Research on optimal scheduling of integrated energy system based on improved multi-objective artificial hummingbird algorithm

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Dades bibliogràfiques
Publicat a:	PLoS One vol. 20, no. 6 (Jun 2025), p. e0325310
Autor principal:	Wei, Liming
Altres autors:	Zhang, Fengyang
Publicat:	Public Library of Science
Matèries:	Energy management Carbon emissions Algorithms Emissions trading Sustainable energy Energy efficiency Clean energy Multiple objective analysis Objectives Industrial plants Energy utilization Pareto optimum Energy consumption Carbon sequestration Efficiency Simplex method Environmental objective Economics Industrial parks Monte Carlo simulation Emissions Carbon Industrial areas Cooling Sustainable development Costs Genetic algorithms Integrated energy systems Renewable resources Optimization Alternative energy sources Demand side management Optimization algorithms Power dispatch Parks & recreation areas Economic
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Resum:	To accelerate energy efficiency improvement and green transition in industrial parks while addressing energy utilization and carbon reduction requirements, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) based on an enhanced multi-objective artificial hummingbird algorithm (MOAHA). The main contributions are threefold: First, we establish an optimized dispatch model incorporating combined cooling, heating and power (CCHP) systems, a refined two-stage power-to-gas (P2G) conversion process, and carbon capture technologies. Second, a stepwise carbon trading mechanism is introduced to further reduce carbon emissions from the IES. Third, a multi-strategy enhanced MOAHA is developed through three key improvements: 1) Logistic-sine fused chaotic mapping for population initialization to enhance distribution uniformity and solution quality; 2) Elite opposition-based learning and adaptive spiral migration foraging mechanisms to optimize individual positions and population diversity; 3) Simplex method integration to strengthen local search capabilities and optimization precision. Comprehensive case studies demonstrate the model’s effectiveness, achieving an 82.9% reduction in carbon emissions and 17.3% decrease in operational costs compared to conventional approaches. The proposed framework provides a technically viable solution for sustainable energy management in industrial parks, effectively balancing economic and environmental objectives.
ISSN:	1932-6203
DOI:	10.1371/journal.pone.0325310
Font:	Health & Medical Collection