scholarly journals Energy-Optimal Structures of HVAC System for Cleanrooms as a Function of Key Constant Parameters and External Climate

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 313
Author(s):  
Mieczysław Porowski ◽  
Monika Jakubiak
Keyword(s):  
Optimal Control ◽  
Objective Function ◽  
Energy Demand ◽  
Heat Recovery ◽  
Optimization Procedure ◽  
Simulation Models ◽  
Primary Energy ◽  
Hvac Systems ◽  
Hvac System ◽  
Optimal Structures

This article presents approximating relations defining energy-optimal structures of the HVAC (Heating, Ventilation, Air Conditioning) system for cleanrooms as a function of key constant parameters and energy-optimal control algorithms for various options of heat recovery and external climates. The annual unit primary energy demand of the HVAC system for thermodynamic air treatment was adopted as the objective function. Research was performed for wide representative variability ranges of key constant parameters: cleanliness class—Cs (ISO5÷ISO8), unit cooling loads —q˙j (100 ÷ 500) W/m2 and percentage of outdoor air—αo (5 ÷ 100)%. HVAC systems are described with vectors x¯ with coordinates defined by constant parameters and decision variables, and the results are presented in the form of approximating functions illustrating zones of energy-optimal structures of the HVAC system x¯* = f (Cs, q˙j, αo). In the optimization procedure, the type of heat recovery as an element of optimal structures of the HVAC system and algorithms of energy-optimal control were defined based on an objective function and simulation models. It was proven that using heat recovery is profitable only for HVAC systems without recirculation and with internal recirculation (savings of 5 ÷ 66%, depending on the type of heat recovery and the climate), while it is not profitable (or generates losses) for HVAC systems with external recirculation or external and internal recirculation at the same time.

Optimization of the HVAC system design to minimize primary energy demand

2014 ◽  
Vol 76 ◽  
pp. 102-108 ◽  
Author(s):  
Janghoo Seo ◽  
Ryozo Ooka ◽  
Jeong Tai Kim ◽  
Yujin Nam
Keyword(s):  
System Design ◽  
Energy Demand ◽  
Primary Energy ◽  
Hvac System ◽  
Primary Energy Demand

scholarly journals Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 730
Author(s):  
Mohamed Toub ◽  
Chethan R. Reddy ◽  
Rush D. Robinett ◽  
Mahdi Shahbakhti
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Hvac Systems ◽  
Hvac System ◽  
Operational Cost ◽  
Concentrated Solar Power ◽  
Future Directions ◽  
Control Techniques ◽  
Optimal Energy Management ◽  
Solar Field

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost.

scholarly journals The influence of internal installation solutions in single-family housing on the "EP" factor in the light of the new requirements of WT 2021

2021 ◽  
Vol 20 (2) ◽  
pp. 029-040
Author(s):  
Aneta Biała
Keyword(s):  
Energy Demand ◽  
Heat Recovery ◽  
Primary Energy ◽  
Single Family ◽  
Primary Energy Demand ◽  
Building Insulation ◽  
Demand Factor ◽  
Recovery System ◽  
Different Types ◽  
Family Housing

The first part of the article presents the upcoming changes in the regulations regarding energy consumption by single-family housing. Current and forthcoming requirements in 2021 for building insulation and maximum EP primary energy demand factor were indicated. The second part of the paper presents the results of research aimed at determining what type of heat source for heating purposes and the type of ventilation will be able to meet the latest requirements. The analysis was based on the determination and comparison of the EP factor in the considered single-family building for selected heating variants assuming two different types of ventilation: gravitational and mechanical supply-exhaust with heat recovery system. Based on the results obtained, an attempt was made to determine the tendency of changes in the design of single-family buildings in terms of choosing the type of heating and ventilation.

