scholarly journals An Event-Triggered Model Predictive Control for Energy Efficiency and Thermal Comfort Optimization in Buildings

2021 ◽  
Vol 2069 (1) ◽  
pp. 012173
Author(s):  
Yang Shiyu ◽  
Chen Wanyu ◽  
Wan Man Pun
Keyword(s):  
Model Predictive Control ◽  
Thermal Comfort ◽  
Predictive Control ◽  
Energy Savings ◽  
Energy Performance ◽  
Control Technique ◽  
Computation Efficiency ◽  
The Cost ◽  
Computation Load ◽  
Event Triggered

Abstract Model predictive control (MPC) is a promising optimal control technique for building automation. However, the high computation load to solve the optimization problem of MPC is challenging its implementation for real-time building control. Typical MPC systems employ the time-triggered mechanism (TTM), which conducts the optimization periodically at each control interval regardless of the necessity. This study proposes an event-triggered mechanism (ETM) for MPC, which conducts the optimization only when there is a triggering event that necessitates it. Contrasting to the conventional ETM that bases only on the current information, the proposed ETM bases on the cost function considering the past, current and future information. An event-triggered model predictive control (ETMPC) system is developed using the proposed ETM. In a simulation environment, the ETMPC system is implemented to control an air-conditioning system. The ETMPC is compared to a MPC employing TTM and a conventional thermostat. The ETMPC improved the computation efficiency by 77.6% - 88.2% as compared to the MPC while achieving similar energy performance as the MPC does (both achieved more than 9% energy savings over the thermostat). The ETMPC only degraded the thermal comfort performance slightly as compared to the MPC but is still much better than the thermostat.

scholarly journals Controlling Switchable Electrochromic Glazing for Energy Savings, Visual Comfort and Thermal Comfort: A Model Predictive Control

CivilEng ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 1019-1053
Author(s):  
Abolfazl Ganji Kheybari ◽  
Tim Steiner ◽  
Steven Liu ◽  
Sabine Hoffmann
Keyword(s):  
Model Predictive Control ◽  
Thermal Comfort ◽  
Predictive Control ◽  
Energy Savings ◽  
Control Strategies ◽  
Temperate Climate ◽  
Base Case ◽  
North East ◽  
Simulation Based ◽  
The Impact

Dynamic façades play an important role in enhancing the overall performance of buildings: they respond to the environmental conditions and adjust the amount of transmitted solar radiation. This paper proposes a simulation-based framework to evaluate the energy and comfort performance of different control strategies for switchable electrochromic glazing (EC). The presented method shows the impact of a model predictive control (MPC) on energy savings and on visual and thermal comfort for different orientations compared to other strategies. Besides manual operation and conventional rule-based controls, the benchmark in this study was a simulation-based control (multi-objective penalty-based control) with optimal performance. The hourly results of various control cases were analyzed based on the established performance indicators and criteria. The cumulative annual results show the capabilities and limitations of each control strategy for an EC glazing. For a temperate climate (Mannheim, Germany), results showed that an MPC for EC glazing provides visual and thermal comfort while saving energy of up to 14%, 37%, 37%, and 34% respectively for facing north, east, south, and west relative to the base-case.

Wide-area Power System Oscillation Damping using Model Predictive Control Technique

2011 ◽  
Vol 131 (7) ◽  
pp. 536-541 ◽  
Author(s):  
Tarek Hassan Mohamed ◽  
Abdel-Moamen Mohammed Abdel-Rahim ◽  
Ahmed Abd-Eltawwab Hassan ◽  
Takashi Hiyama
Keyword(s):  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Wide Area ◽  
Control Technique ◽  
Oscillation Damping

scholarly journals Passive Model Predictive Control on a Two-Body Self-Referenced Point Absorber Wave Energy Converter

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1731
Author(s):  
Dan Montoya ◽  
Elisabetta Tedeschi ◽  
Luca Castellini ◽  
Tiago Martins
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Power Flow ◽  
Linear Constraints ◽  
Wave Energy Converter ◽  
Control Technique ◽  
Computational Time ◽  
Energy Converter ◽  
Point Absorber

