Seasonal optimisation of humidity control systems: how to harness winter potential and prepare for summer peaks

Author: Mycond Technical Department

Humidity control systems are usually designed for average annual or extreme summer conditions, which leads to significant energy overuse in winter due to constant operation of dehumidifiers despite the free potential of dry winter air, or to the inability to maintain target humidity in summer due to underestimation of peak loads. Let’s look at how correct seasonal optimisation helps avoid these common design errors and calculation ambiguities.

Introduction: annual humidity variations and their impact

The climate of the United Kingdom is characterised by significant seasonal changes in air parameters. In winter, with outdoor temperatures from -5°C to +5°C, relative humidity can be 70–90%, yet absolute humidity remains low – around 2–4 g/kg. In summer, when temperatures reach 20–30°C, absolute humidity can rise to 10–15 g/kg at the same relative humidity.

Ignoring these seasonal variations leads to serious energy and operational consequences. In particular, year-round use of mechanical dehumidifiers instead of ventilation-based dehumidification in winter causes electricity overspend of 30–50%. Failing to account for summer peaks often makes it impossible to maintain the design humidity on hot days.

A properly designed system with seasonal optimisation can reduce operating costs by 25–40% throughout the year, depending on the type of facility and equipment.

Physical foundations of seasonal humidity changes

To understand seasonal optimisation of dehumidification systems, it is necessary to consider the basic principles of psychrometry. The key is understanding the difference between relative and absolute humidity.

Absolute humidity (d) is expressed in grams of moisture per kilogram of dry air (g/kg) and indicates the actual moisture content regardless of temperature. This parameter is fundamental when calculating dehumidification potential.

Relative humidity (φ) is the ratio of the actual partial pressure of water vapour to the saturation vapour pressure at a given temperature, expressed as a percentage. With the same absolute humidity but different temperatures, relative humidity will differ.

The calculation of absolute humidity from known temperature and relative humidity can be performed using a psychrometric chart or using formulae that account for the partial pressure of water vapour.

Winter period: using dry air for ventilation dehumidification

In winter in London and other UK cities, outdoor air has low absolute humidity despite high relative humidity. This creates ideal conditions for using ventilation dehumidification.

The principle of ventilation dehumidification consists of replacing moist indoor air with dry outdoor air. The effectiveness of this method depends on the difference in absolute humidity: the greater the difference, the more effective the dehumidification.

The dehumidification potential is calculated by the formula:

W = L × (d_in - d_out)

where:

• W – amount of moisture removed, g/h;
• L – supply air volume, m³/h;
• d_in – absolute humidity of indoor air, g/kg;
• d_out – absolute humidity of outdoor air, g/kg.

Example: for a space with a volume of 1000 m³ with indoor parameters t_in = 20°C, φ_in = 60% (d_in ≈ 8.8 g/kg) and outdoor parameters t_out = 0°C, φ_out = 80% (d_out ≈ 3.0 g/kg), with an air change rate of 1 (L = 1000 m³/h), the dehumidification potential will be:

W = 1000 × (8.8 - 3.0) = 5800 g/h

However, ventilation dehumidification incurs heat losses for heating the supply air, which are calculated by the formula:

Q = L × ρ × c × (t_in - t_out)

where:

• Q – heat losses, W;
• ρ – air density, kg/m³ (approximately 1.2 kg/m³);
• c – specific heat capacity of air, J/(kg·K) (approximately 1005 J/(kg·K)).

For our example, the heat losses will be:

Q = 1000 × 1.2 × 1005 × (20 - 0) / 3600 = 6700 W

By comparing the energy consumption for heating the supply air with the energy consumption of a dehumidifier, it is possible to determine the break-even point – the outdoor air temperature at which ventilation dehumidification becomes energy efficient.

Summer period and peak loads

In summer, UK cities experience elevated values of absolute outdoor humidity, which creates maximum loads on dehumidification systems. Peak loads are formed from two main sources:

1. External moisture ingress – via infiltration and ventilation under maximum outdoor parameters.
2. Internal moisture sources – processes, people, products, open water surfaces, etc.

The calculation of moisture ingress from external sources is performed using the formula:

W_out = L_inf × ρ × (d_out(max) - d_in(target))

where:

• W_out – moisture ingress from external sources, g/h;
• L_inf – infiltration and ventilation volume, m³/h;
• d_out(max) – maximum absolute humidity of outdoor air, g/kg;
• d_in(target) – target absolute humidity of indoor air, g/kg.

