Energies

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23 pages, 3136 KiB

Open AccessArticle

Temperature Control to Improve Performance of Hempcrete-Phase Change Material Wall Assemblies in a Cold Climate

by Miroslava Kavgic and Yaser Abdellatef

Energies 2021, 14(17), 5343; https://doi.org/10.3390/en14175343 - 27 Aug 2021

Cited by 5 | Viewed by 2447

Phase change material (PCM)-enhanced building envelopes can control indoor temperatures and save energy. However, PCM needs to undergo a phase change transition from solid to liquid and back to be fully effective. Furthermore, most previous research integrated PCM with high embodied energy materials. [...] Read more.

Phase change material (PCM)-enhanced building envelopes can control indoor temperatures and save energy. However, PCM needs to undergo a phase change transition from solid to liquid and back to be fully effective. Furthermore, most previous research integrated PCM with high embodied energy materials. This study aims to advance the existing research on integrating PCM into carbon-negative wall assemblies composed of hempcrete and applying temperature control strategies to improve wall systems’ performance while considering the hysteresis phenomenon. Four hempcrete and hempcrete-PCM (HPCM) wall design configurations were simulated and compared under different control strategies designed to reduce energy demand while enhancing the phase change transition of the microencapsulated PCM. The HPCM wall types outperformed the hempcrete wall assembly through heating (~3–7%) and cooling (~7.8–20.7%) energy savings. HPCM walls also maintained higher wall surface temperatures during the coldest days, lower during the warmest days, and within a tighter range than hempcrete assembly, thus improving the thermal comfort. However, the results also show that the optimal performance of thermal energy storage materials requires temperature controls that facilitate their charge and discharge. Hence, applied control strategies reduced heating and cooling energy demand in the range of ~4.4–21.5% and ~14.5–55%, respectively. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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20 pages, 2028 KiB

Open AccessArticle

Development of Advanced Smart Ventilation Controls for Residential Applications

by Iain Walker, Brennan Less, David Lorenzetti and Michael D. Sohn

Energies 2021, 14(17), 5257; https://doi.org/10.3390/en14175257 - 25 Aug 2021

Cited by 3 | Viewed by 2502

Abstract

This study examined the use of zoned ventilation systems using a coupled CONTAM/EnergyPlus model for new California dwellings. Several smart control strategies were developed with a target of halving ventilation-related energy use, largely through reducing dwelling ventilation rates based on zone occupancy. The [...] Read more.

This study examined the use of zoned ventilation systems using a coupled CONTAM/EnergyPlus model for new California dwellings. Several smart control strategies were developed with a target of halving ventilation-related energy use, largely through reducing dwelling ventilation rates based on zone occupancy. The controls were evaluated based on the annual energy consumption relative to continuously operating non-zoned, code-compliant mechanical ventilation systems. The systems were also evaluated from an indoor air quality perspective using the equivalency approach, where the annual personal concentration of a contaminant for a control strategy is compared to the personal concentration that would have occurred using a continuously operating, non-zoned system. Individual occupant personal concentrations were calculated for the following contaminants of concern: moisture, CO₂, particles, and a generic contaminant. Zonal controls that saved energy by reducing outside airflow achieved typical reductions in ventilation-related energy of 10% to 30%, compared to the 7% savings from the unzoned control. However, this was at the expense of increased personal concentrations for some contaminants in most cases. In addition, care is required in the design and evaluation of zonal controls, because control strategies may reduce exposure to some contaminants, while increasing exposure to others. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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14 pages, 4315 KiB

Open AccessArticle

A Study on the Energy Reduction Measures of Data Centers through Chilled Water Temperature Control and Water-Side Economizer

by Yu-Jin Kim, Ju-Wan Ha, Kyung-Soon Park and Young-Hak Song

Energies 2021, 14(12), 3575; https://doi.org/10.3390/en14123575 - 16 Jun 2021

Cited by 1 | Viewed by 2351

Abstract

The degree of integration of IT devices and consumption of cooling energy are consistently increasing owing to developments in the data center industry. Hence, to ensure the smooth operation and fault prevention of IT devices, the energy consumption of cooling systems has increased, [...] Read more.

