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Efficient natural ventilation depends largely on how responsive a building is to changing conditions both indoors and out. Even in otherwise well designed buildings, an inappropriate reaction can cause major operational problems. This may mean levels of comfort and energy consumption are unsatisfactory.

This article examines a potential solution, an intelligent control strategy, to provide the required ventilation rate and cooling capacity.

Lower energy consumption seems to be one of the main benefits of natural ventilation. However, savings on cooling and fan power could be overturned by energy spent on heating. Natural ventilation systems tend to require more heating because of the difficulties in controlling the exact amount of ventilation air and a lack of heat recovery.

As a result, the ultra-energy-efficient dwelling (such as the 鈥減assive house鈥�) relies on mechanical ventilation with heat recovery units rather than natural ventilation in order to keep energy consumption to a minimum. In time, the efficiency of chillers, fans and heat recovery systems will progress to the point where natural ventilation could be hard to justify.

Comfort and operational issues are other areas of concern with natural ventilation. Applied ventilation systems must ensure the right level of temperature and amount of fresh air and handle potential problems such as safety, risk of draught and noise from internal and external sources. Therefore, in order to make naturally ventilated buildings competitive in the long term, a very tight control strategy needs to be set.

Control strategy

As with the mechanical route, natural ventilation airflow is a function of ventilation source capacity and system airflow resistance. However, in contrast to the former, the available capacity of natural ventilation is limited and hard to predict. Constant airflow through the building can be maintained only by fine-tuning the building design, and control of the openings (Figure 1).

Control takes into account

various scenarios of indoor and outdoor conditions so the size and degree of openings will compensate for lower outdoor temperatures or higher wind speeds to provide just the required amount of fresh air or cooling capacity. Therefore, it is proposed to define a new openings size as the ratio of required airflow/cooling to the resulting maximum available airflow/cooling.

The required level of ventilation/cooling capacity is an output of the room controller (constants or temperature and CO2 controller). The maximum available airflow/cooling capacity can be defined using the formulas shown above, with the use of indoor air temperature and readings from the weather station, such as outdoor temperature, wind speed and direction. Several building parameters, such as openings size and location, also need to be taken into account.

The proposed formulas describing the airflow through the building and related cooling capacity are given here (see file attached). The basic formula (Formula 1) for spaces ventilated naturally through direct window openings is based on the Pfaff formula, which was established using numerous tracer gas airflow measurements. This formula would need to be modified if secondary openings are used, such as double skin facade or ductwork (Formula 2). The available cooling capacity could be defined based on the potential airflow and the temperature difference (Formula 3).

Driving forces

The main driving forces of natural ventilation are buoyancy and wind effect. These depend on several factors such as:

•  construction data, such as size, depth of the building, location, construction and size of openings
•  indoor temperature
•  weather data, such as wind speed and direction and outdoor temperature.

Both wind and buoyancy depend on the building characteristics but their sensitivity to the building data is different. Wind-driven flow is turbulent in nature, while the buoyancy relies on the laminar flow through the building.

Wind dominates over buoyancy in most cases, unless relatively high resistance of openings with secondary openings is applied. Figure 2 illustrates the exemplary impact of the opening鈥檚 admittance on the airflow through the building for buoyancy or wind-driven airflow.

Limit functions

The strategy described above enables the natural ventilation openings to deliver the required ventilation rate and/or cooling capacity. However, while doing so, the control system should limit noise and visual disturbances arising from operating the opening鈥檚 actuators and manage additional issues of draught, security and weatherproofing. Finally, the user should always have the ability to override manually the position of the openings.

All the limitations have a different impact on the final selection of the actuator鈥檚 position. Both weatherproofing and security are more like alert functions and they override all the other control functions. Noise and visual disturbance related to the actuator鈥檚 work can be limited by very slow and silent motors, which are already available on the market. If these are not provided, the windows鈥� position should be updated at a specified interval (eg every 15 minutes) and follow an integrated value of the defined actuator鈥檚 positions during this time.

A harder challenge is to predict and reduce risk of draught during operation of the windows. The proposed control algorithm above reduces the risk of draught by keeping the airflow tight at required level. It handles especially well the draught caused by a higher wind speed, since an increase in wind speed results in smaller openings of the facade. This will offset the wind impact and allow for a more laminar flow induced by the buoyancy effect only.

Additional anti-draught measures should be considered during design so the allowed amount of fresh air for low outdoor temperature does not cause the risk of draught. For example, allow only for high-level openings and place radiators underneath, or supply the outside air through larger perforated areas such as ceiling voids.

In case these anti-draught measures are insufficient, it is proposed the control mode should operate in two modes separately. The basic ventilation rate could be limited so it does not cause a risk of draught, however, as it does not provide sufficient ventilation air, additional short-term boost ventilation could be applied to fully refresh the air inside the space.

Boost ventilation could occur when the predicted quality of air drops below a certain limit and/or during specific moments, such as lunch or coffee breaks, or intervals between lessons.

Night cooling and weather prediction

In addition to the basic natural ventilation strategy described above, the efficiency of the natural ventilation to supply cooling capacity to the building can be increased by the use of night purging and weather prediction (Table 1).

The function of night purging alone is to offset the cooling loads of the building from the day before. In this way, night-time ventilation is allowed when overheating has occurred in the building. Detection of the overheated day can be based on the indoor temperature at the end of the occupied period. In the unoccupied period, under the condition that the outside air is colder than the inside air, the system opens the windows (Figure 3, previous page).

The complete control algorithm can be summarised by Formulas 5 and 6 in the box above right.

By applying the methods of night purging described by Formula 5 the building responds to the overheating already observed. The potential efficiency of the night cooling would be much higher if the control allowed for cooling down the building in advance of the hot day. In order to do that, prediction of extreme weather conditions and their impact on the indoor climate should be made. The prediction method can vary from a simple solution to complicated ones.

Simple weather prediction control strategies can be based on the assumption that a hot period seldom comes suddenly. It increases slowly as a wave of heat lasting a certain number of days. Therefore, when the system observes an increasing risk of overheating, action can be taken by lowering the cooling set point temperature. In case the cooling loads start to decrease, the prediction control reduces the pre-cooling of the building by increasing the set point to the default value.

In order to draw a conclusion on the coming heat wave, readings of the indoor temperature and outdoor conditions have to be compared with the readings from one day before (Formulas 7 and 8).

Conclusion

A four-year study at the University of Technology (TU) Delft, the Netherlands, analysed the performance of a typical office building with proposed control algorithms for single-sided natural ventilation together with night purging and a simple weather prediction algorithm. It used a large number of simulations and tests done in mock-ups and real building. The results showed that the building is able to maintain the operative indoor temperature under 26.5掳C during the average year and yet handle the risk of draught and other disturbances.

Thus, carefully designed natural ventilation may challenge mechanical cooling to provide excellent comfort levels and minimise energy consumption. However, such a building would require much greater care and customisation in design, construction and operation. Natural ventilation may indeed become the most energy-efficient design option, but not always an ultra low-budget one.