Simulating hybrid systems with GHEtool

Up until now, GHEtool offered the possibility to optimise hybrid systems, but today we are introducing a whole new simulation module. With both simulation and optimisation now available, you have the complete toolbox at your disposal to design better, more efficient hybrid geothermal systems.

What you need to know about hybrid systems

We’ve already written quite a few articles on the optimisation of hybrid systems. In a first article, we introduced the concept of hybrid systems and geothermal potential. Hybrid systems were defined as the combination of different heating and cooling technologies that together meet the building’s thermal demand. This can be a ground-source heat pump (GSHP) combined with an air-source heat pump (ASHP), a dry cooler with a GSHP, and so on.

Sizing a hybrid system is not trivial—let alone a hybrid geothermal system. That’s why, in a second article, we introduced two design methodologies to help with this: optimising for power and optimising for energy. The first approach results in a system with the lowest investment cost (due to 0% oversizing), but some geothermal potential remains unused. If you instead optimise the system for maximum energy exchange, you deliberately oversize the GSHP to exchange more energy with the ground, which reduces operational costs. An example of this was covered in a third article.

A further innovation came with the introduction of a more generalised approach: optimising for balance, as discussed in our fourth article. Here, you can ensure that the distribution between geothermal energy/power and the auxiliary systems is done in such a way that only a certain, controlled imbalance remains.

Together, these three methodologies form a powerful toolkit for finding optimal solutions. However, they still lacked one key element: the flexibility to implement your own control strategy.

Simulating hybrid systems

The difference between optimisation and simulation

All the methods currently available in GHEtool Cloud are optimisation methods. This means that, given certain boundary conditions—like a fixed borefield size and an hourly thermal demand—you maximise the geothermal share by optimising for either power, energy, or balance. This process can be somewhat slow, as it may require numerous iterations, which is exactly where the flexibility of simulation comes in.

When simulating a hybrid system, you still start with the same known conditions (your borefield size and hourly thermal demand), but now you also define the control strategy of your hybrid system. That is, at which threshold temperature does a certain technology switch on or off? With this strategy and a given weather file, the geothermal demand can be calculated directly based on the control logic—removing the need for iteration. This makes simulations significantly faster. However, the trade-off is that you’re not necessarily working with the optimal solution.

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If you use the optimisation methods, a control strategy is implied. Since you want your fluid temperatures to stay within certain limits, the optimisation algorithm will adapt the load accordingly to meet this requirement. Although this control strategy could be replicated in reality by using a controller setpoint based on the temperature of the geothermal fluids, it is not straightforward to do so.

Three examples of simulating hybrid systems

Imagine you have a large commercial building, where part of the load is provided by a GSHP and part by an ASHP. Since you know that when the outside air temperature is above 10 °C, your ASHP has a higher efficiency than your GSHP, it makes sense— from an electricity consumption standpoint— to preferably use the ASHP instead of the GSHP. This can be easily modelled by defining the ASHP as a hybrid heating technology that works above a threshold temperature.

Another situation can occur, for example, in a renovation context. Imagine you have a (not-so-well-insulated) school building with high-temperature emission systems fed by a gas boiler. In autumn and spring, the GSHP can heat this building perfectly, but when it gets too cold outside, the gas boiler turns on to provide the required higher temperatures. This can be modelled by using a hybrid heating system that works below a temperature threshold.

A final example could be an office building, where the air handling unit (AHU) has difficulty cooling the air using the passive temperatures from the borefield when it is too hot outside. One solution could be to equip the AHU with an active component that kicks in to provide hybrid cooling above a certain temperature threshold.

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There is also a fourth option, where a hybrid system provides cooling when the outside air temperature drops below a certain level. This could, for example, be night ventilation cooling. Since this is not really a ‘system’, this option—although present in GHEtool—will not be discussed further.

In what follows, we will discuss how you can use GHEtool Cloud to simulate these systems.

Simulating hybrid systems with GHEtool Cloud

Within GHEtool, you now have the option (when you have uploaded an hourly load profile) to add a hybrid system when calculating the temperature profile. A screenshot of the input section is shown below.

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Since simulation, as discussed above, is not an iterative process, it is also possible to add a hybrid system when calculating the required borehole depth.

First of all, since these hybrid system simulations are all based on a threshold for the outside air temperature, an EPW weather file is required. Ideally, the same weather file used for the calculation of the hourly load is also used for the simulation, so that the peak thermal demands coincide with the correct weather information.

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When searching for weather files, https://climate.onebuilding.org/ provides free EPW files for almost all regions in the world for different years.

Next, you have the option to add up to four different hybrid systems, each with its own temperature threshold above or below which the respective hybrid system will be preferred for heating or cooling. For each hybrid heating/cooling option, you can also specify the power of that hybrid system.

Note!
Although there are four separate inputs for hybrid systems, this does not necessarily mean that four different systems must be modelled. It is perfectly possible to model a single ASHP that provides both heating above a certain threshold and cooling above a certain threshold.

Example with hybrid heating

The graph below shows the energy distribution for a situation where there is a hybrid heating system that provides 100 kW of heating when the outside temperature drops below 2 °C. As can be seen in the figure, this only occurs (for this weather file) in January, February, and December. In the other months, the effect is negligible.

When another hybrid system is added, providing 200 kW and operating when the outside temperature is above 10 °C, the profile looks like the one below. Here, you can see that the share of geothermal heating is significantly lower, which leads to a different imbalance and, consequently, a different resulting temperature profile.

Limiting the borefield power

As a final option, it is also possible to limit the maximum geothermal power. Imagine, for example, that you have a heating demand of 536 kW and an ASHP already installed to provide some extra cooling in summer. You could then limit the peak power of the GSHP to, for example, 475 kW. This means that in your results, there will now be ‘excess heating’, since 100% of the heating load could not be fulfilled by the GSHP.

In reality, however, your ASHP could take on this part of the load, giving you yet another way to design and simulate hybrid systems. An example is shown below, where around 1.3% of the yearly heating demand is now marked as ‘excess heating’.

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The new module for simulating hybrid systems is a perfect addition to the optimisation methods that were already available. Although it does not guarantee the best solution, it provides a very straightforward way of simulating the behaviour of hybrid systems in real life.

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