
Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105479 - 105479
Published: May 1, 2025
Language: Английский
Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105479 - 105479
Published: May 1, 2025
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Feb. 18, 2025
The global shift towards decentralized energy systems, driven by the integration of distributed generation technologies and renewable sources, underscores critical need for effective management strategies in microgrids. This study proposes a novel multi-objective optimization framework grid-connected microgrids using quantum particle swarm (QPSO) to address dual challenges minimizing operational costs reducing environmental emissions. microgrid configuration analyzed includes sources like photovoltaic panels wind turbines, along with conventional battery storage. By incorporating quantum-inspired mechanics, QPSO overcomes limitations such as premature convergence solution stagnation, often seen traditional methods. Simulation results demonstrate that achieves 9.67% reduction costs, equating savings €158.87, 13.23% carbon emissions, lowering emissions 513.70 kg CO2 equivalent economic scheduling scenario. In environmentally constrained scenario, method delivers balanced €174.11 401.63 CO2. algorithm's performance is validated across various configurations, including standard low-voltage setups. These highlight QPSO's potential an efficient tool optimizing management, promoting both sustainability. provides robust achieving practical solutions real-world applications, emphasizing role advanced techniques sustainable systems.
Language: Английский
Citations
2Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104306 - 104306
Published: Feb. 1, 2025
Language: Английский
Citations
0Energy Informatics, Journal Year: 2025, Volume and Issue: 8(1)
Published: Feb. 27, 2025
Language: Английский
Citations
0Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 23, 2025
This paper investigates the economic energy management of a wireless electric vehicle charging stations (EVCS) connected to hybrid renewable system comprising photovoltaic (PV), wind, battery storage, and main grid. The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm optimize minimize operational costs under varying scenarios. Three distinct EV load profiles are considered evaluate performance proposed optimization technique. Simulation results demonstrate that IHHO achieves significant cost reductions improves utilization efficiency compared other state-of-the-art algorithms such as Quantum Particle Swarm (IQPSO), Honeybee Mating (HBMO), Enhanced Exploratory Whale Algorithm (EEWOA). For scenarios with energies, reduced electricity by up 36.41%, achieving per-unit low 3.17 INR for most demanding profile. Under generation disconnection, maintained its superiority, reducing 37.89% unoptimized dispatch strategies. integration storage further enhanced system's resilience cost-effectiveness, particularly during periods unavailability. algorithm's robust performance, reflected in ability handle dynamic challenging conditions, demonstrates potential practical deployment real-world EVCS powered systems. findings highlight reliable efficient tool optimizing dispatch, promoting energy, supporting sustainable infrastructure development. outperforms all benchmark algorithms, 35.82% Profile 3, minimum 3.11 INR/kWh across Specifically, achieved lowest 6479.72 INR/day 1, 10,893.23 2, 20,821.63 consistently outperforming IQPSO, HBMO, EEWOA.
Language: Английский
Citations
0Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104859 - 104859
Published: April 1, 2025
Language: Английский
Citations
0International Journal of Ambient Energy, Journal Year: 2025, Volume and Issue: 46(1)
Published: March 31, 2025
Language: Английский
Citations
0Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105176 - 105176
Published: May 1, 2025
Language: Английский
Citations
0Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105479 - 105479
Published: May 1, 2025
Language: Английский
Citations
0