The total peak load on the dehumidifier is determined considering all sources of moisture and a simultaneity factor:

W_peak = W_out(max) + W_in(max) + W_reserve

When designing dehumidification units, it is necessary to provide a capacity margin of 15–25% above the calculated peak load to ensure stable system operation.

Transitional seasons: spring and autumn

The shoulder periods in Britain are characterised by unstable outdoor conditions with significant daily fluctuations in temperature and humidity, complicating dehumidification control.

For effective operation during this period, it is recommended to implement adaptive control algorithms that automatically select the optimal operating mode depending on current parameters:

1. Real-time control of absolute humidity of outdoor and indoor air.
2. Automatic switching between ventilation and mechanical dehumidification depending on energy efficiency.
3. Combining dehumidification methods to optimise energy consumption.

Particular attention should be paid to preventing condensation during sharp cold snaps. To do this, it is recommended to:

• Monitor the indoor air dew point temperature and the surface temperatures of envelope structures.
• Proactively increase dehumidification intensity before a forecasted cold snap.
• Provide heating of critical zones if necessary (window openings, external walls).

A decision algorithm for preventing condensation can be as follows:

1. Determine the dew point of the indoor air.
2. Measure or forecast the minimum surface temperatures.
3. If the forecast surface temperature is lower than the dew point or approaches it (difference less than 2°C), take preventive measures:
   • Increase dehumidification intensity to lower the dew point.
   • Provide heating of critical zones.
   • Increase air circulation near cold surfaces.

Energy optimisation of seasonal modes

An annual analysis of the energy consumption of humidity control systems makes it possible to identify periods of maximum and minimum consumption and optimise system operation throughout the year.

To improve energy efficiency in the winter period, it is recommended to integrate heat recovery systems:

• Plate heat exchangers: efficiency 50–70%, no cross-contamination.
• Rotary heat exchangers: efficiency 70–85%, compact, possible cross-contamination.
• Heat pumps on exhaust air: COP above 300% relative to electrical input.

Using heat recovery significantly improves the energy efficiency of ventilation dehumidification in winter, reducing the cost of heating the supply air.

For the summer period, pre-cooling of supply air is effective:

• Indirect evaporative cooling: temperature reduction by 5–10°C without increasing humidity.
• Ground heat exchangers: using the stable ground temperature (8–12°C).

The economic efficiency of seasonal system adaptation is determined by comparing energy consumption under fixed and adaptive modes. Practice shows that additional investment in automation and heat recovery systems pays back within 1–3 years depending on the type of facility and energy tariffs.

Typical design mistakes and their consequences

Typical mistakes in designing seasonal modes of humidity control systems include:

1. Ignoring the winter potential of ventilation dehumidification – losing the opportunity to save 40–60% of energy.
2. Underestimation of summer peak loads by 20–30%, leading to an inability to maintain target humidity in summer.
3. Designing systems only for average annual parameters without considering extremes.
4. Lack of adaptive control during transitional periods.
5. Ignoring heat losses during winter ventilation.

Operational consequences of non-optimised seasonal modes:

• Electricity overspend in winter by 30–50%.
• Inability to maintain target humidity in summer.
• Accelerated equipment wear due to continuous maximum operation.
• Condensation risks in transitional seasons.
• Poor indoor climate for staff.

It is important to note that the proposed seasonal optimisation approaches may require adjustment or be ineffective in the following cases:

• With extremely low outdoor temperatures (below -20°C), when ventilation dehumidification may pose a risk to equipment.
• In processes with critical requirements for parameter stability, where temperature fluctuations are unacceptable.
• For small facilities where capital expenditure on adaptive control does not pay back.
• In climatic zones with a small annual amplitude of temperature and humidity.

Frequently asked questions (FAQ)

How to calculate the potential of winter ventilation dehumidification in detail?

