The design of solar power thermoelectric radiant panel as cooling system in small buildings under tropical climate

Energy efficient HVAC systems

A Study on Floor Supply Air Conditioning System in Building Structure Thermal Storage with Granulated Phase Change Materials : (Part3) Thermal characteristics from experiments simulated air conditioning system in office buildings

Energy Efficiency Analysis in Building Walls in Tropical Climate Using Thermal Insulation System

This paper presents an energy performance assessment on an educational building in Barranquilla, Colombia. The electricity consumption performance was assessed using the software DesignBuilder for two different Air Conditioning (AC) systems. The current electricity intensity is 215.3 kWh/m2-year and centralized AC systems with individual fan coils and a water chiller share 66% of the total consumption and lighting at 16%. The simulation of the AC technology change to Variable Refrigerant Flow (VRF) resulted in an improvement of 38% in AC energy intensity with 88 kWh/m2-year and significant savings in electricity consumption and life-cycle cost of AC systems in buildings.

In tropical climate countries including Vietnam, external heat absorbed into buildings in summer time is mainly depended on solar radiation transmitted through glass windows. This article aims to illustrate data representing the relation among SHGC, OTTV, and energy costs of air conditioning system in buildings.

Review on heat pump coupled desiccant wheel dehumidification and air conditioning systems in buildings

Fuel and electricity consumption for buildings is a crucial aspect of the tropical countries’ policy for limiting national electricity use and thereby reducing atmospheric carbon emissions. Currently, the energy demand for space conditioning is significantly higher, dominated by vapor compression air conditioning systems that contribute 30% of the global electricity consumption in tropical zones. Application of thermoelectric cooling modules can be regarded as one of the favorable options to solve the issue of high electricity consumption and CO2 emissions. This chapter reviews the growing importance of thermoelectric air conditioning systems in buildings. Moreover, thermoelectric coolers that work on the principle of Peltier effect possess certain advantages such as compact size, no moving parts, easy cooling rate control, long life span, and no liquids or gases. In this study, the present scenario of energy supply, energy demand and energy consumption in different sectors of tropical countries is discussed in more detail. Furthermore, the working principles of conventional air conditioning systems are presented and compared with thermoelectric air conditioning principle. This chapter also includes the recent investigations on the advancements and developments in thermoelectric air conditioning for buildings. Finally, this study tends to understand how efficiently thermoelectric cooling systems generate cooling, and its potential to replace traditional air conditioning systems.

Two demonstrations of solar air-conditioning and heating system in office building are introduced, one is solar heating system with seasonal storage, flat plate solar collector integrated into external wall, the solar fraction for space heating is 25%, another is solar-assisted air-conditioning system, evacuated tube solar collector integrated with flat roof, the solar fraction for space heating is 20%, for air-conditioning is 50%. The auxiliary energy equipment is ground-source heat pump system. The control strategy for solar system and auxiliary energy system are also introduced. The project is financial by National Renewable Energy Fund of China.

Heating, ventilation, and air conditioning (HVAC) systems in buildings have great potential to provide regulation capacity that is leveraged to maintain the balance of supply and demand in the power system. In order to make full use of HVAC’s regulation capacity, it is important to accurately evaluate it ahead of time. Because physical model-based approaches are hard to implement and highly personalized for each building, data-driven approaches are preferable for this capacity evaluation. However, given the insufficient data for individual buildings and buildings’ potential unwillingness to share their data because of privacy concerns, it is extremely challenging to build a high-performance data-driven regulation capacity evaluation model. In this paper, we propose a privacy-preserving framework that combines federated learning and transfer learning to evaluate the regulation capacity of HVAC systems in heterogeneous buildings. Specifically, a classified federated learning algorithm is proposed to build capacity evaluation models of HVAC systems for different building types. Each building trains its model locally without sharing data with other buildings to preserve privacy. The algorithm also tackles data insufficiency and achieves high evaluation accuracy. In addition, we design a cross-type transfer learning algorithm to enhance model generalization and further address data deficiency. A protocol is created for the above two algorithms to protect privacy and security. Finally, numerical case studies are conducted to validate the proposed framework.

Energy policy for integrating the building environmental performance model of an air conditioned building in a subtropical climate

In this paper an abstract model for adaptation of enterprise technologies in heterogeneous networks of small devices is proposed. The model is based on hierarchical multi- tier approach for better manageability and administration. Its structure allows not only separation between business and presentation logic, but also separation of enterprise and automation functions. Thus, changes in business and automation logics do not affect the user. The actual distribution of functions appears on the service and automation tiers. The level of abstraction of the model allows its usage in various environments - home and office automation, industry, medicine, agriculture. In the paper an experimental application of the presented model for an effective management of HVAC (heating, ventilation and air conditioning) systems in buildings is discussed. subsystems. The key goal of the work, presented in the paper, is the analysis of the latest off-the-shelf technologies in business information systems and their possible adaptation in distributed automation, based on controllers with embedded communication facilities. For this purpose, a model of information flow and representation in distributed automation systems is developed, employing the standards of e-business, working on the web. An experimental application of the presented model for an effective management of Heating, Ventilation, and Air-Conditioning (HVAC) systems in residential buildings is proposed. The limited resources of the embedded devices as well as the dynamic nature of building's automation networks are impending factors for the adaptation of web services into the systems. The rest of the paper is organized as follows:

Warming impact on energy use of HVAC system in buildings of different thermal qualities and in different climates

Comparative analysis of cooling energy performance between water-cooled VRF and conventional AHU systems in a commercial building

The importance of the security of building management systems (BMSs) has increased given the advances in the technologies used. Since the Heating, Ventilation, and Air Conditioning (HVAC) system in buildings accounts for about 40% of the total energy consumption, threats targeting the HVAC system can be quite severe and costly. Given the limitations on accessing a real HVAC system for research purposes and the unavailability of public labeled datasets to investigate the cybersecurity of HVAC systems, this paper presents a dataset of a 12-zone HVAC system that was collected from a simulation model using the Transient System Simulation Tool (TRNSYS). It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings [1] by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.

As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort and reducing energy consumption. These HVAC systems in smart buildings rely 'on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks. Such faulty sensor inputs may lead to the violation of indoor environment requirements (e.g., temperature, humidity, etc.) and the increase of energy consumption. While many model-based approaches have been proposed in the literature for building HVAC control, it is costly to develop accurate physical models for ensuring their performance and even more challenging to address the impact of sensor faults. In this work, we present a novel learning-based framework for sensor fault-tolerant HVAC control, which includes three deep learning based components for 1) generating temperature proposals with the consideration of possible sensor faults, 2) selecting one of the proposals based on the assessment of their accuracy, and 3) applying reinforcement learning with the selected temperature proposal. Moreover, to address the challenge of training data insufficiency in building-related tasks, we propose a model-assisted learning method leveraging an abstract model of building physical dynamics. Through extensive experiments, we demonstrate that the proposed fault-tolerant HVAC control framework can significantly reduce building temperature violations under a variety of sensor fault patterns while maintaining energy efficiency.