Multi frequency stability optimization of integrated energy systems considering virtual energy storage characteristics of heating networks

Wang, Yongli; Dong, Huanran; Ma, Kaiwei; Wang, Hui; Zhang, Jihui

doi:10.1016/j.applthermaleng.2024.124254

Applied Thermal Engineering

2024

DOI: 10.1016/j.applthermaleng.2024.124254

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Multi frequency stability optimization of integrated energy systems considering virtual energy storage characteristics of heating networks

Yongli Wang,

Huanran Dong,

Kaiwei Ma

et al.

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Cited by 2 publications

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Energy Storage Optimization in Renewable Energy Systems using Particle Swarm Optimization

Nidziy,

Bobba,

Seshapp

et al. 2024

E3S Web Conf.

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This research examines the application of Particle Swarm Optimization (PSO) to optimize energy storage optimizations with the objectives of improving energy generation, cost-efficiency, system dependability, and environmental sustainability. The optimisation of solar panel and energy storage capacities was conducted using empirical data from various microgrid locations: Site 1, which had a capacity of 90 kW solar and 40 kW wind, Site 2, which had a capacity of 50 kW wind and 80 kW solar, Site 3, which had a capacity of 60 kW wind and 110 kW solar, and Site 4, which had a capacity of 45 kW wind and 85 kW solar. The findings suggest that energy generation increased significantly by 15% to 25% across all sites following optimization. Furthermore, significant decreases in the levelized cost of energy (LCOE) between 10% and 14% were noted, providing confirmation of the economic feasibility. Increased grid stability of 17% to 24% during periods when microgrids were operating under stable conditions demonstrates that PSO-optimized configurations are dependable. The positive environmental effects of solutions derived from PSO were apparent, as evidenced by the conservation of carbon emissions and ecological footprints, which decreased by 7% to 15%. The sensitivity analysis validated the optimized configurations' robustness, establishing their ability to withstand changes in parameters. In summary, the utilization of PSO to optimize energy storage optimizations showcases its capacity to enhance the efficiency, dependability, cost-effectiveness, and environmental impact of these systems. This advances the possibility of constructing microgrids that exclusively utilize sustainable renewable energy sources.

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Energy Storage Optimization in Renewable Energy Systems using Particle Swarm Optimization

Nidziy,

Bobba,

Seshapp

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

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Optimizing Energy Distribution and Utilization in Multi-Building Complexes Using Effective Thermal Storage Systems and Renewable Energy Sharing

Vafaeva,

Soujanya,

Singh

et al. 2024

E3S Web Conf.

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An increase in renewable energy sources and a subsequent need for more energy-efficient construction practices have prompted efforts to optimize energy distribution networks. Various building types, including residential, hotel, and hospital structures, may benefit from solar-based integrated energy systems (SIES) that include energy-sharing mechanisms and Effective Thermal Storage Systems (ETSS). This new approach is presented in the present research. In this paper a new optimization model is proposed that consider the correlation of energy storage system with fluctuating load demands of the building (BL). This theology makes it possible for any building with high energy demand in the day to trade excess power with another building which has low demand during the same time. From the simulation we get that grid power consumption is reduced from homes by 15%, hotels by 12% and hospitals by 18% through use of energy-sharing and Energy Transfer System (ETSS). Efficient energy redistribution management also helps increase the consumption of renewable resources by 20%. The proposed method led to a cumulative increase in the overall efficiency by 12% compared to the control strategy by optimizing the energy supply and demand in various sorts of buildings. Comparing our method with the previous work clearly shows that using the proposed approach yields better energy saving and higher usage of renewable energy sources because the method takes into consideration building plan and load profile. These results serve as a foundation for integrated energy systems of a smart city solution that incorporates ETSS and energy sharing.

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Multi frequency stability optimization of integrated energy systems considering virtual energy storage characteristics of heating networks

Cited by 2 publications

References 35 publications

Energy Storage Optimization in Renewable Energy Systems using Particle Swarm Optimization

Energy Storage Optimization in Renewable Energy Systems using Particle Swarm Optimization

Optimizing Energy Distribution and Utilization in Multi-Building Complexes Using Effective Thermal Storage Systems and Renewable Energy Sharing

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