The degree of integration of IT devices and consumption of cooling energy are consistently increasing owing to developments in the data center industry. Hence, to ensure the smooth operation and fault prevention of IT devices, the energy consumption of cooling systems has increased, leading to active research on improvements in cooling system performance for reducing energy consumption. This study examines the reduction in cooling energy consumption using a simulation by applying chilled water control and a water-side economizer (WSE) system to enhance the cooling system efficiency. The simulation results showed that the energy consumption was reduced by 1.8% when the chilled water temperature was set to 11 °C in a conventional system and by up to 19.6% when WSE was also applied. Furthermore, when the changes in chilled water temperature were applied for efficient operation of WSE, the energy consumption was reduced by up to 30.1% compared to that in conventional energy systems. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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19 pages, 19548 KiB

Open AccessArticle

Multi-Objective Optimization of HVAC Operation for Balancing Energy Use and Occupant Comfort in Educational Buildings

by Alessandro Franco, Carlo Bartoli, Paolo Conti, Lorenzo Miserocchi and Daniele Testi

Energies 2021, 14(10), 2847; https://doi.org/10.3390/en14102847 - 14 May 2021

Cited by 12 | Viewed by 2838

Abstract

The paper provides a methodology for the optimal control of heating, ventilation, and air conditioning (HVAC) systems used in public buildings, with the purpose of obtaining high comfort and safety standards along with energy efficiency. The combination of the two concurrent objectives of [...] Read more.

The paper provides a methodology for the optimal control of heating, ventilation, and air conditioning (HVAC) systems used in public buildings, with the purpose of obtaining high comfort and safety standards along with energy efficiency. The combination of the two concurrent objectives of minimizing energy use and guaranteeing high standards of occupant comfort is obtained by means of multi-objective optimization, in which a comfort model is combined along with a dynamic energy model of the building. The use of dynamic setpoints for the HVAC and the inclusion of comfort indicators represent a step forward, compared to the current design and operation procedures suggested by technical standards. The utilization of the proposed methodology is tested with reference to a case study, represented by an academic building used by the University of Pisa for educational purposes, whose extensive and variable occupancy can help to emphasize the importance of comfort in the operation of HVAC systems in different climatic conditions and with different occupancy profiles. We show how this optimization brings interesting results in terms of energy-saving (up to 30%), obtaining an increased comfort level (of more than 25%) compared to the operating conditions suggested by technical standards. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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18 pages, 4260 KiB

Open AccessArticle

An Integrated Approach to Adaptive Control and Supervisory Optimisation of HVAC Control Systems for Demand Response Applications

by Akinkunmi Adegbenro, Michael Short and Claudio Angione

Energies 2021, 14(8), 2078; https://doi.org/10.3390/en14082078 - 8 Apr 2021

Cited by 10 | Viewed by 3540

Abstract

Heating, ventilating, and air-conditioning (HVAC) systems account for a large percentage of energy consumption in buildings. Implementation of efficient optimisation and control mechanisms has been identified as one crucial way to help reduce and shift HVAC systems’ energy consumption to both save economic [...] Read more.

Heating, ventilating, and air-conditioning (HVAC) systems account for a large percentage of energy consumption in buildings. Implementation of efficient optimisation and control mechanisms has been identified as one crucial way to help reduce and shift HVAC systems’ energy consumption to both save economic costs and foster improved integration with renewables. This has led to the development of various control techniques, some of which have produced promising results. However, very few of these control mechanisms have fully considered important factors such as electricity time of use (TOU) price information, occupant thermal comfort, computational complexity, and nonlinear HVAC dynamics to design a demand response schema. In this paper, a novel two-stage integrated approach for such is proposed and evaluated. A model predictive control (MPC)-based optimiser for supervisory setpoint control is integrated with a digital parameter-adaptive controller for use in a demand response/demand management environment. The optimiser is designed to shift the heating load (and hence electrical load) to off-peak periods by minimising a trade-off between thermal comfort and electricity costs, generating a setpoint trajectory for the inner loop HVAC tracking controller. The tracking controller provides HVAC model information to the outer loop for calibration purposes. By way of calibrated simulations, it was found that significant energy saving and cost reduction could be achieved in comparison to a traditional on/off or variable HVAC control system with a fixed setpoint temperature. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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22 pages, 12234 KiB

