Predictive Control: 8 Optimizations in HVAC and Refrigeration

Whether you are a manager of industrial or commercial buildings, you are now facing a major economic challenge: controlling energy costs despite a significant increase in prices. One can argue that if you had access to technology that could reduce costs while maintaining the efficiency of your heating and refrigeration equipment, with a return on investment of less than a year, it would arouse your interest. 

For all large buildings with high heating and/or refrigeration consumption, the question remains the same: how can we optimize energy management without compromising productivity? 

This is where BeeBryte comes in. As experts in energy optimization of heating and refrigeration systems, we offer an equipment control solution that not only reduces your energy costs but also ensures optimal operation of your facilities. 

This is not done by magic; this article gives you in detail the optimization techniques that can be implemented via our reactive control service. 

  

The following points will be discussed: 

1) The comparison between reactive and predictive optimization 

2) The types of energy optimization 

3) The benefits of predictive and automatic control  

 

 

There are two main categories of optimization: 

Reactive optimization consists of monitoring and reacting to variations in equipment behavior. For example, you can adapt the ventilation speed of a refrigerant according to the temperature difference between air and refrigerant. 

Predictive optimization, as the name suggests, relies on prediction and anticipation rather than simple reaction. It is based on more sophisticated computing capabilities: it uses models calculated from data collected on equipment, allowing an optimal management scenario to be determined. 

This method also takes into account external factors: weather forecasts, variable energy rates (e.g. peak and off-peak hours) or the production of electricity from solar panels to improve self-consumption. 

 

Let’s take a concrete example of predictive optimization: 

Take a large commercial complex, which would be equipped with our pilotage service. Our technology continuously analyzes weather data and updates energy rates. 

Suppose a heatwave is expected the next day. In anticipation, the system adjusts the settings of the air conditioning system during off-peak hours of the night, when energy is cheaper, and the efficiency of the air conditioning system is better. 

Thus, the building is pre-cooled at a lower cost before full hours and maximum temperatures arrive, ensuring comfort and energy savings throughout the day. 

 

2) The types of energy optimization: 

1) Dynamic control of chillers 

Our approach to the control of a chillers’ groups involves finely regulating the operational power of each group within the refrigeration system. The main objective is to maintain the relative energy efficiency (EER) or the coefficient of performance (COP) at its optimal level for the entire refrigeration system. 

In practice, this involves precisely controlling the cooling sequences—“chillers”—adapted to the specific thermal needs of the site, often used for areas requiring rigorous temperature control, such as refrigerated cells. 

This regulation is crucial for the proper maintenance of temperatures, especially in large-scale infrastructures such as warehouses or large commercial complexes, where thermal stability is essential for the storage and preservation of products. This proactive adjustment helps to significantly reduce energy costs. 

  

2) HVAC and refrigeration equipment set temperature “fine” 

We use a fine setting of the set temperature of HVAC-R equipment, adapting the temperature according to the weather forecast, the exact arrangement of the transmitters in the building, and a business model to anticipate the receipt and shipment of commodities. 

Our control service analyzes the weather conditions and the internal temperature to automatically adjust the set temperature for each zone, taking into account its position in space and its impact on the temperature maintenance. 

This precise control minimizes energy consumption while maintaining a uniform temperature throughout the site, thus contributing to the maintenance in operational conditions of equipment that operates only at the required level and not excessively. 

Graph: temperature changes before predictive control: higher than median (4) 

Graph: temperature changes with predictive control: more adjusted and stable compared to the median (4) 

 

3) Optimized heat recovery management 

Here, it is about precisely adjusting the high pressure (HP) according to the actual heat recovery needs, thus avoiding any waste of energy and unnecessary overproduction. 

How does it work? We set up a prediction model that estimates heating needs. This model helps us to define the ideal high pressure for each situation, allowing heat recovery to be optimized without wasting energy. 

