{"id":5519,"date":"2026-10-27T10:51:26","date_gmt":"2026-10-27T09:51:26","guid":{"rendered":"https:\/\/ghetool.eu\/?post_type=course&#038;p=5519"},"modified":"2026-10-27T10:51:27","modified_gmt":"2026-10-27T09:51:27","slug":"optimiser-le-systeme-hybride-pour-obtenir-un-rendement-energetique-maximal","status":"publish","type":"course","link":"https:\/\/ghetool.eu\/fr_fr\/course\/optimise-hybrid-system-for-maximum-energy\/","title":{"rendered":"Optimiser le syst\u00e8me hybride pour un rendement \u00e9nerg\u00e9tique maximal"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In the previous chapter, the algorithm to optimise a hybrid geothermal system for the maximum geothermal power share was discussed. The main benefit of this approach was that it avoided any oversizing of the entire hybrid system, but the downside was that it left some geothermal potential for energy behind. This is exactly what can be solved by using an optimisation strategy for the maximum geothermal energy share.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n<iframe title=\"Chapitre 9.3 : Optimiser l&amp;apos;\u00e9nergie\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/C0Gb5T_DvHk?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n\n\n\n\n\n\n\n<h2 class=\"wp-block-heading\">Hybrid system optimised for energy<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">When the borefield is optimised for maximum geothermal energy, the design objective is the following:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>Maximise the heating, cooling and\/or domestic hot water demand so that the energy you inject into and extract from the ground over the entire simulation period is maximised.<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">The design philosophy of the methodology above comes down to reducing all geothermal potential for energy until there is no geothermal potential left. This can be seen in the temperature profile below.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1420\" height=\"500\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1.png\" alt=\"Example of an temperature profile optimised for the maximum geothermal energy.\" class=\"wp-image-5521\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1.png 1420w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1-18x6.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1-300x106.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1-767x270.png 767w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-optimise-energy-1-1024x361.png 1024w\" sizes=\"(max-width: 1420px) 100vw, 1420px\" \/><figcaption class=\"wp-element-caption\">Example of an temperature profile optimised for the maximum geothermal energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">In contrast, however, to the method to maximise the geothermal power, this optimisation strategy does not guarantee that the resulting power, which gives you the highest energy exchange over the whole simulation period, can always be used during that same simulation period. In other words, when the algorithm gives back x kW of required power, it is certain that this leads to the highest energy exchange over the entire simulation period, but it does not mean that one can have this x kW at all times during the simulation period.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This implies that, in the design of the hybrid technologies, this should be accounted for. In the end, the cumulative installed power will be greater than in the case of the optimisation for power, because here the geothermal power cannot be guaranteed at all times.<\/p>\n\n\n\n<div class=\"note\">It is important to note that oversizing is not by definition a problem. In some larger systems, designers even often go for a certain percentage of oversizing (or put, for example, heat pumps in cascade), so that it is easier to maintain them and it also gives more security of supply if something goes wrong with one machine.<\/div>\n\n\n\n<p class=\"wp-block-paragraph\">In the section below, the algorithm for optimising the energy exchange will be explained.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Optimisation algorithm<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Since the design of hybrid geothermal systems is not trivial and can sometimes give surprising results, it is important to understand the underlying optimisation algorithm in depth. The algorithmic reasoning is explained below.<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Start with an hourly heating, cooling (and optionally domestic hot water) demand profile and a certain fixed borefield design.<\/li>\n\n\n\n<li>Iterate through each hour (i) of the simulation period, performing the following steps:\n<ol class=\"wp-block-list\">\n<li>Calculate the fluid temperature at time (i), using all the previous loads and assuming the building energy demand at time (i) is delivered by the borefield.<\/li>\n\n\n\n<li>Check whether:\n<ol class=\"wp-block-list\">\n<li>The minimum fluid temperature at the current hour is below the set threshold.<br>If it is, the extraction power is too high, so it should be reduced by limiting either the heating or the domestic hot water demand. Depending on which one you want to reduce first, the heating or the domestic hot water demand will be reduced by x% for the current hour.<br>If the fluid temperature is above the threshold, the current heating and domestic hot water demand can be provided by the geothermal borefield.<\/li>\n\n\n\n<li>The maximum fluid temperature at the current hour is higher than the set threshold.<br>If it is, the injection power is too high, meaning that the cooling power should be reduced by x% for the current hour.<br>If the fluid temperature is below the threshold, the borefield can handle the injection, and no changes are necessary.<\/li>\n<\/ol>\n<\/li>\n\n\n\n<li>If the fluid temperature is within the limits, the power for the geothermal system is set, and the remaining power that cannot be delivered by the borefield at the current hour must be supplied by the hybrid solution. Proceed to step (2.5).<\/li>\n\n\n\n<li>If the fluid temperature is outside the limits, adjust the hourly load to align with the new peak powers determined in step (2.2) and go back to step (2.1).