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LAP Lambert Academic Publishing AI-Driven Optimization for Solar Energy Systems: AI-Driven Optimization for Solar Energy Systems: Nature-Inspired Algorithms for Solar Energy System

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£69.51 £64.01 £65.21 £66.41 £67.61 £68.81 £70.01 25 July 2026 08 August 2026 22 August 2026 05 September 2026 19 September 2026
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Description
The rising global demand for sustainable energy has accelerated solar PV adoption, yet efficiency is limited by challenges such as variable irradiance, partial shading, storage, and grid integration. This study explores 15 nature-inspired AI optimization algorithms-ABC, PSO, PIO, DIO, PDO, SMO, RIOA, ACO, TIOA, OIOA, EIO, CIO, OOA, PIOA, and MLO-that mimic biological behaviors to solve nonlinear, multi-objective problems in solar systems. Using theoretical models and case studies, the research shows how these methods improve MPPT, tilt/orientation, storage scheduling, microgrid dispatch, and reliability. Results highlight ABC, ACO, TIOA, CIO, RIOA, and OOA as top performers, achieving 98-99% MPPT efficiency, 6-9% annual yield gains, and major reductions in storage losses and diesel reliance. Lightweight approaches like PDO and simplified ABC excel in embedded MPPT, while CIO, OIOA, and EIO deliver high-accuracy offline tilt and layout optimization. Specialized roles include MLO for power quality and PIOA/OOA for resource scheduling. Collectively, these algorithms provide adaptive, scalable solutions that boost efficiency, cut costs, and enhance sustainability in solar energy.

Product Specifications
Brand
LAP Lambert Academic Publishing
Format
paperback
ASIN
6202452587
Category
Books > Subjects > Science, Nature & Maths > Engineering & Technology > Electronics & Communications Engineering > Electronics Engineering
Domain
Amazon UK
Release Date
09 October 2025
Listed Since
05 November 2025

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