Stanislaw Kajl

Optimization of HVAC Control System Strategy Using Two-Objective Genetic Algorithm

Intelligent building technology for building operation, called the optimization process, is developed and validated in this paper. The optimization process using a multi-objective genetic algorithm will permit the optimal operation of the buildings mechanical systems when installed in parallel with a buildings central control system. Using this proposed optimization process, the supervisory control strategy setpoints, such as supply air temperature, supply duct static pressure, chilled water supply temperature, minimum outdoor ventilation, reheat (or zone supply air temperature), and zone air temperatures are optimized with respect to energy use and thermal comfort. HVAC system steady-state models developed and validated against the monitored data of the existing VAV system are used for energy use and thermal comfort calculations. The proposed optimization process is validated on an existing VAV system for two summer months. Many control strategies applied in a multi-zone HVAC system are also tested and evaluated for one summer day.

Evolutionary algorithms for multi-objective optimization in HVAC system control strategy

The supervisory control strategy set points for an existing HVAC system could be optimized using a two-objective evolutionary algorithm. The set points for the supply air temperature, the supply duct static pressure, the chilled water temperature, and the zone temperatures are the problem variables, while energy use and thermal comfort are the objective functions. Different evolutionary algorithm methods for two-objective optimization in HVAC systems are evaluated. It was concluded that controlled elitist non-dominated sorting genetic algorithms offer great potential for finding the Pareto-optimal solutions of investigated problems. The results also showed that the on-line implementation of optimization process could save energy by 19.5%. The two-objective optimization could also help control daily energy use while bringing about further energy use savings as compared to a one-objective optimization.

Two-objective on-line optimization of supervisory control strategy

The set points of supervisory control strategy are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values of zone temperatures, supply duct static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes all the individual component models developed and validated against the monitored data of an existing VAV system. It serves to calculate energy use during the optimization process, whereas the actual energy use is determined by using monitoring data and the appropriate validated component models. A comparison, done for one summer week, of actual and optimal energy use shows that the on-line implementation of a genetic algorithm optimization program to determine the optimal set points of supervisory control strategy could save energy by 19.5%, while satisfying the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy than the application of the one-objective optimization problem.

Ventilation Control Strategy Using the Supply CO2 Concentration Setpoint

This paper proposes a new ventilation control strategy applied to multiple spaces subject to variable occupancy. The strategy specified for real-time, online ventilation control takes advantage of uninitiated air from some overventilated spaces to be used as fresh outdoor air in order to reduce system energy use while maintaining the indoor air quality (IAQ) in each space. This proposed strategy maintains a supply CO2 concentration setpoint low enough to dilute CO2 generated by full occupancy in critical zones. The supply CO2 concentration setpoint could be determined online using the monitored zone airflow rates. It is tested and evaluated by making comparisons with other known control strategies. An existing VAV system installed at the École de technologie supérieure is used to evaluate this new strategy. The outdoor air fraction and associated energy use of investigated ventilation control strategies are calculated using the VAV system component models that are developed and validated against the monitored data.

Prediction of building thermal performance using fuzzy decision support system

An approach to predicting building thermal performance by means of a fuzzy decision support system (FDSS) is proposed in this paper. The following factors are considered for prediction purposes: indoor and outdoor air temperatures, solar radiation, internal gains, wind speed, time (hour and date). A decomposition of a building heat flow into seven (7) components is proposed and respective partial knowledge bases are created for the prediction of the building performance or the control and diagnostics of heating, ventilating and air conditioning (HVAC) systems. The simulation results show that the presented method seems to be promising.<<ETX>>

Study of potential nonconformities of a new recreation center building's envelope

This article presents a building envelopes analysis in order to verify the compliance with mandatory provisions of the Model National Energy Code for Buildings in Canada (MNECB 1997). Because some of the requirements are «not met», investigations were carried out to provide justifications in order to prove that the building can be considered as an exception to the mandatory provisions of MNECB. Therefore, we evaluate the impact of three (3) potential nonconformities of the buildings walls on the building energy performance. In regards to article 3.1.1.1.4 of MNECB, there is an exception if it can be proved that permanent process (like heat recovery of refrigeration compressors) can produce at all times enough heat that no other heating source is required. First of all, by using simulation, we were able to indicate that almost all buildings heating will be provided by energy recovery from ice rinks refrigeration systems (99.2%). Secondly, by using an energy analysis carried out with HEAT2 software, we can show that the increase of heating energy demand caused by the 3 studied walls is very low. This represents an increase of the heating energy demand of only 0.2%, and this, regardless of the heat recovery process. Because the nonconforming wall sections are small (0.97% of the envelope area), this mainly explains the minor impact in terms of building performance. In conclusion, according to the results obtained, we were able to recommend the building for consideration as an exception to the mandatory provisions of MNECB.

Simplified optimization method for preliminary design of HVAC system and real building application

HVAC systems (heating, ventilation, and air conditioning) are recognized as the greatest energy consumers in commercial and institutional buildings. Generally, designers use common sense, historical data, and subjective experience in designing these systems; this includes the number of systems chosen and the grouping of the zones served by these systems. HVAC energy efficiency is not an easily calculable criterion during the selection of these systems; usually the first selection criterion is the weakest investment cost. In this article, we present a simplified optimization method for preliminary design of HVAC system using the zones’ daily profile loads. A global load ratio is applied as an optimization function. The global load ratio represents the relationship between the systems real load and its possible maximum load for a given period. The variables for the optimization problem are: (i) grouping of the zones served by the systems and (ii) number of systems serving the building. Type of system was preselected for the present study, but this could also serve as an optimization variable. The correlations between global load ratio and energy consumption were shown using an office building. Then, this method was applied on an existing institutional building and compared with the detailed optimization method. In the second method, the HVAC energy consumption, calculated using DOE-2 software, was used as the optimization function. The comparison made among the existing, reference, and optimized buildings (all sharing the same constraints) have yielded significant energy savings for HVAC energy consumption. A life cycle cost analysis has also been done to estimate savings in terms of investment, operation and maintenance costs. These savings depend upon building configuration, the constraints imposed, the types of HVAC systems selected, and the control strategies for these systems.

On fuzzy control of ventilation process in air-ventilated closed areas with emission of noxious gases

This paper presents the idea of the application of a fuzzy logic controller to the control of a ventilation process in air-ventilated closed areas with emission of noxious gases. The results of the simulation of such a control using an approximate model of the process mentioned above are shown. The experiment indicates that the delay time in the inflow of fresh air causes unfading oscillations of the concentration of gases, which may exceed the admissible level.<<ETX>>