Open AccessArticle

Model Predictive Control with Adaptive Building Model for Heating Using the Hybrid Air-Conditioning System in a Railway Station

by Ruixin Lv, Zhongyuan Yuan, Bo Lei, Jiacheng Zheng and Xiujing Luo

Energies 2021, 14(7), 1996; https://doi.org/10.3390/en14071996 - 5 Apr 2021

Cited by 17 | Viewed by 3609

Abstract

A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of [...] Read more.

A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of the railway station on Tibetan Plateau. The MPC controller applies an off-line method of updating the building model to improve the accuracy of predicting indoor conditions. The control performance of the adaptive MPC is compared with the proportional-integral-derivative (PID) control, as well as an MPC without adaptive model through simulation constructed based on a TRNSYS-MATLAB co-simulation testbed. The results show that the implementation of the adaptive MPC can improve indoor thermal comfort and reduce 22.2% energy consumption compared to the PID control. Compared to the MPC without adaptive model, the adaptive MPC achieves fewer violations of constraints and reduces energy consumption by 11.5% through periodic model updating. This study focuses on the design of a control system to maintain indoor thermal comfort and improve system efficiency. The proposed method could also be applied in other public buildings. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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17 pages, 4361 KiB

Open AccessArticle

Development of an Optimal Start Control Strategy for a Variable Refrigerant Flow (VRF) System

by Yusung Lee and Woohyun Kim

Energies 2021, 14(2), 271; https://doi.org/10.3390/en14020271 - 6 Jan 2021

Cited by 11 | Viewed by 2221

Abstract

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used [...] Read more.

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used to determine the length of time required to bring each zone from its current temperature to the set point. The existing data are used to evaluate and validated the predictive performance of three data-based models. Experiments are conducted using three outdoor units and eight indoor units on site. The experimental test is performed to validate the performance of proposed optimal control by comparing between conventional and optimal control methods. Then, the ability to save energy wasted for maintaining temperature after temperature reaches the set points is evaluated through the comparison of energy usage. Given these results, 30.5% of energy is saved on average for each outdoor unit and the proposed optimal control strategy makes the zones comfortable. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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15 pages, 2561 KiB

Open AccessArticle

Integrated Unfold-PCA Monitoring Application for Smart Buildings: An AHU Application Example

by Llorenç Burgas, Joan Colomer, Joaquim Melendez, Francisco Ignacio Gamero and Sergio Herraiz

Energies 2021, 14(1), 235; https://doi.org/10.3390/en14010235 - 5 Jan 2021

Cited by 8 | Viewed by 2564

Abstract

This paper presents a complete methodology, together with its implementation as a web application, for monitoring smart buildings. The approach uses unfold-Principal Component Analysis (unfold-PCA) as a batch projection method and two statistics, Hotelling’s T-squared (T²) and the squared prediction [...] Read more.

This paper presents a complete methodology, together with its implementation as a web application, for monitoring smart buildings. The approach uses unfold-Principal Component Analysis (unfold-PCA) as a batch projection method and two statistics, Hotelling’s T-squared (T²) and the squared prediction error (SPE), for alarm generation resulting in two simple control charts independently on the number of variables involved. The method consists of modelling the normal operating conditions of a building (entire building, room or subsystem) with latent variables described expressing the principal components. Thus, the method allows detecting faults and misbehaviour as a deviation of previously mentioned statistics from their statistical thresholds. Once a fault or misbehaviour is detected, the isolation of sensors that mostly contribute to such detection is proposed as a first step for diagnosis. The methodology has been implemented under a SaaS (software as a service) approach to be offered to multiple buildings as an on-line application for facility managers. The application is general enough to be used for monitoring complete buildings, or parts of them, using on-line data. A complete example of use for monitoring the performance of the air handling unit of a lecture theatre is presented as demonstrative example and results are discussed Full article

(This article belongs to the Special Issue Advanced Control Strategies for Buildings and HVAC Systems)

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