Static Pressure Reset Research Articles

Model-based optimal control strategy for multizone VAV air-conditioning systems for neutralizing room pressure and minimizing fan energy consumption

Control strategies for variable air volume (VAV) air-conditioning systems play a pivotal role in ensuring indoor environmental quality and energy efficiency. However, conventional approaches, such as static pressure reset (SPR) control, focus on managing indoor air temperature without considering the room pressure, which can lead to unbalanced room pressure and undesirable air leakage. Moreover, with the application of prevalent building pressure control strategies, such as airflow tracking control, to multizone VAV systems, neutralization of the room pressure is difficult across multiple zones in VAV systems. Therefore, this study introduces a model-based optimal control strategy for multizone VAV air-conditioning systems. The proposed strategy uses a multiobjective optimization framework to regulate fan frequencies and damper openings on both the supply and return sides. This holistic approach facilitates the simultaneous control of the indoor air temperature and room pressure while minimizing fan energy consumption. To assess the effectiveness of the proposed strategy, four control strategies were tested using a Python-based simulation testbed. The results demonstrate that the proposed strategy effectively maintains the indoor air temperature, neutralizes room pressure, and reduces fan energy consumption, thereby contributing to the overall efficiency of the VAV system. Moreover, the results highlight the limitations associated with combining airflow tracking control with SPR control for room pressure regulation in multizone VAV systems. This highlights the importance of adopting a model-based approach to address the complexities of concurrent room pressure and indoor air temperature control.

Static pressure reset control strategy for roof fans in centralized cooking exhaust systems

Excessive static pressure and inadequate flow rate at each terminal of the centralized cooking exhaust systems contribute to poor indoor air quality in kitchens. Roof fans can improve the ventilation performance of centralized cooking exhaust system, but the optimal control strategy for roof fans is currently unavailable. This paper proposes a static pressure reset control strategy for variable frequency operation of roof fans that follows the law of normal distribution of simultaneous operating rate. The effect of the roof fan on the static pressure and flow rate distribution in a centralized cooking exhaust system with multiple power sources of range hoods is investigated. The relationship between simultaneous cooking rate and the appropriate set point of the roof fan is determined using experimental and simulation methods. The results show that the proposed static pressure reset control strategy for roof fans has improved control performance and significant potential for energy savings.

Static pressure set-point reset smoothing scheme based-on improved iterative learning control and variable trajectory for air-conditioning system

Variable static pressure is the main strategy for air volume adjustment in variable air volume air-conditioning system and can offer huge energy savings compared with constant air volume systems. When parameter set-points reset with load, dynamic processes are excited. Some processes take a long time to reach a new stable state with large overshoots. Improved iterative learning control (ILC) algorithm is studied to ameliorate transition processes of the static pressure reset control loop. A mathematical model of the static pressure control loop is established, and a new desired trajectory is given to improve the system tracking performance. Simulation and experimental studies are performed on traditional Proportion Integration Differentiation (PID) control, Proportion Differentiation (PD) type ILC, fuzzy gain PD type ILC and variable speed-integral PID type ILC. Results show that the system has the smallest overshoot and the shortest adjustment time with the fuzzy gain PD type ILC. Meanwhile the system can be betterly stabilized near the set-point with smallest evaluation index and the desired trajectory can be tracked with better dynamic performance. Studies show that the dynamic process is smoothed by improved ILC and variable trajectory. It is of great significance to enhance the whole system stability.

Online reset strategy based on linear correlation for variable static pressure control of VAV system

In comparison with constant static pressure and total air volume control strategies, a static pressure reset strategy for variable static pressure control of Variable Air Volume (VAV) air conditioning systems shows evident energy-saving potential. How to establish a relationship between feedback parameters representing the load demand and duct static pressure setpoint has been attached great importance to. This study provides a novel static pressure reset strategy with a linear adjustment algorithm to build a simple linear functional relation between the terminal maximum damper position and the static pressure setpoint. Also, the robust regions are introduced into the algorithm to enhance the system stability and online applicability. Experiments are conducted to compare the proposed strategy with a fixed static pressure strategy and a static pressure reset strategy with a fixed step value in an integrated experimental control system for a VAV system. Experimental results indicate that all three strategies can realize real-time control of room temperature while the proposed strategy has better stability with the least number of setpoint reset times. The mean of the damper position is 16.74% and 8.56% higher than the other two strategies accompanying with a minimum of 5% energy saving of the proposed control method.

