Control strategy for dynamic operation of multiple chillers under random load constraints

Xuefeng Liu, Bin Huang and Yulan Zheng

Energy, 2023, vol. 270, issue C

Abstract: Under the influence of building load stochasticity and thermal inertia of central air conditioning system, the lag of control strategy makes it difficult for the cooling source system to meet the cooling demand of users in real time, which affects the operational energy efficiency ratio of the cooling source system. In this regard, this paper proposes a chiller dynamic optimization method based on Markov chain model predictive control algorithm, which studies the optimization of parallel operation characteristics of multiple chillers on the basis of correcting the occurrence of small probability events and avoiding frequent chiller starts and stops, reveals the prediction law of hourly load distribution of the future air conditioning system, explores the balance point between the prediction time of building load and the calculation time of chiller control strategy, provides a theoretical basis and reference for determining the time limit of the optimal calculation and the output of the optimal control strategy. The study provides a theoretical basis and reference for determining the time limit of the optimal calculation and the output of the optimal control strategy. It is found that the optimal control strategy not only has good optimization effect, but also the confidence is significantly increased by 56.7%.

Keywords: Load randomness; Operation optimization; Markov chain; Chillers; Energy conservation (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:270:y:2023:i:c:s0360544223003262

DOI: 10.1016/j.energy.2023.126932

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