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Research on Optimal Control Algorithm of Ice Thermal-Storage Air-Conditioning System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 890 ))

Abstract

The constraint-based nonlinear multivariate function optimization algorithm was used to optimize the distribution of cooling load between chillers and ice-storage tanks. The goal is to minimize the cooling load and system running costs of the air-conditioning system. Based on the peak-valley price principle of the power grid system, the most economical running of the ice-storage air-conditioning system is achieved. The results show that compared with the traditional ice-storage air-conditioning system control algorithm, the proposed method can reduce the power consumption of the system by 10.32% and reduce the system operating cost by 12.07% under the premise of satisfying the demand for terminal cooling capacity.

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Acknowledgements

This work is supported by the National Key Research and Development Project of China with the grant number: 2017YFC0704100 (entitled New Generation Intelligent Building Platform Techniques) and Xi’an Beilin District Science and Technology Plan Project with the grant number: GX1603 (entitled An Energy-Saving Optimized Operation Strategy for an Ice Storage Air Conditioning System in Xi’an, China).

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Correspondence to Junqi Yu .

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Yu, J., Yang, X., Zhao, A., Zhou, M., Ren, Y. (2019). Research on Optimal Control Algorithm of Ice Thermal-Storage Air-Conditioning System. In: Fang, Q., Zhu, Q., Qiao, F. (eds) Advancements in Smart City and Intelligent Building. ICSCIB 2018. Advances in Intelligent Systems and Computing, vol 890 . Springer, Singapore. https://doi.org/10.1007/978-981-13-6733-5_19

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  • DOI: https://doi.org/10.1007/978-981-13-6733-5_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6732-8

  • Online ISBN: 978-981-13-6733-5

  • eBook Packages: EngineeringEngineering (R0)

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