Modeling, air balancing and optimal pressure set-point selection for the ventilation system with minimized energy consumption

Traditional static pressure reset control strategies commonly use a feedback indicator to reset the static pressure; this results in under-ventilation in certain zones and over-ventilation in others. Based on this issue, the objective of this study was to develop a model-based, improved, static pressure reset control strategy, providing a well-balanced system to eliminate under-ventilation and over-ventilation, while consuming minimal energy. In the study reported here, a comprehensive mathematical model was established to simulate the non-linear behavior of the ventilation system, and a supervised machine learning algorithm for a support vector machine was used to obtain values for unknown parameters in the model. The resulting model was then used as the basis for development of a damper position control method and to determine the damper position, given a desired airflow rate. An optimal, static pressure set-point selection method was also proposed using the developed model to calculate the minimum static pressure set-point in a closed-form. As a result, the revised system consumed less energy owing to the better-balanced system and optimized pressure set-point selection. Moreover, through the application of the damper position control method, the ventilation system was well-balanced and eliminated both under-ventilation and over-ventilation. Experimental tests were carried out to validate the performance of the proposed method in comparison with the conventional static pressure reset strategy, data from which were collected to train the proposed model.

Rule-based fuzzy control method for static pressure reset using improved Mamdani model in VAV systems

In variable air volume air(VAV) conditioning systems, conventional methods for static pressure reset depends on accurate mathematics models which are often difficult to be built. On the contrary, controls, which are based on a series of control rules derived from the operating and commissioning experience, have the capacity to achieve better effects. A rule-based fuzzy control method (RBFCM) for static pressure reset is proposed using improved Mamdani model and functioning fuzzy subset inference method, which reflects the physical characteristics of the controlled object and is convenient for the engineers to understand and use. The development and implementation of the proposed RBFCM are necessary to demonstrate in detail. Through comparative experiments, the proposed RBFCM is compared with the conventional fixed-step method and itself with different actual domain in a control experiment platform for the VAV air conditioning system. Experimental results indicate that the proposed RBFCM has better control performances and outstanding energy-saving potential if the actual domain can be selected reasonably. A minimum of 33% energy saving rate of the proposed RBFCM with the optimal actual domain is shown through experimental study.

Impact of the duct static pressure reset control strategy on the energy consumption by the HVAC system

This article addresses different duct static pressure control strategies which could be implemented in variable air volume air-conditioning systems (VAV). Two pressure reset control strategies are compared to the commonly used control solution based on the “Constant static pressure” method. First pressure reset control strategy, known as PID Control, uses signals from VAV boxes controllers to reset duct static pressure in a way that one of the VAV dampers is maintained almost entirely open. Second strategy decreases static pressure setpoint until an adjustable number of pressure requests occur. As a response to the certain amount of requests, static pressure setpoint is increased. This strategy is called Trim & Respond. Both static pressure reset control strategies described in this paper are considered to have more significant potential for energy savings than the “Constant static pressure” method. In order to validate this potential, several simulations for different control strategies were carried out and the obtained results are compared and analysed. The theoretical limit of the energy savings - set of the optimal control actions, was estimated with Nelder-Mead algorithm and also presented in this article. General description of the static pressure control strategies Constant static pressure, PID Control and Trim & Respond is given.

