Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 24, 2024
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 17, 2025
In this paper, a comprehensive energy management framework for microgrids that incorporates price-based demand response programs (DRPs) and leverages an advanced optimization method-Greedy Rat Swarm Optimizer (GRSO) is proposed. The primary objective to minimize the generation cost environmental impact of microgrid systems by effectively scheduling distributed resources (DERs), including renewable sources (RES) such as solar wind, alongside fossil-fuel-based generators. Four distinct models-exponential, hyperbolic, logarithmic, critical peak pricing (CPP)-are developed, each reflecting different price elasticity demand. These models are integrated with flexible matrix assess dynamic consumer fluctuating electricity prices. study evaluates four operational scenarios, focusing on grid participation, DER utilization, real-time (RTP), time use (TOU), strategies. Quantitative results demonstrate significant cost-saving potential integrating DRPs operations. optimal scenario, GRSO achieved minimum 882¥ base load profile. Further, when (CPP) was applied, reduced 746¥, representing 15.4% reduction. For scenario where grid's participation limited, logarithmic-based model decreased 817¥, while full interaction led higher reductions. Additionally, our show reduction in load, factor improvements up 87.7% across studied profiles. Furthermore, limiting upstream power capacity 30 kW resulted 7% increase all cases, confirming importance reducing costs. algorithm outperformed traditional metaheuristics terms both execution convergence, making it viable solution optimization. conclusion, proposed GRSO-based provides efficient approach minimization, achieving costs notable benefits emissions. This highlights strategies sustainable cost-effective management.
Language: Английский
Citations
5
Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103671 - 103671
Published: Dec. 1, 2024
Language: Английский
Citations
12
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
1
Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 21, 2025
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 30, 2025
Microgrid systems have evolved based on renewable energies including wind, solar, and hydrogen to make the satisfaction of loads far from main grid more flexible controllable using both island- grid-connected modes. Albeit microgrids can gain beneficial results in cost energy schedules once operating mode, such are vulnerable malicious attacks viewpoint cybersecurity. With this mind, paper explores a novel advanced attack model named false transferred data injection (FTDI) aiming manipulatively alter power flowing microgrid upstream raise voltage usability probability. One crucial piece information that uses change system cause greatest amount damage while concealing attacker's view is stability index. Saying transaction between within broad scope bilateral exchange at any given moment noteworthy. Put otherwise, with respect FTDI assault, microgrid's direction just as significant detection value. Therefore, running detector needs concurrently detect changes value power. To overcome problem, presents learning generative network model, adversarial (GAN) paradigm, recognize probability values maliciously aimed. end, studied wind turbine, photovoltaic, storage, tidal fuel cell units performed tested 24-bus IEEE satisfy local load demands. Comparative analysis indicates notable gains, scores 0.95%, 0.92%, 0.7%, 10% for Hit rate, C.R. F.A. Miss rate order evaluate GAN-based microgrid.
Language: Английский
Citations
0
iScience, Journal Year: 2025, Volume and Issue: 28(3), P. 112121 - 112121
Published: Feb. 27, 2025
Language: Английский
Citations
0
Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 24, 2024
Language: Английский
Citations
0