£149.99

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23 days of data · current price £150

Elsevier Statistical Relational AI in Photovoltaic Power Uncertainty Analysis

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Description

Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis is a comprehensive guide to addressing uncertainty challenges in photovoltaic power generation systems. This Elsevier publication integrates theoretical frameworks with practical models and code examples to help engineers and researchers understand and apply advanced methods across multiple time scales. The book covers critical applications including photovoltaic power prediction, probabilistic power flow analysis, and stochastic planning, providing actionable solutions for managing the unpredictability inherent in solar energy systems. Whether you work in renewable energy development, grid management, or power systems research, this resource combines statistical methods with relational artificial intelligence techniques to improve decision-making and system reliability in photovoltaic installations.

Key Features

Addresses uncertainty analysis and modelling in photovoltaic power generation using StaRAI methodology at different time scales.

Includes practical models, cases, and code to support collaborative learning and real-world application of AI techniques.

Covers photovoltaic power prediction, probabilistic power flow, stochastic planning, and related uncertainty topics.

Published by Elsevier, a trusted academic publisher specialising in technical and scientific content for professionals.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
18 April 2025
Listed Since
17 August 2024

Barcode

No barcode data available

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