Statistically informed static pressure control in multiple-zone VAV systems

The proliferation of Building Automation Systems (BAS) has enabled the development of and use of more complex algorithms for controlling HVAC systems and increase energy efficiency in commercial buildings. One such complex algorithm, static pressure reset, which is associated with minimization of the static pressure in the supply air duct at all times while still maintaining zonal comfort—is a proven low cost means to reduce fan power consumption in Variable Air Volume (VAV) systems.Here we explore the possibility of utilizing historical BAS data to estimate annual energy savings from static pressure reset in any facility. The approach employed first establishes a statistical relationship between the effective system loss coefficient as a function of the mean VAV damper position using the measured duct static pressure, VAV damper positions and airflows. Observed is that the system loss coefficient decreases with an increase in mean VAV damper position. Thus, the desired control algorithm for minimizing fan power should seek to maximize the individual VAV damper positions needed for comfort. However, for a given duct static pressure, control sensitivity is diminished as more dampers are opened fully. Application of Static Pressure Reset in a number of buildings reveals that there is a maximum number of zonal dampers that can be fully opened before control robustness diminishes. In this condition, any additional increase in damper position has little effect on the system and zonal flowrates. If more flow is required, the static pressure must be increased. In this context, given the system loss relationship with mean damper position and the estimated maximum number of dampers that can be opened, the potential increase in the mean damper position to a value achievable if the maximum number of dampers are opened can be estimated at all times in the study period. This permits estimation of the minimal static pressure required. Savings can be estimated for the historical conditions based upon comparison of the predicted fan power based upon the optimal static pressure with the actual fan power. This methodology was tested on three different buildings with varying system characteristics. Savings estimates correlated well to the savings actually realized from static pressure reset. This result has significant implications for energy service providers, who could use the predictions to guarantee savings from static pressure reset.

Experimental study on a novel fuzzy control method for static pressure reset based on the maximum damper position feedback

In variable air volume (VAV) systems, conventional control methods reset the supply air static pressure based on the exact mathematics model of the controlled objects which are often difficult to be founded, because the VAV controlled systems have the characteristics of nonlinear, multivariable and long delay times. In order to develop a simple inference process for real-time applications, this paper presents a novel fuzzy control method for static pressure reset with no using of the mathematics model. The proposed fuzzy control method is developed based on the maximum damper position feedback using Mamdani-type fuzzy rule and functioning fuzzy subset inference (FFSI). This study provides the detail implement process of the proposed fuzzy control method. Supported by the experimental data, the proposed method is compared with optimal fixed changing step method in an integrated control test rig for a VAV air conditioning system. Experimental results show that the proposed method has better energy efficient and control performance. A minimum of 7% energy saving of the proposed fuzzy control method is shown through experimental study.

A Review of Static Pressure Reset Control in Variable Air Volume Air Condition System

For the sake of energy saving of variable air volume (VAV) system, this paper presents the a review of static pressure control around the optimization problem of static pressure reset in VAV air conditioning system. Then, main control methods of static pressure reset are described, and existing problems are analyzed and concluded. Finally, it is pointed out that the critical technology and the development trend of static pressure reset control. This overview is not intended to be an exhaustive survey on this topic, and any omission of other works is purely unintentional.

Comparison of different fan control strategies on a variable air volume systems through simulations and experiments

Through a variable frequency drive (VFD), a variable air volume air handling system can significantly reduce supply fan power under partial load conditions. Typically, the VFD on a supply fan motor is modulated to maintain a supply air duct static pressure set point. The static pressure set point can be either constant or dynamically reset in response to different load conditions. In this paper, comprehensive mathematical models are established to describe the performance of a VFD-motor-fan system under three different static pressure control strategies: constant static pressure set point, static pressure reset by total airflow rate, and static pressure reset by highest zone demand. The total input power to the system, including the energy imparted into the air as well as the energy losses from the VFD, motor, and fan, are simulated and compared among the different static pressure reset strategies with different minimum airflow ratios. The simulation results show that more than 50% of electrical power savings can be realized by static pressure reset when the diversity of the zone thermal loads is moderate. In addition, although a lower minimum airflow ratio can result in more power savings, there were no significant power saving by reducing the minimum airflow ratio from 30% to 10% due to relatively high energy losses of the fan, motor and VFD at low load and speed conditions. Finally, experiments were carried out to demonstrate the performance comparison of three different control strategies.

A Static Pressure Reset Control System with a New Type of Flow Damper for Use in Low Pressure Ventilation Systems