Secondly, we adjust the high pressure in real time by continuously analyzing the heating needs. This dynamic approach allows us to optimize the heat recovery process as needs change, resulting in tangible energy savings. 

  

4) Floating high pressure (HP) and low pressure (LP) adjustment 

The purpose of adjusting high pressure and low floating pressure is to balance cooling performance with energy consumption. For example, for high pressure, we model the consumption of compressors and condensers according to external parameters (weather, cold load, etc.) and determine the optimal setpoint that minimizes the consumption of the whole. 

Our optimization process requires real-time temperature and load level data from the system to optimize high pressure. At the same time, the low pressure is adjusted according to the needs of the emitters. 

Our service involves monitoring the outside temperature but also a constantly evaluating each compressor’s load and condenser capacity. 

Compressor unit—condenser: a set of components for compressing and cooling the refrigerant, performing heat exchange, and promoting the cooling of the indoor unit. 

In addition, we have developed a predictive algorithm that takes into account the potential variations caused by the operational conditions of the building and the weather variations. This method allows us to make continuous adjustments to high and low pressure. 

  

5) Modulation of transmitters 

“Emitters” refers to devices that release heat or cold into the environment, such as air conditioning units, radiators, fan coils, etc. These emitters are often controlled by building technical management system (BMS) to maintain the target temperature of an area. 

Our optimization aims to precisely maintain the targeted temperature taking into account weather variations and internal activity. Our teams ensure, through our control system, a continuous adaptation of the status of each transmitter to meet the cooling or heating needs of the area. This method allows optimal adjustment of the ON/OFF operation of each transmitter. 

  

6) Optimization of ventilation 

Ventilation optimizations take two forms: 

–  Advanced control 

Continuously monitoring the condition of the valve and the internal temperature, we intelligently adjust the shutdown of a fan to use the thermal inertia still present in the exchanger to continue the diffusion of cold while preventing excessive ice formation on the latter. This proactive approach not only extends the life of the hardware, but also reduces associated maintenance costs. 

 

–  Adaptive management 

This approach involves precisely adjusting the ventilation speed according to current and anticipated cooling needs, while taking into account variations in activity and weather conditions. For example, during periods of low activity or cooler temperatures, fans can operate at a reduced speed while maintaining adequate thermal comfort. 

  

7) Defrost optimization 

Our defrosting optimization involves the intelligent management of defrosting cycles for cold emitters. We continuously monitor the operating time of these transmitters as well as the actual conditions that can lead to ice formation. Based on these observations, our system precisely adjusts the frequency and duration of defrost cycles. 

We are also able to select the most suitable type of defrosting (natural or by heat input) to optimize the use of energy. 

By eliminating unnecessary defrosting cycles, our system ensures that transmitters remain efficient longer and that cooling remains possible when necessary. 

  

8) Demand response and flexibility  

Demand response is a financially rewarded technique which consists of voluntarily reducing the electricity consumption of a building during periods when the demand for energy is very high and prices are, therefore, also higher. 

The goal, beyond acquiring additional income, is to reduce energy costs and help stabilize the electricity grid by avoiding peaks in consumption. 

Refrigeration systems typically supply cold to buildings that have a thermal inertia, i.e. the temperature will increase slowly when the cold supply is shut down for a short period of time. This phenomenon is what we call flexibility, the ability to shift consumption in time without having to harm the operational temperature constraints of the site.

Although the flexibility physically always comes to storing cold in the building during one period to use less cold production during another period, the flexibility of a building can be financially optimized in two different ways depending on how this flexibility is financially valorised:

 

1. Implicit flexibility

When a building has an electricity contract with a certain degree of variability, e.g. a difference between day and night tariffs, our optimization will be able to optimally exploit the electricity price spread. The consumption will be shifted towards periods of low price to reduce the consumption during high price time frames. Nevertheless, to be profitable the overconsumption generated by this optimization must be financially cancelled by the price differences. Our machine learning model predictive control optimization can optimally exploit this implicit flexibility.