The calculation of winter ventilation dehumidification potential is carried out in several steps. First, determine the absolute humidity of indoor and outdoor air from psychrometric tables or calculations. Then calculate the difference in absolute humidity Δd = d_in - d_out. The dehumidification potential is W = L × Δd, where L is the air exchange volume. To assess economic feasibility, compare the energy for air heating Q = L × ρ × c × (t_in - t_out) with the energy consumption of the dehumidifier. For example, for a warehouse with a volume of 5000 m³ at t_in = 18°C, φ_in = 60%, t_out = 2°C, φ_out = 85%, L = 2500 m³/h, the dehumidification potential will be approximately 11 kg/h with heating energy consumption around 15 kW, which is significantly more efficient compared to a mechanical dehumidifier of the same capacity.

Under which specific temperature and humidity values does outdoor air become ineffective for dehumidification?

Ventilation dehumidification becomes ineffective when the energy spent on heating the air exceeds the energy saved on the dehumidifier’s operation. The switching point is calculated from the comparison: E_vent < E_dehum, where E_vent is the heating energy and E_dehum is the dehumidifier energy to remove the same amount of moisture. For London, ventilation dehumidification is typically effective at t_out < 10°C and an absolute humidity difference greater than 2 g/kg. The switching point for each facility is calculated individually, considering the energy characteristics of the equipment. For example, for a system with a condensing dehumidifier (specific consumption 0.5 kWh/kg of moisture) and an electric heater, switching is advisable at outdoor temperatures above 5–7°C for Manchester.

What is the methodology for determining the peak summer load on the dehumidification system?

Determining the peak summer load includes assessing all possible moisture sources: 1) External sources: W_out = L_inf × ρ × (d_out(max) - d_in), where L_inf is the infiltration and ventilation volume; 2) Internal sources: processes, staff, products, evaporation from open surfaces; 3) Simultaneity factor K_simult (usually 0.8–1.0). Total peak load: W_peak = (W_out(max) + W_in(max)) × K_simult + W_reserve. For a 100 m² pool in Glasgow, for example, moisture release from the water surface is ~12 kg/h, from people ~2 kg/h, external ingress under maximum parameters ~8 kg/h, which, considering a simultaneity factor of 0.9 and a 20% reserve, gives W_peak ≈ 26 kg/h.

Which control parameters should be adjusted in the transitional seasons?

In transitional seasons, it is recommended to adapt the following parameters: 1) Humidity and temperature setpoints – adjust allowable ranges considering outdoor conditions; 2) PID controller algorithms – tune coefficients to ensure stable operation under variable conditions; 3) Fan operating modes – modulate speed depending on humidity load; 4) Switching thresholds between dehumidification modes – ventilation/mechanical; 5) Heat recovery modes – disable or enable bypass depending on temperatures. For the spring period in Edinburgh, for example, it is advisable to set a wider permissible humidity range (45–65% instead of 50–60%), increase the PID integration time, and configure automatic mode switching when d_out < d_in - 1 g/kg.

How to prevent condensation during sharp cold snaps?

To prevent condensation during sharp cold snaps, it is necessary to: 1) Calculate the dew point temperature from current indoor air parameters: t_dew = f(t_in, φ_in); 2) Identify critical zones with minimum surface temperatures (external walls, windows, thermal bridges); 3) Organise monitoring of surface temperatures t_surface; 4) When t_surface approaches t_dew (difference less than 3°C), activate preventive measures. For a warehouse with cold walls in Liverpool, an effective solution is a combination of: increasing air exchange near critical zones, reducing relative humidity by 10–15% 6–8 hours before the forecasted cold snap, and, if necessary, providing local surface heating to a temperature above t_dew + 3°C.

Conclusions

Seasonal optimisation of humidity control systems is a comprehensive engineering approach that enables significant economic and operational benefits. Key principles to consider when designing and operating systems:

1. Using the potential of dry winter air for ventilation dehumidification reduces energy consumption by 30–50% during the cold season.
2. Correct calculation of peak summer loads, accounting for all moisture sources and a 15–25% capacity margin, ensures stable parameters in summer.
3. Implementing adaptive control algorithms for transitional seasons allows for optimised energy consumption and prevents condensation.
4. Integration of heat recovery systems increases the efficiency of ventilation dehumidification in winter.
5. Mandatory calculation of the energy balance for different seasons at the design stage reveals optimal operating modes.

Investment in seasonal optimisation of humidity control systems pays back within 1–3 years and delivers a 25–45% reduction in operating costs over the entire service life, while improving reliability and stability of indoor climate control.