The control strategy for mechanical ventilation systems has significant impact on the performance of the system, in terms of energy consumption and correct air distribution. This paper presents a static pressure reset control system employing a new type of flow damper with lower pressure loss for use in low pressure ventilation systems. The flow damper has a droplet shape that minimizes turbulence generation and the resulting pressure loss. The performance of the damper was examined by making measurements of pressure loss and airflow. These were used to determine the required pressure loss for operation and the airflow accuracy. Results were compared to similar tests carried out with conventional flat plate dampers. A static pressure reset control algorithm was programmed and analyzed on a test system consisting of three dampers, representing three office rooms. The comparison of the dampers shows that the droplet shaped damper resulted in an airflow of 234 L/s at 30 Pa pressure loss, more than twice the airflow past a flat-plate damper at the same pressure loss (114 L/s). Also the droplet shaped damper could operate precisely down to 5 Pa pressure loss. The programmed control algorithm ensured that one damper was always fully opened, based on the flow demand to the zone, and that this reduces the static pressure loss under partial load by up to 53%. However, as the maximum static pressure during the tests was 15 Pa, the reduction was only 8 Pa, so it was not possible to document any significant fan power saving compared to a fixed static pressure control. A maximum static pressure of 15 Pa is a reduction of more than 50% compared to flat-plate dampers that required at least 30 Pa to operate precisely; this is expected to yield fan energy savings in practice.

Energy Saving Strategies for Air Handlers

ABSTRACT As a central part of the HVAC system for most commercial buildings, air handlers offer a variety of energy saving opportunities. This article discusses many, but not all, energy savings strategies and actions associated with air handlers. Most energy engineers and facility managers are familiar with basic energy saving actions such as scheduling, variable speed control, economizing, and reducing outdoor air intake. Energy saving control strategies also include static pressure reset, good for a variable air volume (VAV) system, and discharge air temperature reset, more appropriate for a constant volume reheat or lab air system. Hot and cold deck reset can reduce the energy use of dual duct systems, which can also be partially or completely converted to VAV. Discharge air temperature control can be used to control humidity levels. Separate, dedicated air handlers for lab spaces and areas with high ventilation allow for higher supply air temperatures and savings in both cooling and reheat energy. Selecting supply air temperature and humidity levels based on temperature and humidity limits, as well as sensible and latent cooling loads, can allow for additional energy savings and improved climate control. Controls that can select the cooling coil discharge air temperature and the cooling coil bypass factor can allow for supply air that accurately meets loads and reduces costly reheating. Most data centers have no heating load, so rogue heating by HVAC systems serving data centers can easily be eliminated with a change in setpoints. Improved air distribution can reduce problems with uneven cooling in data centers, as well as help reduce fan energy use and avoid the costly addition of cooling capacity. Unnecessary humidification loads can also be essentially eliminated from a data center with proper discharge air temperature control.

System Design for Demand Controlled Ventilation in Multi-Family Dwellings

This paper presents an investigation into solutions for the system design of a centralized DCV system in multi-family dwellings. The design focused on simple and inexpensive solutions. A cost benefit estimate showed that the initial cost of implementing DCV in a system with an efficient heat exchanger should not exceed 3400 DKK per dwelling in regions with weather conditions similar to the Danish climate. A design expected to fulfil this requirement was investigated in detail with regard to its electricity consumption by evaluation of different control strategies. Systems with variable airflows are typically controlled by maintaining the static pressure at a fixed level at a selected point in the main duct. However, sustaining the static pressure at a fixed level at part load leads to throttling of all control components and thereby unnecessary energy consumption. Resetting the static pressure at part load reduces throttling and energy can be saved. A static pressure reset strategy was applied to a dwelling-specific DCV system where the airflow varied between three fixed rates. The system performance was evaluated for two diffusers. The annual electricity consumption was reduced by 20% to 30% when resetting the static pressure at part load condition compared to a control strategy with fixed static pressure.

Modelica-based modelling and simulation to support research and development in building energy and control systems

Traditional building simulation programs possess attributes that make them difficult to use for the design and analysis of building energy and control systems and for the support of model-based research and development of systems that may not already be implemented in these programs. This article presents characteristic features of such applications, and it shows how equation-based object-oriented modelling can meet requirements that arise in such applications. Next, the implementation of an open-source component model library for building energy systems is presented. The library has been developed using the equation-based object-oriented Modelica modelling language. Technical challenges of modelling and simulating such systems are discussed. Research needs are presented to make this technology accessible to user groups that have more stringent requirements with respect to the numerical robustness of simulation than a research community may have. Two examples are presented in which models from the here described library were used. The first example describes the design of a controller for a nonlinear model of a heating coil using model reduction and frequency domain analysis. The second example describes the tuning of control parameters for a static pressure reset controller of a variable air volume flow system. The tuning has been done by solving a non-convex optimization problem that minimizes fan energy subject to state constraints.