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Proceedings of eSim 2016: 9th Conference of IBPSA-Canada

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Intelligent control of hybrid cooling for telecommunication base stations

Jiaqiang Wang, Quan Zhang, Yuebin Yu

Abstract: Telecommunication base stations consume significant amount of energy for heating and cooling the space. This study explores the application of model predictive control (MPC) technology to hybrid cooling systems with ventilation and air-conditioning cooling in TBSs and demonstrates the potential performance of MPC. Discrete particle swarm optimization (DPSO) algorithm is adopted as the optimizer to handle the nonlinearity. Simulations are performed for a typical week during a cooling season. The results show that the MPC controller has better performance over conventional control methods, with a maximum reduction of 50% in terms of daily cooling power requirement, while increasing the control accuracy in terms of the maximum deviation from the desired temperature range. The study also quantifies the impact of model uncertainty on the MPC with different coefficient of performance on the internal model.
Pages: 397 - 404
Paper:
esim2016_56-187