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

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Pubblicato in:PLoS One vol. 20, no. 6 (Jun 2025), p. e0325310
Autore principale: Wei, Liming
Altri autori: Zhang, Fengyang
Pubblicazione:
Public Library of Science
Soggetti:
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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Abstract: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
Fonte:Health & Medical Collection