A novel distributed economic model predictive control approach for building air-conditioning systems in microgrids
type: Item
instance of: scholarly article
title: A novel distributed economic model predictive control approach for building air-conditioning systems in microgrids
zbMATH Open document ID: 1390.93116
author: Ruigang Wang
author: Jie Bao
author: Xinan Zhang
published in: Mathematics
publication date: 2018-07-05T00:00:00Z
review text: Summary: With the penetration of grid-connected renewable energy generation, microgrids are facing stability and power quality problems caused by renewable intermittency. To alleviate such problems, Demand Side Management (DSM) of responsive loads, such as Building Air-Conditioning System (BACS), has been proposed and studied. In recent years, numerous control approaches have been published for proper management of single BACS. The majority of these approaches focus on either the control of BACS for attenuating power fluctuations in the grid or the operating cost minimization on behalf of the residents. These two control objectives are paramount for BACS control in microgrids and can be conflicting. As such, they should be considered together in control design. As individual buildings may have different owners/residents, it is natural to control different BACSs in an autonomous and self-interested manner to minimize the operational costs for the owners/residents. Unfortunately, such ``selfish'' operation can result in abrupt and large power fluctuations at the Point of Common Coupling (PCC) of the microgrid due to lack of coordination. Consequently, the original objective of mitigating power fluctuations generated by renewable intermittency cannot be achieved. To minimize the operating costs of individual BACSs and simultaneously ensure desirable overall power flow at PCC, this paper proposes a novel distributed control framework based on the dissipativity theory. The proposed method achieves the objective of renewable intermittency mitigation through proper coordination of distributed BACS controllers and is scalable and computationally efficient. Simulation studies are carried out to illustrate the efficacy of the proposed control framework.
Mathematics Subject Classification ID: 93A15
Mathematics Subject Classification ID: 93A14
Mathematics Subject Classification ID: 93B40
zbMATH DE Number: 6898752
zbMATH Keywords: model predictive control (MPC)
zbMATH Keywords: dissipativity
zbMATH Keywords: building air-conditioning system (BACS)
zbMATH Keywords: microgrids
describes a project that uses: SeDuMi
describes a project that uses: YALMIP
MaRDI profile type: Publication
full work available at URL: math6040060
OpenAlex ID: W2800966811
cites work: Q3112649
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DOI: 10.3390/MATH6040060
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description: scientific article; zbMATH DE number 6898752