<\/li>\n\n\n\n<li>Once the fluid temperature at time (i) is acceptable, move to the next hour.<\/li>\n<\/ol>\n<\/li>\n\n\n\n<li>Done.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">In the algorithm above, the major difference from the previous algorithm (see <a href=\"https:\/\/ghetool.eu\/course\/optimise-hybrid-system-for-maximum-power\">Part 9.2<\/a>) is that here the peak power for heating, cooling and domestic hot water is reduced for<strong> each hour individually<\/strong>, whereas in the optimisation for power it is reduced for <strong>the entire simulation period<\/strong>. Therefore, it is possible that in this case the available power for heating, cooling or domestic hot water will change. This is shown in the graph below.<\/p>\n\n\n\n<div class=\"advanced\">In reality, the algorithm does not literally iterate through every hour, but it always simulates a certain window (for example, 1000 hours). This is because at many hours in the simulation period, especially in the mid-seasons, 100% of the building load can be provided by the borefield. In that case, the load is not changed and no recalculation is required. By working with a simulation window, one avoids too much recalculation and speeds up the algorithm.<\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"836\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph.png\" alt=\"Geothermal contribution graph for an hybrid system optimised for energy.\" class=\"wp-image-5522\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph.png 836w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-300x144.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-18x9.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-767x367.png 767w\" sizes=\"(max-width: 836px) 100vw, 836px\" \/><figcaption class=\"wp-element-caption\">Geothermal contribution graph for an hybrid system optimised for energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">The geothermal contribution graph above is for the optimise for energy method what the load-duration curve is for the optimise for power algorithm. Here, in every year of the simulation period, the available geothermal power (and corresponding energy exchange) can change due to the imbalance of the system. Looking at the temperature profile earlier, a clearly extraction-dominated system was visible, where the extraction power (heating and domestic hot water) reduces over the years and the cooling increases.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is exactly what is visible in a graph like the one above: over the years, the heating power as well as the baseload heating goes down, together with the energy demand, whereas the cooling power goes up.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Example in GHEtool<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In order to illustrate the advantages and disadvantages of this method when compared to the optimisation for power approach, the same example as in the previous chapter is discussed. To start, the same 5&#215;5 borefield with a drilling depth of 100 m is considered. The geothermal share of the hybrid geothermal system is shown below.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"708\" height=\"319\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-5x5-1.png\" alt=\"Geothermal share for a hybrid system optimised for energy and a borefield of 5x5 boreholes.\" class=\"wp-image-5523\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-5x5-1.png 708w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-5x5-1-18x8.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-5x5-1-300x135.png 300w\" sizes=\"(max-width: 708px) 100vw, 708px\" \/><figcaption class=\"wp-element-caption\">Geothermal share for a hybrid system optimised for energy and a borefield of 5&#215;5 boreholes.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">The first thing that one can notice is that the same borefield that, in the previous chapter, could only deliver 89.5% of the heating demand and 97% of the cooling demand can now deliver 99% in heating and 99.9% in cooling, but in order to achieve this, one needs to install 48 kW instead of 25 kW and 97 kW instead of 54 kW, respectively.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The first thing that one can notice is that the same borefield that, in the previous chapter, could only deliver 89.5% of the heating demand and 97% of the cooling demand can now deliver 99% in heating and 99.9% in cooling, but in order to achieve this, one needs to install 48 kW instead of 25 kW and 97 kW instead of 54 kW, respectively.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"836\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contributino-graph-5x5-1.png\" alt=\"Geothermal contribution graph for a borefield of 5x5 boreholes optimised for energy.\" class=\"wp-image-5525\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contributino-graph-5x5-1.png 836w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contributino-graph-5x5-1-18x9.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contributino-graph-5x5-1-300x144.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contributino-graph-5x5-1-767x367.png 767w\" sizes=\"(max-width: 836px) 100vw, 836px\" \/><figcaption class=\"wp-element-caption\">Geothermal contribution graph for a borefield of 5&#215;5 boreholes optimised for energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">In the graph above, it is clear that in the first 1-3 years, the geothermal cooling power increases significantly due to the imbalance on the borefield and the lower and lower fluid temperatures over these first 3 years. From 3 years onward, the peak cooling stays the same and the maximum fluid temperature limit is also no longer met. After approximately 15 years, when the minimum fluid temperature limit is reached, the available power in heating reduces as well. It is due to the initially lower geothermal cooling potential, as well as the lower geothermal heating potential after 20-25 years, that the hybrid system should be designed larger to account for this.