EnergyBidSim: AI-Powered Price Forecasting for Day-Ahead Markets

Name: EnergyBidSim: AI-Powered Price Forecasting for Day-Ahead Markets
Brand: LAP LAMBERT Academic Publishing
Availability: OutOfStock
Rating: 5 (1 reviews)

By Pooja Jain

0 - Default Title

Description

This book presents advanced meta-heuristic algorithms and a Multi-Agent System (MAS) for intelligent bidding in the restructured day-ahead energy market. Enhanced versions of Moth Flame Optimizer (OB-MFO), Firefly Algorithm (RFA), and a hybrid WOA-SCA are proposed using opposition-based learning and adaptive techniques, showing superior performance on benchmark tests. These algorithms are applied to market bidding scenarios under uncertainty, evaluated using metrics like price volatility and market power. A layered MAS framework is also introduced, enabling dynamic decision-making with incomplete data. Results on test systems, including IEEE-14 bus, show improved accuracy and efficiency over traditional methods.

Product details

Binding:: Paperback
Number of Pages:: 268
Release Date:: 2025-10-09
Publication Date:: 2025-10-09
Publisher:: LAP LAMBERT Academic Publishing
Languages:: Original: English
ISBN10:: 6208447550
ISBN13:: 9786208447557
GPSR Manufacturer Reference:: [email protected]
Weight:: 417 g
Height:: 150 cm
Width:: 220 cm
Thickness:: 17 cm

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