scholarly journals HVAC Systems Applied in University Buildings with Control Based on PMV and aPMV Indexes

Inventions ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 3 ◽  
Author(s):  
Eusébio Conceição ◽  
António Sousa ◽  
João Gomes ◽  
António Ruano
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Hvac Systems ◽  
Hvac System ◽  
Predicted Mean Vote ◽  
Consumption Level ◽  
Comfort Levels ◽  
Winter Conditions ◽  
University Buildings ◽  
Hvac Control

In this work, HVAC (Heating, Ventilation and Air Conditioning) systems applied in university buildings with control based on PMV (Predicted Mean Vote) and aPMV (adaptive Predicted Mean Vote) indexes are discussed. The building’s thermal behavior with complex topology, in transient thermal conditions, for summer and winter conditions is simulated by software. The university building is divided into 124 spaces, on two levels with an area of 5931 m2, and is composed of 201 transparent surfaces and 1740 opaque surfaces. There are 86 compartments equipped with HVAC systems. The simulation considers the actual occupation and ventilation cycles, the external environmental variables, the internal HVAC system and the occupants’ and building’s characteristics. In this work, a new HVAC control system, designed to simultaneously obtain better occupants’ thermal comfort levels according to category C of ISO 7730 with less energy consumption, is presented. This new HVAC system with aPMV index control is numerically implemented, and its performance is compared with the performance of the same HVAC system with the usual PMV index control. Both HVAC control systems turn on only when the PMV index or the aPMV index reaches values below −0.7, in winter conditions, and when the PMV index or the aPMV index reaches values above +0.7, in summer conditions. In accordance with the results obtained, the HVAC system guarantees negative PMV and aPMV indexes in winter conditions and positive PMV and aPMV indexes in summer conditions. The energy consumption level is higher in winter conditions than in summer conditions for compartments with shading, and it is lower in winter conditions than in summer conditions for compartments exposed to direct solar radiation. The consumption level is higher using the PMV control than with the aPMV control. Air temperature, in accordance with Portuguese standards, is higher than 20 °C in winter conditions and lower than 27 °C in summer conditions. In Mediterranean climates, the HVAC systems with aPMV control provide better occupants’ thermal comfort levels and less energy consumption than the HVAC system with PMV control.

scholarly journals Modeling and Experimental Investigation of Thermal Comfort and Energy Consumption in a Battery Electric Bus

2021 ◽  
Vol 12 (1) ◽  
pp. 7
Author(s):  
Francesco Cigarini ◽  
Tu-Anh Fay ◽  
Nikolay Artemenko ◽  
Dietmar Göhlich
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Air Conditioning ◽  
Hvac Systems ◽  
State Of Charge ◽  
Hvac System ◽  
Data Logger ◽  
Winter Conditions ◽  
Electric Bus ◽  
Thermal Comfort Model

In battery electric buses (e-buses), the substantial energy consumption of the heating, ventilation, and air conditioning (HVAC) system can cause significant reductions of the available travel range. Additionally, HVAC systems are often operated at higher levels than what required for the thermal comfort of the passengers. Therefore, this paper proposes a method to experimentally investigate the influence of the HVAC system on the energy consumption and thermal comfort in a 12m e-bus. An appropriate thermal comfort model is identified and the required climatic input parameters are selected and measured with self-developed sensor stations. The energy consumption of the e-bus, the state of charge (SoC) of the battery and the available travel range are measured by an embedded data logger. Climatic measurements are then performed with heating on and off on a Berlin bus line in winter conditions. The results show that the energy consumption of the e-bus is increased by a factor of 1.9 with heating on, while both the SoC and travel range are reduced accordingly. Comparing the thermal comfort with heating on and off, a decrease from “comfortable” to “slightly uncomfortable but acceptable” is observed.