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"744\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-5x5-2.png\" alt=\"\" class=\"wp-image-5526\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-5x5-2.png 744w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-5x5-2-300x161.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-5x5-2-18x10.png 18w\" sizes=\"(max-width: 744px) 100vw, 744px\" \/><figcaption class=\"wp-element-caption\">Temperature profile for a borefield of 5&#215;5 boreholes optimised for energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">When the borefield is reduced to a 4&#215;5 case, the geothermal contribution can be seen below.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"714\" height=\"315\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x5-1.png\" alt=\"Geothermal share for a hybrid system optimised for energy and a borefield of 4x5 boreholes.\" class=\"wp-image-5527\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x5-1.png 714w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x5-1-18x8.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x5-1-300x132.png 300w\" sizes=\"(max-width: 714px) 100vw, 714px\" \/><figcaption class=\"wp-element-caption\">Geothermal share for a hybrid system optimised for energy and a borefield of 4&#215;5 boreholes.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">Again, just as in the case of the optimisation for power, reducing the borefield size reduces the geothermal share. This time, the remaining geothermal share is 91.8% in heating and 99.9% in cooling, significantly higher than the 73% and 92% for the optimisation for power, but again at the cost of a larger cumulative installed power.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Reducing the borefield further to a 4&#215;4 borefield results in the following geothermal share.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"706\" height=\"313\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x4-2.png\" alt=\"Geothermal share for a hybrid system optimised for energy and a borefield of 4x4 boreholes.\" class=\"wp-image-5528\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x4-2.png 706w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x4-2-300x133.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-share-4x4-2-18x8.png 18w\" sizes=\"(max-width: 706px) 100vw, 706px\" \/><figcaption class=\"wp-element-caption\">Geothermal share for a hybrid system optimised for energy and a borefield of 4&#215;4 boreholes.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">For this smaller borefield, the geothermal heating share stays above 80%, whereas it was 57% in the case of the optimisation for power. In contrast, however, to the previous chapter, there is already a very small part of the domestic hot water demand that can no longer be provided by the borefield. This is because the optimise for energy method allows for a larger imbalance (74 MWh\/year compared to 61 MWh\/year), so the fluid temperatures are also lower in the last year, making it impossible to stay within the limits by only reducing the heating demand. The temperature profile now looks like this.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"744\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-4x4-1.png\" alt=\"Temperature profile for a 4x4 borefield optimised for energy.\" class=\"wp-image-5529\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-4x4-1.png 744w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-4x4-1-18x10.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-4x4-1-300x161.png 300w\" sizes=\"(max-width: 744px) 100vw, 744px\" \/><figcaption class=\"wp-element-caption\">Temperature profile for a 4&#215;4 borefield optimised for energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">With this temperature profile in mind, the geothermal contribution graph below makes sense. Due to the significant imbalance, the heating power reduces from 48 kW in the first year to 32 kW in the last year. Meanwhile, the cooling increases from 60 kW in the first year to 97 kW from year 11 onwards.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"836\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-1.png\" alt=\"Geothermal contribution graph for a borefield of 4x4 boreholes optimised for energy.\" class=\"wp-image-5530\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-1.png 836w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-1-300x144.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-1-18x9.png 18w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-1-767x367.png 767w\" sizes=\"(max-width: 836px) 100vw, 836px\" \/><figcaption class=\"wp-element-caption\">Geothermal contribution graph for a borefield of 4&#215;4 boreholes optimised for energy.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">One way to look at the difference between the optimise for power and optimise for energy methods is that these are just two different viewpoints on the same problem, two edge cases, so to speak, and that in reality the optimal solution will be somewhere in between. For example, the optimise for power case of the 4&#215;4 borefield yielded a maximum geothermal power of 13 kW with a yearly heating load of 53 MWh. If we run the same simulation with the optimise for energy method and we limit the peak heating to 13 kW, the following temperature profile is obtained.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"744\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-limit.png\" alt=\"Temperature profile for a 4x4 borefield optimised for energy with a maximum geothermal heating power of 13 kW.\" class=\"wp-image-5531\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-limit.png 744w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-limit-300x161.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Temperature-profile-limit-18x10.png 18w\" sizes=\"(max-width: 744px) 100vw, 744px\" \/><figcaption class=\"wp-element-caption\">Temperature profile for a 4&#215;4 borefield optimised for energy with a maximum geothermal heating power of 13 kW.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">Since in the simulation above only the heating was limited to the solution of the optimise for power case, the fluid temperatures still reach the maximum limit, whereas the minimum temperature does not. This means that, when compared to the optimise for power case, more heat injection takes place in this scenario, reducing the imbalance from 61 MWh\/year to 59 MWh\/year, and the same 13 kW of heating can deliver 55 MWh\/year on average in this case because of the higher injection load.