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An economic model predictive control framework for distributed embedded battery applications.

Number: pap. 3134

Author(s) : PATEL N. R., RAWLINGS J. B.

Summary

Since building heating, ventilation, and air conditioning (HVAC) systems are significant consumers of primary energy, considerable efforts are being made to improve energy efficiency and decrease energy costs in these applications. Notably, substantial opportunities in the area of HVAC control exist for decreasing energy costs by shifting loads from peak periods to off-peak periods in the presence of time-varying utility prices. Economic model predictive control (MPC) has been shown to significantly decrease the energy costs of commercial HVAC systems via load shifting. Typically, thermal energy storage (TES) is used for this purpose; however, with batteries becoming less expensive to manufacture, electrical energy storage in batteries is becoming a viable option for load shifting. In this work, largescale embedded battery applications are considered in which the batteries are directly packaged with airside equipment such as air handler units (AHUs), roof-top units (RTUs), and variable refrigerant flow systems (VRFs). In this paper, we propose a hierarchical control system framework for the economic optimization of distributed embedded battery units. The architecture considers both building mass storage as well as the electrical energy storage of the battery units. A high-level problem performs an economic optimization over the entire system using aggregate models. The low-level layer is broken into subsystems, each optimizing its local decisions with higher fidelity models. Advantages of this framework include: (i) no iterative communication required between subsystems, (ii) decreased computational complexity in the high-level problem allowing for real-time online implementation, and (iii) management of total demand across the entire system to reduce peak demand charges. We conclude with a simulation study demonstrating the benefits of the proposed control architecture.

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Pages: 10

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Details

  • Original title: An economic model predictive control framework for distributed embedded battery applications.
  • Record ID : 30024735
  • Languages: English
  • Subject: Environment
  • Source: 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
  • Publication date: 2018/07/09

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