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 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 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 A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 530 ◽  
Author(s):  
Jing Zhao ◽  
Yu Shan
Keyword(s):  
Energy Consumption ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Air Conditioning ◽  
Control Strategies ◽  
Hvac Systems ◽  
Hvac System ◽  
Pump System ◽  
Heat Pump System ◽  
Load Forecast

The energy consumption of air-conditioning systems is a major part of energy consumption in buildings. Optimal control strategies have been increasingly developed in building heating, ventilation, and air-conditioning (HVAC) systems. In this paper, a load forecast fuzzy (LFF) control strategy was proposed. The predictive load based on the SVM method was used as the input parameter of the fuzzy controller to perform feedforward fuzzy control on the HVAC system. This control method was considered as an effective way to reduce energy consumption while ensuring indoor comfort, which can solve the problem of hysteresis and inaccuracy in building HVAC systems by controlling the HVAC system in advance. The case study was conducted on a ground source heat pump system in Tianjin University to validate the proposed control strategy. In addition, the advantages of the LFF control strategy were verified by comparing with two feedback control strategies, which are the supply water temperature (SWT) control strategy and the room temperature fuzzy (RTF) control strategy. Results show that the proposed LFF control strategy is capable not only to ensure the minimum indoor temperature fluctuations but also decrease the total energy consumption.

scholarly journals A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 400 ◽  
Author(s):  
Zelin Nie ◽  
Feng Gao ◽  
Chao-Bo Yan
Keyword(s):  
Optimization Model ◽  
Air Conditioning ◽  
State Of The Art ◽  
Hvac Systems ◽  
Practical Significance ◽  
Hvac System ◽  
Bilinear Model ◽  
Optimization And Control ◽  
And Control ◽  
Slow Timescale

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.

scholarly journals Building energy consumption prediction and energy control of large-scale shopping malls based on a noncentralized self-adaptive energy management control system

2020 ◽  
pp. 014459872092073
Author(s):  
Bao Peng ◽  
Hui-Min Zou ◽  
Peng-Fei Bai ◽  
Yu-Yang Feng
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Air Conditioning ◽  
Large Scale ◽  
Commercial Buildings ◽  
Shopping Malls ◽  
Consumption Values ◽  
Central Air Conditioning ◽  
Energy Consumption Prediction ◽  
Consumption Prediction

Central air conditioning is the main energy-consuming equipment in modern large-scale commercial buildings. Its energy consumption generally accounts for more than 60% of the electricity load of an entire building, and there is a rising trend. Focusing on reducing central air conditioning energy consumption is a first priority to achieve energy savings in modern large-scale commercial buildings. To study the main influencing factors of central air conditioning energy consumption in large shopping malls, in-depth collection and analysis of energy consumption data of Shenzhen Tian-hong shopping mall were considered, and the impact of factors such as the basic composition of central air conditioning, time, and Shenzhen weather on the energy consumption of shopping malls was considered. The most representative Buji Rainbow store of the Rainbow Group is used as the research object. The influencing factors of central air conditioning on its energy consumption are divided into air conditioning pumps, host 1–1, host 1–2, host 2–1, and host 2–2. The power consumption of the freezer and the eight impact indicators of time and weather in Shenzhen were constructed using Pearson correlation coefficients and a long short-term memory neural network method to construct a regression model of the energy consumption prediction of the mall building. The average relative deviation between the predicted energy consumption values and the measured energy consumption values is less than 10%, which indicates that the main influencing factors selected in this paper can better explain the energy consumption of the mall, and the obtained energy consumption prediction model has high accuracy.

scholarly journals An exploration of the feasibility of converting the New Zealand commercial building stock to be Net Zero Energy

2021 ◽  
Author(s):  
◽  
Shaan Cory
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
New Zealand ◽  
Commercial Buildings ◽  
Commercial Building ◽  
Zero Energy ◽  
Building Stock ◽  
Energy Models ◽  
Net Zero Energy ◽  
Net Zero