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The corresponding geothermal contribution graph is shown below.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"836\" height=\"400\" src=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-limit.png\" alt=\"Geothermal contribution graph for a borefield of 4x4 boreholes optimised for energy with a limit of 13 kW in heating.\" class=\"wp-image-5532\" srcset=\"https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-limit.png 836w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-limit-300x144.png 300w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-limit-767x367.png 767w, https:\/\/ghetool.eu\/wp-content\/uploads\/2026\/10\/Geothermal-contribution-graph-4x4-limit-18x9.png 18w\" sizes=\"(max-width: 836px) 100vw, 836px\" \/><figcaption class=\"wp-element-caption\">Geothermal contribution graph for a borefield of 4&#215;4 boreholes optimised for energy with a limit of 13 kW in heating.<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">In the temperature profile above, the heating and domestic hot water loads (i.e. all extraction loads) are constant over the simulation period, indicating that there is no oversizing anymore in heating. In cooling, the load increases year after year due to the imbalance of the system.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This imbalance, which is present in both the energy and power optimisation, can still be very pronounced and can raise questions about the durability of a design like this. What happens after 40 years? Therefore, the next chapter discusses the last optimisation algorithm: optimise for balance.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">This chapter introduced the second methodology to design a hybrid geothermal system, namely one for maximum geothermal energy. By reducing the maximum peak power in heating, domestic hot water and\/or cooling in every hour of the simulation period, a load profile can be obtained such that the resulting temperature profile always stays within the temperature limits and meanwhile exchanges the maximum amount of energy with the ground, however at the cost of oversizing the entire hybrid system.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the example, it was shown that geothermal shares in heating of 80% can be obtained, whereas the same borefield with an optimisation for power only gave a geothermal energy share in heating of 57%. Using the functionality to limit the geothermal power, the oversizing can be controlled in order to find the sweet spot between both methods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, both the optimise for energy and the optimise for power methods still have a significant imbalance. In the <a href=\"https:\/\/ghetool.eu\/course\/optimise-hybrid-system-for-maximum-energy\/\">next chapter<\/a>, the optimise for balance method will overcome this.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">References<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Peere, W. (2025). Three ways to design a hybrid geothermal heating and cooling system for an office building. In <em>Proceedings of Geo-Rin Conference<\/em>. Benasque (Spain), 2-6 June 2025. [<a href=\"https:\/\/dialnet.unirioja.es\/servlet\/articulo?codigo=10467989\" target=\"_blank\" rel=\"noopener\">online<\/a>] <\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Questions<\/h2>\n\n\n\n<div class=\"question\" data-chapter=\"3\">How would you control such a hybrid system in practice?<\/div>\n\n\n\n<div class=\"question\" data-chapter=\"3\">In the first geothermal contribution graph in this chapter, the baseload in domestic hot water goes down, but the peak power stays the same. How is that possible?<\/div>\n\n\n\n<div class=\"question\" data-chapter=\"3\">For the 5&#215;5 borefield, a cumulative installed power of 75 kW was required to deliver the required heating load. However, when looking at the geothermal contribution graph, the geothermal peak power never goes below 45 kW. Since the heating demand is maximum 50 kW, why is the required hybrid power 25 kW?<\/div>\n\n\n\n<div class=\"question\" data-chapter=\"3\">How do the results of an optimisation for energy and an optimisation for power differ when the limits in heating, cooling and domestic hot water are set identical to the results of the optimisation for power?<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Downloads<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Download GHEtool simulation from this chapter <a href=\"https:\/\/ghetool.eu\/wp-content\/uploads\/course\/resources\/Course%209.3\/Course%209.3.pdf\">here<\/a>.<\/li>\n\n\n\n<li>Download the CSV file of the load <a href=\"https:\/\/ghetool.eu\/wp-content\/uploads\/course\/resources\/course%209.2\/Residential.csv\">here<\/a>.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dans ce chapitre, nous expliquons la m\u00e9thodologie permettant de concevoir un syst\u00e8me hybride optimis\u00e9 pour maximiser les \u00e9changes d'\u00e9nergie g\u00e9othermique.<\/p>","protected":false},"template":"","section":[124],"chapter":[150],"authors":[39],"class_list":["post-5519","course","type-course","status-publish","hentry","section-chapter-3","chapter-part-9","authors-wouter-peere"],"_links":{"self":[{"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/course\/5519","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/course"}],"about":[{"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/types\/course"}],"wp:attachment":[{"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/media?parent=5519"}],"wp:term":[{"taxonomy":"section","embeddable":true,"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/section?post=5519"},{"taxonomy":"chapter","embeddable":true,"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/chapter?post=5519"},{"taxonomy":"authors","embeddable":true,"href":"https:\/\/ghetool.eu\/fr_fr\/wp-json\/wp\/v2\/authors?post=5519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}