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

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2078
Author(s):  
Akinkunmi Adegbenro ◽  
Michael Short ◽  
Claudio Angione
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Demand Response ◽  
Demand Management ◽  
Integrated Approach ◽  
Adaptive Controller ◽  
Hvac Systems ◽  
Control Mechanisms ◽  
Tracking Controller ◽  
Hvac Control

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.

scholarly journals Thermal Comfort Study Based on PMV-PPD in the Building of a Screening Center for COVID-19

2021 ◽  
Author(s):  
Danial Mohammadi ◽  
Simin Nasrabadi
Keyword(s):  
Thermal Stress ◽  
Energy Consumption ◽  
Thermal Comfort ◽  
Air Conditioning ◽  
Thermal Condition ◽  
R Software ◽  
Air Conditioning System ◽  
Thermal Index ◽  
Predicted Mean Vote ◽  
Hot Climate

Background: One way to achieve a standard heating, ventilating, and air conditioning system with maximum satisfaction is to use a thermal index to identify and determine the thermal comfort of people. In this study we intend to evaluate thermal comfort based on PMV-PPD (Predicted Mean Vote/Predicted Percentage Dissatisfied) model in workers of screening center for COVID-19. Methods: The study period was from March 1 to October 31, 2020. In this study, we used the ISO 7730 model to determinate PMV-PPD index. PMV index was used to determine thermal comfort at different scales in Birjand city with arid and hot climate. All data were analyzed using R software (version 3.3.0) and IBM SPSS statistics softwares. Results: The maximum and minimum recorded physical PMV values in the study period were observed in June as (2.09 ± 0.03) and March as (-1.27 ± 0.14), respectively. The amplitude of the thermal sense in the study period was varied between slightly cool (-1.5) and warm (+2.5). The PPD in spring was 40% which indicated slightly warm to hot condition. Conclusions: The October was the only month during the study in which thermal stress was in comfort or neutral thermal condition.  Our results suggest that thermal comfort has dimensions and indices which are helpful in managing energy consumption.

scholarly journals Effect of Different HVAC Control Strategies on Thermal Comfort and Adaptive Behavior in High-Rise Apartments

2021 ◽  
Vol 13 (21) ◽  
pp. 11767
Author(s):  
Jihye Ryu ◽  
Jungsoo Kim
Keyword(s):  
Thermal Comfort ◽  
Adaptive Behavior ◽  
Control Strategies ◽  
Control Measures ◽  
Hvac System ◽  
Comfort Zone ◽  
Residential Sector ◽  
High Rise ◽  
Hvac Control ◽  
The Impact

In the residential sector, householders play an active role in regulating the indoor climate via diverse control measures such as the operation of air-conditioners or windows. The main research question asked in this paper is whether control decisions made by householders are rational and effective in terms of achieving comfort and energy efficiency. Based on a field study in South Korea, this paper explores how a HVAC control strategy for high-rise apartment buildings can affect occupant comfort and adaptive behavior. Two different control strategies: (1) occupant control (OC), where occupants were allowed to freely operate the HVAC system and (2) comfort-zone control (CC), where the operation of the HVAC system was determined by the researcher, based on a pre-defined comfort zone, were applied to, and tested within the participating households in summer. The impact of the two control strategies on indoor thermal environments, thermal comfort, and occupant adaptive behavior were analyzed. We find that the CC strategy is more energy/comfort efficient than OC because: (1) comfort was be achieved at a higher indoor temperature, and (2) unnecessary control behaviors leading to cooling load increase can be minimized, which have major implications for energy consumption reduction in the residential sector.

Intelligent Approaches for Modeling and Optimizing HVAC Systems’ Energy Use

2017 ◽  
Author(s):  
Raymond C. Tesiero ◽  
Nabil Nassif ◽  
Balakrishna Gokaraju ◽  
Daniel Adrian Doss
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Hvac Systems ◽  
Optimization Process ◽  
Hvac System ◽  
Building Automation ◽  
Set Point ◽  
Chilled Water ◽  
Self Tuning ◽  
Self Learning

