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 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 Performance Analyses of Temperature Controls by a Network-Based Learning Controller for an Indoor Space in a Cold Area

2020 ◽  
Vol 12 (20) ◽  
pp. 8515 ◽  
Author(s):  
Jonghoon Ahn
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Use ◽  
Fuzzy Logic Controller ◽  
Sustainable Use ◽  
Adaptive Controller ◽  
Comfort Level ◽  
Effective Control ◽  
Control Precision ◽  
Neural Network Controller

For the sustainable use of building spaces, various methods have been studied to satisfy specific conditions required by the characteristics of space types and the energy use in operation. However, several effective control approaches adopting the latest statistical tools may have problems such as higher control precision increases energy consumption, or lower energy consumption decreases their control precision. This study proposes an optimized model to reach the indoor set-point temperature by controlling the amount of heating supply air and its temperature and investigates the efficiency of an adaptive controller to maintain indoor thermal comfort within setting ranges. In the consistency of the comfort level, the fuzzy logic controller was found to be 1.76% and the artificial neural network controller to be 17.83%, respectively, more efficient than the conventional thermostat. In addition, for energy use efficiency, both of the controllers were confirmed to be over 3.0% more efficient. Consequently, the network-based controller with the adaptive controller checking comfort levels effectively works to improve both energy efficiency and thermal comfort. This improvement can be significant in places such as commercial high-rises, large hospitals, and data centers where many spaces are intensively woven with appropriate thermal environments to maintain users’ workability.

Energetic and Economic Potential for Load Control for Residential Customers in Austin, TX

2020 ◽  
Author(s):  
Arkasama Bandyopadhyay ◽  
Julia P. Conger ◽  
Emily A. Beagle ◽  
Michael E. Webber ◽  
Benjamin D. Leibowicz
Keyword(s):  
Energy Consumption ◽  
Demand Response ◽  
Linear Optimization ◽  
Peak Load ◽  
Load Control ◽  
Control Mechanisms ◽  
Electricity Grid ◽  
Water Heaters ◽  
Direct Load Control ◽  
Air Conditioning Systems

Abstract This study uses a linear optimization framework to evaluate the effect of different demand response (DR)/load control mechanisms on reduction in peak load and energy consumption from the electricity grid in a home with four major controllable appliances — HVAC (heating, ventilation, and air-conditioning) systems, electric water heaters (EWHs), electric vehicles (EVs), and pool pumps (PPs). Two incentive-based DR methods and four price-based DR schemes — real time pricing (RTP), time-of-use (TOU) rates, critical peak prices (CPP), and variable peak prices (VPP) — are analyzed. Load reduction potential is evaluated for scenarios where the home has both onsite solar and storage, only solar, and no solar or storage. Results show that, from the utility’s perspective, the optimal load control schemes, which result in greatest reduction in peak load and energy consumption from the grid during peak hours, are CPP and VPP (critical price option). By considering the combined effect of demand response, solar generation, and energy storage systems, this study aims to equip electric utilities with the ability to make decisions about dynamic rate design and direct load control to curtail peak demand and shift energy usage.

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 Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season

2020 ◽  
Vol 12 (22) ◽  
pp. 9667
Author(s):  
Jonghoon Ahn
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Use ◽  
Learning Algorithm ◽  
Adaptive Controller ◽  
Comfort Level ◽  
Adaptive Model ◽  
Comfort Levels ◽  
Proposed Model ◽  
High Consistency

In thermal controls in buildings, recent statistical and data-driven approaches to optimize supply air conditions have been examined in association with several types of building spaces and patterns of energy consumption. However, many strategies may have some problems where high-control precision may increase energy use, or low energy use in systems may decrease indoor thermal quality. This study investigates a neural network algorithm with an adaptive model on how to control the supply air conditions reflecting learned data. During the process, the adaptive model complements the signals from the network to independently maintain the comfort level within setting ranges. Although the proposed model effectively optimizes energy consumption and supply air conditions, it achieves quite improved comfort levels about 14% more efficient than comparison models. Consequently, it is confirmed that a network and learning algorithm equipped with an adaptive controller properly responds to users’ comfort levels and system’s energy consumption in a single space. The improved performance in space levels can be significant in places where many spaces are systematically connected, and in places which require a high consistency of indoor thermal comfort. Another advantage of the proposed model is that it properly reduces an increase in energy consumption despite an intensive strategy is utilized to improve thermal comfort.

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 Smart HVAC Control in IoT: Energy Consumption Minimization with User Comfort Constraints

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jordi Serra ◽  
David Pubill ◽  
Angelos Antonopoulos ◽  
Christos Verikoukis
Keyword(s):  
Energy Consumption ◽  
Smart Grids ◽  
Hvac Systems ◽  
Energy Price ◽  
Time Interval ◽  
Consumption Cost ◽  
Scheduling Method ◽  
Hvac Control ◽  
The Internet Of Things ◽  
Variable Energy

Smart grid is one of the main applications of the Internet of Things (IoT) paradigm. Within this context, this paper addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable energy price. To that end, first, we propose an energy scheduling method that minimizes the energy consumption cost for a particular time interval, taking into account the energy price and a set of comfort constraints, that is, a range of temperatures according to user’s preferences for a given room. Then, we propose an energy scheduler where the user may select to relax the temperature constraints to save more energy. Moreover, thanks to the IoT paradigm, the user may interact remotely with the HVAC control system. In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user’s device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.

scholarly journals Energy-Saving Potential of Extending Temperature Set-Points in a VRF Air-Conditioned Building

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2160 ◽  
Author(s):  
Joowook Kim ◽  
Doosam Song ◽  
Suyeon Kim ◽  
Sohyun Park ◽  
Youngjin Choi ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Saving ◽  
Energy Efficient ◽  
Air Conditioning ◽  
Control Strategies ◽  
Hvac Systems ◽  
Set Point ◽  
Energy Saving Potential ◽  
Human Thermal Comfort

Building energy savings and occupant thermal comfort are the main issues in building technology. As such, the development of energy-efficient heating, ventilation, and air-conditioning (HVAC) systems and the control strategies of HVAC systems are emerging as important topics in the HVAC industry. Variable refrigerant flow (VRF) systems have efficient energy performance, so the use of VRF systems in buildings is increasing. However, most studies on VRF systems focus on improving mechanical efficiency, with few studies on energy-efficient control while satisfying the thermal comfort of occupants. The goal is to estimate the energy-saving potential of adjusting the temperature set-points and dead-band (range) in VRF air-conditioned building. To do so, we analyzed the influence of control strategies of a VRF system on human thermal comfort and energy consumption using a simulation method. The results showed that energy consumption can be reduced by 25.4% for predicted mean vote (PMV)-based control and 27.0% for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) comfort range control compared with the typical set-point temperature control of a VRF system. The indoor thermal environments of the analyzed control strategies are controlled in the thermal comfort range, which is based on a PMV at ±0.5. Compared with the typical set-point control, PMV and ASHRAE comfort range-based control reduced the operation time of the compressor in the VRF system.

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