Scientific Reports 15, Article number: 24339 (2025) Cite this article Integrating solar and wind energy with battery storage systems into microgrids is gaining prominence in both remote areas and high-rise urban buildings.
The efficiency of charging and discharging is 95% , and = 10 years = 3650 days. Furthermore, the = 1 YUAN/kWh, = 0.5 YUAN/kWh and = 0.4 YUAN/kWh. Based on these conditions, we have devised a configuration for coordinating and optimizing the microgrid wind and energy storage systems.
It is recommended that energy storage be integrated in order to optimize the allocation of wind energy. Figure 1 illustrates the operational status of the microgrid, including instances of interconnection with the main grid, the installed capacity of wind power in each microgrid, and the maximum load parameters.
In Microgrid 1, wind turbines dominate the investment portfolio with an allocation of approximately 130,000 $, followed by solar installations at 55,000 $, and energy storage at 110,000 $. This indicates a wind-centric strategy, likely due to favorable wind conditions or spatial availability.
Therefore, through new energy structure optimization and complementary methods, it is possible to fully utilize the advantages of the geographical environment and improve the energy
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This study focuses on the optimization of wind-solar storage capacity allocation in intelligent microgrid systems using the Particle Swarm Optimization (PSO) algorithm. The
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Considering the capacity configuration of wind, solar and energy storage in a microgrid group containing N sub-microgrids, in order to take into account, the economic benefits of microgrid
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Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and
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Finally, the hybrid decreasing strategy is adopted in the process of vigilance position update. The ISSA can improve the search efficiency of the algorithm, avoid premature convergence
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To address the collaborative optimization challenge in multi-microgrid systems with significant renewable energy integration, this study presents a dual-layer optimization model
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In the context of vigorously advocating the transformation of electric energy production to green and low emission, it is very important to rationally allocate the wind-solar storage capacity of micro-grid.
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Consequently, we will proceed to investigate the optimized allocation of coordinated wind, solar, and storage resources in the integrated microgrid configuration.
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Integrating solar and wind energy with battery storage systems into microgrids is gaining prominence in both remote areas and high-rise urban buildings.
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Abstract. Due to the uncertain and randomness of both wind power photovoltaic output of power generation side and charging load of user side, a set of wind-solar-storage-charging multi-energy
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