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Planning parameters for energy storage equipment.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Planning_parameters_for_energy_storage_equipment_/29914100
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With the escalating global energy demand and the pressing need for clean energy, innovations in building energy systems are crucial. This paper proposes a Multi - load Balancing Control Strategy (MLBS) based on the Improved Tuna Swarm Optimization (ITSO) algorithm. By integrating battery and compressed air energy storage, the strategy enhances the building energy system’s flexible dispatch capability.A building complex in Huai’an, Jiangsu is used as a case study. Two cases are compared: one without MLBS and the other with MLBS using a low - carbon economic dispatch model. Results show that MLBS effectively adjusts electric and thermal loads. After applying MLBS and the low - carbon economic dispatch strategy, the quarterly planning cost drops to 110.37 million, the operating cost to 204.28 tons, the carbon trading cost to 8.15 million, and the total carbon emission to 137.27 million, significantly lower than the values without the strategy. Moreover, the TSO - MLBS energy scheduling strategy adopted in this paper has the shortest computation time and lower energy scheduling cost, offering a double improvement in economic efficiency and carbon emission reduction.
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2025-08-14
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