Wave energy is nowadays one of the most promising renewable energy sources; however, wave energy technology has not reached the fully-commercial stage, yet. One key aspect to achieve this goal is to identify an effective control strategy for each selected Wave Energy Converter (WEC), in order to extract the maximum energy from the waves, while respecting the physical constraints of the device. Model Predictive Control (MPC) can inherently satisfy these requirements. Generally, MPC is formulated as a quadratic programming problem with linear constraints (e.g., on position, speed and Power Take-Off (PTO) force). Since, in the most general case, this control technique requires bidirectional power flow between the PTO system and the grid, it has similar characteristics as reactive control. This means that, under some operating conditions, the energy losses may be equivalent, or even larger, than the energy yielded. As many WECs are designed to only allow unidirectional power flow, it is necessary to set nonlinear constraints. This makes the optimization problem significantly more expensive in terms of computational time. This work proposes two MPC control strategies applied to a two-body point absorber that address this issue from two different perspectives: (a) adapting the MPC formulation to passive loading strategy; and (b) adapting linear constraints in the MPC in order to only allow an unidirectional power flow. The results show that the two alternative proposals have similar performance in terms of computational time compared to the regular MPC and obtain considerably more power than the linear passive control, thus proving to be a good option for unidirectional PTO systems.

scholarly journals A New Model Predictive Control Method for Eliminating Hydraulic Oscillation and Dynamic Hydraulic Imbalance in a Complex Chilled Water System

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3608
Author(s):  
Yang Yuan ◽  
Neng Zhu ◽  
Haizhu Zhou ◽  
Hai Wang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Water System ◽  
Energy Performance ◽  
Effective Control ◽  
New Model ◽  
Chilled Water ◽  
Chilled Water System ◽  
Hydraulic Oscillation

To enhance the energy performance of a central air-conditioning system, an effective control method for the chilled water system is always essential. However, it is a real challenge to distribute exact cooling energy to multiple terminal units in different floors via a complex chilled water network. To mitigate hydraulic imbalance in a complex chilled water system, many throttle valves and variable-speed pumps are installed, which are usually regulated by PID-based controllers. Due to the severe hydraulic coupling among the valves and pumps, the hydraulic oscillation phenomena often occur while using those feedback-based controllers. Based on a data-calibrated water distribution model which can accurately predict the hydraulic behaviors of a chilled water system, a new Model Predictive Control (MPC) method is proposed in this study. The proposed method is validated by a real-life chilled water system in a 22-floor hotel. By the proposed method, the valves and pumps can be regulated safely without any hydraulic oscillations. Simultaneously, the hydraulic imbalance among different floors is also eliminated, which can save 23.3% electricity consumption of the pumps.

Event-triggered model predictive control of positive systems with random actuator saturation

2021 ◽  
Author(s):  
Junfeng Zhang ◽  
Suhuan Zhang ◽  
Peng Lin
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Actuator Saturation ◽  
Domain Of Attraction ◽  
Programming Approach ◽  
Interval Estimate ◽  
Positive Systems ◽  
Predictive Algorithm ◽  
Controller Gain ◽  
Event Triggered

Abstract This paper investigates the event-triggered model predictive control of positive systems with actuator saturation. Interval and polytopic uncertainties are imposed on the systems, respectively. First, a new model with actuator saturation obeying Bernoulli distribution is established, which is more general and powerful for describing the saturation phenomenon than the saturation in a certain way. Then, a linear event-triggering condition is constructed based on the state and error signal. An interval estimate approach is presented to reach the positivity and stability of the systems. The saturation part in the controller is technically transformed into a non-saturation part. Thus, a linear programming approach is proposed to compute the event-triggered controller gain and the corresponding domain of attraction gain. A predictive algorithm is introduced for the computation of the event-triggered controller parameters. Finally, an example is provided to illustrate the validity of the design.

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