2. Explicit flexibility

Demand response mechanisms allow to sell electrical flexibility on energy markets. The electricity system operator will then use this electrical flexibility to balance our grid and to reduce peak demand during the coldest winter days. When prices on these markets spikes, a demand response service can generate a substantial supplementary remuneration next to our “classic” energy efficiency savings.

 

Good to know:  We offer a tailor-made optimization service which adapts to the size of your site and the type of equipment you have. It is “erase ready.” 

  

3) The benefits of predictive and automatic control 

–  Energy savings  

Our teams of engineers and thermal engineers have developed a “predictive” control service for heating, ventilation, air conditioning and refrigeration (HVAC-R) systems. What is the role and importance of prediction? 

Thanks to our service, temperature and energy adjustments no longer follow only fixed and programmed formulas; they are anticipated and adapted according to needs, with a finesse that takes into account the rhythm of life in the buildings they serve (ex: absence of people early in the morning or late in the evening, etc.), but also weather conditions. 

Behind this service are experts in thermal, data, IT and engineering who work to constantly refine their algorithms, based on real data and continuous feedback, to better adapt and react to the needs of users. This allows substantial energy savings (up to 40%) while improving occupant comfort and minimizing environmental impact. 

  

–  Augmented Intelligence  

In this way, we are adding a smart overlay to the controllers, thermal equipment and the BMS without impacting facilities or on-site operations. 

Data from your equipment that is useful for our optimization processes is stored in our cloud. Then the predictive management service can easily anticipate the internal and external activities of your site. 

–  Internally, we monitor equipment operation and human activity. This includes, for example, motion detection, entry and exit, opening and closing doors, etc. 

–  For external activities, this concerns the constant evolution of weather conditions and the real-time evolution of energy rates. 

This anticipation of which we are capable is a complex task that requires speed and precision that only our algorithms and our system can guarantee. 

  

–  Equipment interconnection  

Site equipment often communicates via a variety of protocols. Our predictive management service plays a crucial role in linking these devices to facilitate and optimize their collective operation. 

To ensure efficient interconnection, our engineering team conducts detailed analysis and comprehensive data collection. The goal is to gain an in-depth understanding of each piece of equipment and the way it operates and interacts on site, without altering or disrupting existing facilities. 

This analysis allows us to create a consistent and comprehensive overview of site operations, providing a perspective that site managers may not have without this integration. This initial optimization step is essential to ensure that all equipment works in a synchronized and efficient manner. 

  

–  24/7 dynamic equipment control  

Our intelligent control service offers precise and dynamic control of HVAC-R equipment, operating 24/7. It integrates perfectly with existing technical building management systems and can be deployed without major disruption. 

It offers a full range of features: visualization, forecasting, analysis, diagnosis, and above all, intelligent automatic control of equipment. In other words, you have everything you need for efficient and optimized energy management right at your fingertips. 

Important: Our control does not exclude your control; the service can be deactivated with a simple turn of a key if necessary. 

  

–  No replacement or modification of existing equipment  

Our predictive control service is designed to seamlessly integrate with your existing HVAC-R equipment. This integration is done without requiring replacement or modification, thus avoiding additional costs related to the acquisition of new equipment. 

 

Conclusion

The integration of our control service can significantly enhance the energy management of industrial and commercial buildings.

Our service seamlessly integrates with existing HVAC-R systems, optimizing their energy efficiency without requiring costly replacements or modifications.

We utilize data collected in advance and in real-time from your equipment, as well as from sensors for weather conditions, for example. This allows us to conduct predictive analyses to adjust equipment operations according to climatic variations, energy price fluctuations, and internal needs.

Every action we take, whether it involves optimizing defrost cycles or adjusting pressures in cooling systems, is designed to improve the energy management of your equipment while meticulously adhering to your guidelines.

In summary, our approach aims to provide smarter and more efficient energy management by continuously adapting systems to dynamic conditions. This benefits both the environment and the economic performance of your systems.

 

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