{ "item_title" : "EnergyBidSim", "item_author" : [" Pooja Jain", "Ankush Tandon "], "item_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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/6/20/844/755/6208447550_b.jpg", "price_data" : { "retail_price" : "106.00", "online_price" : "106.00", "our_price" : "106.00", "club_price" : "106.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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