Co-design of control algorithm and embedded platform for building HVAC systems

Maasoumy, Mehdi; Zhu, Qi; Li, Cheng; Meggers, Forrest; Sangiovanni-Vincentelli, A.

doi:10.1145/2502524.2502533

Cited by 30 publications

(22 citation statements)

References 15 publications

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“…For energyefficient HVAC control, a set of system models and algorithms is proposed in [27], [28], [29], [30], [31], [32], [33]. In [27], a non-linear model of the overall cooling system is proposed, and an MPC scheme for minimizing energy consumption is developed.…”

Section: Related Workmentioning

confidence: 99%

“…In [30], a building thermal behavior is modeled as RC networks and validated against historical data, and a tracking linear-quadratic regulator (LQR) is proposed for HVAC control. The work in [32] uses the similar building model as in [30], and proposes a set of HVAC control algorithms that address the sensing data inaccuracy using unscented or extended Kalman filters. In addition to scheduling energy loads, there are also approaches proposed for scheduling heterogeneous energy sources such as battery storage at individual customer level [34], [35], [36], [37], [38].…”

Section: Related Workmentioning

confidence: 99%

“…We use a building thermal dynamics model similarly as in [30], [41], where a building is considered as a network. The building can be modeled by using two types of nodes: walls and rooms.…”

Section: Building Thermal Dynamics Modelmentioning

confidence: 99%

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Proactive Demand Participation of Smart Buildings in Smart Grid

Wei

Zhu

2016

IEEE Trans. Comput.

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Abstract-Buildings account for nearly 40 percent of the total energy consumption in the United States. As a critical step toward smart cities, it is essential to intelligently manage and coordinate the building operations to improve the efficiency and reliability of overall energy system. With the advent of smart meters and two-way communication systems, various energy consumptions from smart buildings can now be coordinated across the smart grid together with other energy loads and power plants. In this paper, we propose a comprehensive framework to integrate the operations of smart buildings into the energy scheduling of bulk power system through proactive building demand participation. This new scheme enables buildings to proactively express and communicate their energy consumption preferences to smart grid operators rather than passively receive and react to market signals and instructions such as time varying electricity prices. The proposed scheme is implemented in a simulation environment. The experiment results show that the proactive demand response scheme can achieve up to 10 percent system generation cost reduction and 20 percent building operation cost reduction compared with passive demand response scheme. The results also demonstrate that the system cost savings increase significantly with more flexible load installed and higher percentage of proactive customers participation level in the power network.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Proactive Demand Participation of Smart Buildings in Smart Grid

Wei

Zhu

2016

IEEE Trans. Comput.

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“…Another study was completed relating to building control temperature sensor data from the BubbleZERO to quantify the impact of sensor calibration in a model-predictive controls environment. The study focused on the co-design of an intelligent control algorithm within an embedded platform to optimize an HVAC system with respect to energy cost and monetary cost while satisfying the constraints for user comfort level [32]. It has served as showroom, demonstrating LowEx systems to a large variety of visitors from Singapore and abroad, challenging and enriching the discussion about novel solutions and building design.…”

Section: The Bubblezero As Integrated System Laboratorymentioning

confidence: 99%

BubbleZERO—Design, Construction and Operation of a Transportable Research Laboratory for Low Exergy Building System Evaluation in the Tropics

et al. 2013

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Abstract:We present the design, construction and operation of a novel building systems laboratory, the BubbleZERO-Zero Emission Research Operation. Our objective was to design a space to evaluate the performance of Swiss-developed low exergy building systems in the tropical climate of Singapore using an integrated design approach. The method we employed for evaluation in the tropics was to design and build a test bed out of the shipping containers that transported the prototype low exergy systems from Switzerland to Singapore. This approach resulted in a novel laboratory environment containing radiant cooling panels and decentralized air supply, along with a self-shading, inflated "bubble" skin, experimental low emissivity (LowE) glazing, LED lighting, wireless sensors and distributed control. The laboratory evaluates and demonstrates for OPEN ACCESSEnergies 2013, 6 4552 the first time in Singapore an integrated high-temperature cooling system with separate demand-controlled ventilation adapted for the tropics. It is a functional lab testing system in real tropical conditions. As such, the results showing the ability to mitigate the risk of condensation by maintaining a dew point below 18 °C by the separate decentralized ventilation are significant and necessary for potential future implementation in buildings. In addition, the control system provides new proof of concept for distributed wireless sensors and control for reliable automation of the systems. These key results are presented along with the integrated design process and real-life tropical operation of the laboratory.

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“…In [6], a building thermal behavior is modeled as RC networks and validated against historical data, and a tracking linear-quadratic regulator (LQR) is proposed for HVAC control. The work in [8] uses the similar building model as in [6], and proposes a set of HVAC control algorithms that address the sensing data inaccuracy using unscented or extended Kalman filters. There are also approaches proposed for optimizing EV charging [10]- [12] to reduce the peak demand and total energy cost, with utilization of renewable energy sources including solar and wind.…”

Section: Introductionmentioning

confidence: 99%

Co-scheduling of HVAC control, EV charging and battery usage for building energy efficiency

Wei¹,

Zhu²,

Maasoumy³

2014

2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

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Building stock consumes 40% of primary energy consumption in the United States. Among various types of energy loads in buildings, HVAC (heating, ventilation, and air conditioning) and EV (electric vehicle) charging are two of the most important ones and have distinct characteristics. HVAC system accounts for 50% of the building energy consumption and typically operates throughout the day, while EV charging is an emerging major energy load that is hard to predict and may cause spikes in energy demand. To maximize building energy efficiency and grid stability, it is important to address both types of energy loads in a holistic framework. Furthermore, on the supply side, the utilization of multiple energy sources such as grid electricity, solar, wind, and battery storage provides more opportunities for energy efficiency, and should be considered together with the scheduling of energy loads. In this paper, we present a novel model predictive control (MPC) based algorithm to co-schedule HVAC control, EV scheduling and battery usage for reducing the total building energy consumption and the peak energy demand, while maintaining the temperature within the comfort zone for building occupants and meeting the deadlines for EV charging. Experiment results demonstrate the effectiveness of our approach under a variety of demand, supply and environment constraints.

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Co-design of control algorithm and embedded platform for building HVAC systems

Cited by 30 publications

References 15 publications

Proactive Demand Participation of Smart Buildings in Smart Grid

Proactive Demand Participation of Smart Buildings in Smart Grid

BubbleZERO—Design, Construction and Operation of a Transportable Research Laboratory for Low Exergy Building System Evaluation in the Tropics

Co-scheduling of HVAC control, EV charging and battery usage for building energy efficiency

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