This thesis explores the feasibility of converting the current New Zealand commercial building stock to Net Zero Energy (NZE). The analysis presented is grounded in real building performance and construction information. The goal was to establish results that are as realistic as possible to actual building performance. The Net Zero Energy Building (Net ZEB) concept is one of many low energy building movements that respond to the issues of climate change and energy security. The Net ZEB concept strives to reduce demand for energy and then to offset any residual energy consumption with non-CO2 emitting renewable energy technologies. The (re-)design focus for Net ZEBs is to reduce annual energy consumption to be equal to or less than any generated renewable energy. This is an important concept since approximately 40 percent of all energy and emissions worldwide are building related. If all buildings were designed and operated to be NZE, the existing energy can be used by other sectors which will increase energy security. Conversely, reducing the fossil fuel CO2 producing component of the energy consumed by buildings has the benefit of negating building’s contribution to climate change. The Net ZEB concept assumes each building is grid-connected, and balances the energy taken from the grid against the energy put back into the grid over a year. This study exploits the available synergies of the grid connection to achieve NZE for the whole building stock. Thus each individual building does not need to be NZE at the site, but they act as a community to reach NZE collectively. Furthermore, any grid-tied renewable energy does not need to be offset, only the non-renewable portion. A NZE target was calculated to determine the percentage reduction in current energy consumption needed before the current commercial building stock could be considered NZE. It was found that a 45 percent reduction in primary energy would offset all non-renewable CO2 emitting energy supply currently consumed by the New Zealand commercial building stock. Previous studies assessing whether converting an entire stock of commercial buildings to NZE is possible used prototypical building energy models. Prototypical models represent a hypothetical average building and have many assumptions about the way a building is operated. This thesis develops a method that takes a representative sample of real commercial buildings and makes calibrated energy models that can be aggregated to represent energy consumption for all commercial buildings in New Zealand. The developed calibration method makes use of as-built building information and a standardised procedure for identifying the inaccurate model inputs which need to be corrected for a building energy model to be calibrated. To further base the process in reality, a set of Energy Conservation Measures (ECM) that had been implemented in real Net ZEBs worldwide was adopted for the proposed retrofits. These ECMs were combined into Net ZEB solution sets for retrofitting the aggregated commercial building models. Optimisation of the Net ZEB solution sets was performed on hundreds of models to maximise energy savings. It took over six months for all of the optimisations to be completed. This thesis demonstrates the estimated New Zealand commercial building stock’s energy consumption based upon the calibrated energy models was robust by comparing it to an external estimate. It shows that NZE can be achieved by applying well understood Net ZEB solution sets to the New Zealand commercial building stock. 96 percent of the NZE goal is attainable just through demand reduction without the use of onsite renewable energy generation. The additional four percent of reduction required to meet NZE is easily attainable with onsite renewable generation. Another benefit is that the retrofitted commercial buildings will provide improved thermal comfort for the occupants. Having established NZE was possible, this thesis concludes with an analysis of the broader implications of achieving the NZE goal. It identifies the next step would be to design a NZE commercial building stock that reduces the stresses on the existing energy infrastructure. The Solution Set adopted was not developed with the interaction of the building and electrical grid in mind. To have a practical implementation of NZE will require costing and community prioritisation. This would be the next phase of work assessing nationwide NZE retrofit.

scholarly journals Energy Efficient Air Curtains for Industrial Gates in Cold Climates

2021 ◽  
Vol 246 ◽  
pp. 08005
Author(s):  
A.S. Strongin ◽  
A.M. Zhivov
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Air Conditioning ◽  
Thermal Power ◽  
Hvac Systems ◽  
Energy Resources ◽  
Cold Climates ◽  
Construction Costs ◽  
Reduce Energy Consumption

In geographical areas with cold climates, large, massively constructed industrial and warehouse buildings and logistics complexes are large consumers of energy resources. The great height and large contained volumes of the premises, the presence of a significant number of doors, and building configurations that include many transport corridors all require the use of air-thermal curtains to increase the energy efficiency of the buildings’ heating, ventilating, and air-conditioning (HVAC) systems, which commonly produce several thousand kilowatts of thermal power. Optimization of air curtains can improve the microclimates of the premises, achieve savings in the initial construction costs, and also reduce energy consumption during operation by 10–20%.

Impacts of Air Conditioning Equipment Sizing on Energy Performance of US Office Buildings

2021 ◽  
pp. 1-24
Author(s):  
Franklin Chiu ◽  
Moncef Krarti
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Performance ◽  
Office Buildings ◽  
Peak Demand ◽  
Capital Costs ◽  
Wide Range ◽  
Ac Systems ◽  
Equipment Sizing ◽  
Conditioning Equipment

Abstract The paper summarizes the results of a systematic and comprehensive analysis to investigate the impacts of inadequate sizing air conditioning (AC) systems on the overall energy consumption of medium and large office buildings located in representative US cities. The effects of proper sizing on the overall and disaggregated AC systems are evaluated in terms of energy consumption, peak demand, equipment run-time, and indoor thermal comfort. The presented analysis covers the performance a wide range of AC equipment components that serve US office buildings including packaged rooftop units as well as central cooling plants. The analysis results indicate that oversizing penalties can be significant on the annual energy consumption and electrical peak demand as well as capital costs for both medium and large office buildings. In particular, the reliance on simplified calculation methods and rules-of-thumb to determine equipment capacities can lead to significantly oversizing AC systems for office buildings in the vast majority of US climates and can result in increases of annual energy consumption and electrical peak demand of up to 29%. Moreover, oversizing increases capital costs required for air conditioning office buildings and extends cycling periods and associated structural stresses and failures of AC equipment.

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.

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