🧠 MATLAB Genetic Algorithm for Hybrid Energy System Optimization

This repository provides a MATLAB-based simulation and optimization tool that uses a Genetic Algorithm (GA) to determine the optimal configuration of a hybrid energy system. The system includes solar panels, wind turbines, batteries, and diesel generators, designed to meet dynamic hourly energy demand while minimizing the Levelized Cost of Energy (LCOE).

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🚀 Features

• Optimization Algorithm:

  • Custom-built Genetic Algorithm for multi-component energy systems.
  • Includes selection, crossover, and mutation operators.
  • Convergence criteria based on LCOE error threshold and generation count.

• Energy System Modeling:

  • Supports solar PV, wind turbines, diesel generators, and battery banks.
  • Realistic power output calculations based on weather data.
  • SOC (State of Charge) tracking for battery modeling.

• Smart Resource Allocation:

  • Adapts to constraints like available installation area.
  • Uses probabilistic mutation and selection for diverse solution exploration.

• Interactive Progress Visualization:

  • Dynamic progress bar with estimated time remaining.
  • Generates post-optimization plots and pie charts summarizing energy contributions.

• Modular Structure:

  • Key logic separated into functions:
    • algoritmoGenetico.m: Main optimization controller.
    • planta_new.m: Energy calculation and simulation.
    • reproduccion.m: GA crossover logic.
    • mutacion.m: GA mutation logic.
    • specialTurbine.m: Wind turbine performance modeling.
    • cargaExcel.m: Input parameter loading.