P&O. Statistical validation from N=30 GA executions confirms convergence reliability with σ = 0.35%. | |