Advanced energy management control systems (EMCS), or building automation systems (BAS), offer an excellent means of reducing energy consumption in heating, ventilating, and air conditioning (HVAC) systems while maintaining and improving indoor environmental conditions. This can be achieved through the use of computational intelligence and optimization. This paper evaluates model-based optimization processes (OP) for HVAC systems utilizing any computer algebra system (CAS), genetic algorithms and self-learning or self-tuning models (STM), which minimizes the error between measured and predicted performance data. The OP can be integrated into the EMCS to perform several intelligent functions achieving optimal system performance. The development of several self-learning HVAC models and optimizing the process (minimizing energy use) is tested using data collected from an actual HVAC system. Using this optimization process (OP), the optimal variable set points (OVSP), such as supply air temperature (Ts), supply duct static pressure (Ps), chilled water supply temperature (Tw), minimum outdoor ventilation, and chilled water differential pressure set-point (Dpw) are optimized with respect to energy use of the HVAC’s cooling side including the chiller, pump, and fan. The optimized set point variables minimize energy use and maintain thermal comfort incorporating ASHRAE’s new ventilation standard 62.1-2013. This research focuses primarily with: on-line, self-tuning, optimization process (OLSTOP); HVAC design principles; and control strategies within a building automation system (BAS) controller. The HVAC controller will achieve the lowest energy consumption of the cooling side while maintaining occupant comfort by performing and prioritizing the appropriate actions. The program’s algorithms analyze multiple variables (humidity, pressure, temperature, CO2, etc.) simultaneously at key locations throughout the HVAC system (pumps, cooling coil, chiller, fan, etc.) to reach the function’s objective, which is the lowest energy consumption while maintaining occupancy comfort.

Requirements of Air-Conditioning Systems’ Developments in Hospitals and Critical Healthcare Facilities

Volume 3 ◽  
2004 ◽  
Author(s):  
Essam E. Khalil ◽  
Ramiz Kameel
Keyword(s):  
Energy Consumption ◽  
Air Quality ◽  
Thermal Comfort ◽  
Air Conditioning ◽  
Hvac Systems ◽  
Comfort Level ◽  
Current Status ◽  
Healthcare Applications ◽  
Healthcare Facilities ◽  
Intelligent Technique

The balance between thermal comfort and air quality in healthcare facilities to optimize the Indoor Air Quality (IAQ) is the main aim of this paper. The present paper will present this balance from the viewpoint of the air conditioning design. It was found that the design of the HVAC airside systems plays an important role for achieving the optimum air quality beside the optimum comfort level. This paper highlights the importance of the proper airside design on the IAQ. The present paper introduces some recommendations for airside designs to facilitate the development of optimum HVAC systems. This paper also stresses on the factors that improve the thermal comfort and air quality for the already existed systems (for maintenance procedure). To design an optimum HVAC airside system that provides comfort and air quality in the air-conditioned spaces with efficient energy consumption is a great challenge. The present paper defines the current status, future requirements, and expectations. Based on this analysis and the vast progress of computers and associated software, the artificial intelligent technique will be a competitor candidate to the experimental and numerical techniques. Finally, the researches that relate between the different designs of the HVAC systems and energy consumption should concern with the optimization of airside design as the expected target to enhance the indoor environment. The present paper reviews the results of recent advances that are concerned with the HVAC design engineering in the healthcare applications. The following requirements are necessary for Health and hygiene considerations: • Air movements are to be restricted in and between the various hospital departments (no cross movement). • Appropriate ventilation and filtration is used to dilute and reduce contamination in the form of odour, air-borne micro organisms, viruses, hazardous chemical and radioactive substances. • Temperature and relative humidity are to be regulated and attained for various medical areas. • Environmental compliance conditions should be maintained, accurately controlled and monitored.

scholarly journals Determining the Modelling Input Parameters for Heating, Ventilation, and Air Conditioning Systems in New Zealand Commercial Buildings

2021 ◽  
Author(s):  
◽  
Anthony Gates
Keyword(s):  
Energy Consumption ◽  
New Zealand ◽  
Air Conditioning ◽  
Energy Performance ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Hvac System ◽  
Input Parameters ◽  
Parameter Values ◽  
The Ideal