Analysis of HVAC Energy in Automotive Paint Shop

2015 ◽  
Author(s):  
Lujia Feng ◽  
Laine Mears
Keyword(s):  
Energy Demand ◽  
Thermodynamic Simulation ◽  
Simulation Models ◽  
High Energy ◽  
Optimal Operation ◽  
Working Environment ◽  
Hvac System ◽  
Paint Shop ◽  
Automotive Manufacturing ◽  
Automotive Paint

Paint shop is the biggest energy consumer in automotive manufacturing plant. Large amount of conditioned air, which leads to a high energy demand, is one of the basic demands in guaranteeing high quality product and a comfortable working environment. A good design of HVAC system in the paint shop is also crucial in energy conservation. This paper presents thermodynamic simulation models of the HVAC system for both painting booth and building. Key parameter effects of the energy consumption were analyzed; different air flow routes were compared. Finally, optimal operation strategies in terms of energy, cost, and emission were discussed.

scholarly journals A study on evaluation systems for optimized design GSHP and ES technologies used in HVAC systems

2021 ◽  
Author(s):  
Ruifang Zhou ◽  
Dejian Gong ◽  
Shengjie Zhu ◽  
Jianchao Ma ◽  
Jiufa Chen
Keyword(s):  
Life Cycle Cost ◽  
Evaluation System ◽  
Operating Cost ◽  
Primary Energy ◽  
Hvac Systems ◽  
Optimized Design ◽  
Fuzzy Evaluation ◽  
Hvac System ◽  
Evaluation Systems ◽  
Annual Operating Cost

Abstract Due to the lack of suitable evaluation systems for heating, ventilation, air-conditioning (HVAC) systems with ground source heat pump (GSHP) and energy storage (ES) technologies, it is difficult to design a building HVAC system to achieve optimized design with regard to investment cost, energy saving and environmental protection. This is a study on developing a fuzzy evaluation system by including GSHP and ES with comprehensively determined weights into an HVAC system. A questionnaire method was used and the answers from 21 HVAC experts were analyzed to facilitate the modeling. Taking a commercial integrated project in Nanjing as an engineering case, the evaluation system was tested. If the system with a comprehensive merit value of 0.303 is adopted, the annual operating cost is reduced by 32.5%, the annual total life cycle cost is reduced by 26.5% and the primary energy consumption and carbon emissions are reduced by 10.5%, with the initial investment increased by 6.5%. This study revealed that the newly developed evaluation system is very useful for realizing the optimal design of HVAC systems.

Saving Primary Energy Consumption Through Exergy Analysis of Combine Distillation and Power Plant

2012 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Alhassan Salami Tijani ◽  
Nazri Mohammed ◽  
Werner Witt
Keyword(s):  
Energy Consumption ◽  
Power Plant ◽  
Heat Pump ◽  
Heat Recovery ◽  
Energy Savings ◽  
Primary Energy ◽  
Heat Pumps ◽  
Saturated Steam ◽  
Distillation Unit ◽  
Primary Energy Consumption

Industrial heat pumps are heat-recovery systems that allow the temperature ofwaste-heat stream to be increased to a higher, more efficient temperature. Consequently, heat pumps can improve energy efficiency in industrial processes as well as energy savings when conventional passive-heat recovery is not possible. In this paper, possible ways of saving energy in the chemical industry are considered, the objective is to reduce the primary energy (such as coal) consumption of power plant. Particularly the thermodynamic analyses ofintegrating backpressure turbine ofa power plant with distillation units have been considered. Some practical examples such as conventional distillation unit and heat pump are used as a means of reducing primary energy consumption with tangible indications of energy savings. The heat pump distillation is operated via electrical power from the power plant. The exergy efficiency ofthe primary fuel is calculated for different operating range ofthe heat pump distillation. This is then compared with a conventional distillation unit that depends on saturated steam from a power plant as the source of energy. The results obtained show that heat pump distillation is an economic way to save energy if the temperaturedifference between the overhead and the bottom is small. Based on the result, the energy saved by the application of a heat pump distillation is improved compared to conventional distillation unit.

Data mining approach for improving the optimal control of HVAC systems: An event-driven strategy

2021 ◽  
Vol 39 ◽  
pp. 102246
Author(s):  
Junqi Wang ◽  
Jin Hou ◽  
Jianping Chen ◽  
Qiming Fu ◽  
Gongsheng Huang
Keyword(s):  
Data Mining ◽  
Optimal Control ◽  
Hvac Systems ◽  
Data Mining Approach ◽  
Event Driven

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 A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

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