<p>Template energy calculation models that have been produced by the Building Energy End-use Study (BEES) team are used to quickly and reliably model commercial buildings and calculate their energy performance. The template models contain standardised equipment, lighting, and occupancy loads; cooling and heating requirements are calculated using an ideal loads air system. Using seven buildings, Cory et al. 2011a have demonstrated that the template models have the potential to closely match the monthly energy performance of detailed (individually purpose built) models and the real buildings. Three of these models were within the ±5% acceptable tolerance to be considered calibrated. The four template models that were not within the acceptable tolerance have been identified to have complex Heating, Ventilation, and Air Conditioning (HVAC) systems that the ideal loads air systems could not replicate. Because HVAC systems consume one of the largest proportions of energy in commercial buildings, this has a significant impact on the reliability of the template models. To address this issue, a set of detailed HVAC systems were needed to replace the ideal loads air systems. Due to HVAC system parameters not being collected by the BEES team and the lack of published modelling input parameters available, it is unknown what values are reasonable to use in the models. This study used a Delphi survey to collect real building information of the commonly installed HVAC systems in New Zealand commercial buildings. The survey formed a consensus between HVAC engineers that determined what the most commonly installed systems are and their associated performance values. The outcome of the survey was a documented set of system types and modelling input parameters that are representative of New Zealand HVAC systems. The responses of the survey were used to produce a set of HVAC system templates that replace the ideal loads air systems. The HVAC template models updated the software default parameter values with values that are representative of commonly installed systems in New Zealand. The importance of the updated input values was illustrated through a comparison of the calculated monthly energy consumption. The resulting difference in energy consumption using the updated parameter values is typically <5% monthly; at worst it is 75% for Variable Air Volume (VAV) system in the Wellington climate during June.</p>

scholarly journals Modeling and control design of residential HVAC systems for operating cost reduction

2021 ◽  
Author(s):  
Abdul Afram
Keyword(s):  
Complex System ◽  
Energy Consumption ◽  
Operating Cost ◽  
Control Design ◽  
Cost Savings ◽  
Hvac Systems ◽  
Conservation Strategies ◽  
Hvac System ◽  
Modeling And Control ◽  
Supervisory Controller

The residential HVAC systems in Canada can consume more than 60% of the total energy in a house which results in higher operating costs and environmental pollution. The HVAC is a complex system with variable loads acting on it due to the changes in weather and occupancy. The energy consumption of the HVAC systems can be reduced by adapting to the ever changing loads and implementation of energy conservation strategies along with the appropriate control design. Most of the existing HVAC systems use simple on/off controllers and lack any supervisory controller to reduce the energy consumption and operating cost of the system. In Ontario, due to the variable price of electricity, there is an opportunity to design intelligent control system which can shift the loads to off-peak hours and reduce the operating cost of the HVAC system. In order to take advantage of this opportunity, a supervisory controller based on model predictive control (MPC) was designed in this research. The residential HVAC system models were developed and accurately calibrated with the data measured from the Toronto and Region Conservation Authority’s Archetype Sustainable House, House B (TRCA-ASHB) located in Vaughan, Ontario, Canada. Since HVAC is a large and complex system, it was divided into its major subsystems called energy recovery ventilator (ERV), air handling unit (AHU), radiant floor heating (RFH) system, ground source heat pump (GSHP) and buffer tank (BT). The models of each of the subsystem were developed and calibrated individually. The models were then combined together to develop the model of the whole residential HVAC system. The developed model is able to predict the temperature, flow rate, energy consumption and cost for each individual subsystem and whole HVAC system. The model was used to simulate the performance of the existing HVAC system with on/off controllers and develop the supervisory MPC. The supervisory controller was implemented on the HVAC system of TRCA-ASHB and at least 16% cost savings were verified.

Indoor Thermal Comfort and its Effect on Building Energy Consumption

2011 ◽  
Vol 71-78 ◽  
pp. 3516-3519 ◽  
Author(s):  
Xue Bin Yang ◽  
De Fa Sun ◽  
Xiang Jiang Zhou ◽  
Ling Ling Cai ◽  
Ying Ji
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Savings ◽  
Thermal Sensation ◽  
Building Energy ◽  
Building Energy Consumption ◽  
Predicted Mean Vote ◽  
Indoor Thermal Comfort ◽  
Air Speed ◽  
Comfort Parameters

The indoor thermal comfort and its effect on building energy consumption have been conducted by literature reviewing in the study. The linear relationship and the related formulations of various thermal comfort indictors are summarized to evaluate the human comfort. These parameters include predicted mean vote, thermal sensation vote, adaptive predicted mean vote, thermal comfort vote, and thermal acceptability. Under different climatic or regional conditions, both relationships between thermal comfort parameters and indoor or outdoor air temperature, and between comfort vote and another comfort parameter, are summarized for their definition and formulation. The comfort parameters such as local air speed, neutral temperature, PMV set point and others will directly impact the building energy usage. It is of significance to seek an optimal alternative for energy savings.

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