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11 International Conference on Sustainable Energy technologies (SET-2012) September 2-5, 2012 Vancouver, Canada
DOMESTIC SOLAR EARTH CHARGING: MODELLING THE PROCESS FOR AUGMENTATION OF HEAT PUMP Architect David Nicholson-Cole with the support of Professor S. Riffat. Department of Architecture and Built Environment, University of Nottingham Email: david.nicholson-cole@nottingham.ac.uk
ABSTRACT This paper is a progress update on the solar thermal augmentation system for ground source heat pumps using solarium style panels to recharge the ground, previously reported at SET 2011. The system is running on a house in Nottingham, England. The house has a 4kW photovoltaic array and a ground source heat pump for heating and hot water, using twin 48 metre boreholes. Real-time, diurnial and inter-seasonal solar charging restores the energy level in the earth, thus preventing progressive chilling of the borehole zone. The first development in 2012 is that there is now sufficient real data collected to construct a computer simulation with that data, to see how it compares with the real pattern of behaviour. The modelling process attempts to identify the thermal elasticity of the borehole. The second development in 2012 has been the addition of an additional method of solar capture, vacuum tubes working to the same boreholes, with independent controls, pumping and metering. The solar collection systems provide a way of comparing the cost effectiveness, technical and visual impact of the technologies. Solar augmentation can improve the GSHP performance by a significant percentage, more than the 15% expected – it has been more like 40%, causing one to detect an accelerative effect with solar charging. The resulting economies have been sufficient to reduce the annual electrical consumption for heating and hot water to less than the annual power generated by the PV array on the roof, thus achieving net-zero carbon emission. 1.0 INTRODUCTION Previous papers by the authors in SET 2011 AND CIBSE/ASHRAE 2012 [1] reported on an augmentation system for ground source heat pumps (GSHP) using solarium style panels to recharge the ground, thermally – referred to as the ‘Sunbox’ for the remainder of this paper (in 2010). In addition, in early 2012, the author has added vacuum tubes to the east facing roof, also connected to the ground loop of the heat pump. This installation is domestic scale, fitting a single house as a real-world, real-time, full-scale lived-in experiment. The house construction is a regular British developer house with better than average insulation. The author has used ‘Active house’ [2] concepts to bring the house to Net-Zero – powering ‘up’ by gathering solar electrical energy, and powering ‘down’ by reducing the power consumption of the house and heating. This experiment has shown that PV and Solar augmented GSHP can be effective as a new build or partial retrofit solution. The house is on the gas grid. At the time of house construction in 2006, the justification for a GSHP instead of a gas boiler was that a mono-fuel based system, electricity, is preferable to active burning of fossil fuel sources for six reasons: 1. If we burn fossil fuel or biomass, we cannot avoid emission of CO2, even if we find other ways to offset or compensate. 2. Governments of all hues intend to increase the proportion of renewable electricity by 2020-30, to meet European targets. This will include large scale wind power, but also includes thousands of home generators using photovoltaic panels. [3] 3. The technology of heating with electricity is becoming more efficient with well installed and designed heat pumps which can use renewably sourced electricity to extract heat from a renewable source such as air, ground or water. 4. Individual buildings and groups of buildings can home-generate enough electricity annually to meet their annual electrical requirements for space heating and hot water too, if other conditions are satisfied such as insulation, air tightness and system design. 5. Electricity and thermal flows are capable of being metered precisely, yielding the researcher with definitive proof of the carbon balance. 6. It is a fundamental tenet of renewable energy that the wholesale cost of the fuel, solar energy, is free, even though most of it arrives at times when we do not need it, in summer. We need considerable ingenuity to use this clean energy source successfully, when we need it. Energy Storage is the primary method for this project.
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1.1 Background: The House and Borehole The author’s occupied detached house in Nottingham, England is a 'developer' property built in 2006-7 with brick-block walls, 100mm cavity fill insulation, and 400mm in the roof. Total floor area is 120 square metres (Fig.1). It is not practical to insulate it further, other than hunting down air leakage gaps. It has a Swedish manufactured 2kW/6kW ground source heat pump with an integrated 185 litre water tank (Fig.2). The house has under-floor heating on ground and first floors. The originally estimated total heat and DHW requirement is 14,600 kWh. Prior to this project, the GSHP had an estimated electrical consumption of 5,200 kWh, giving an average COP of 2.5-2.9. Variations are due to weather statistics (degree days) and patterns of occupancy (e.g. visitors). The owners have an ascetic lifestyle. The ground source heat pump was commissioned in March 2007. The thermal source is a twin vertical borehole set, 48m deep in dense clay-marl soil, encompassing approximately 3,600 cubic metres. The surrounding mass is infinite, i.e. there is no insulating envelope. The ground loop is a closed circuit of 40mm plastic pipes. 2 x 45m of which can be considered to be the active length (ignoring the top 3m), and the peak demand on the borehole is 4 kW. This requires the ground to deliver an average of 44 watts/metre, which is safe for the dense damp clay-marl of the site, according to the Veissman Technical Guide. [4]. However, there is always room for improvement in performance.
Figure 1 - Peveril Solar house from the SE, 2012. The solar heat source is combined from Sunbox and vacuum tubes (Photo: author)
Figure 2 – IVT Greenline C6 GSHP including 185L water tank. (Diagram: IVT website)
1.2 Cooling of the ground The author (and house owner) is concerned that over successive years, there is a risk of deep ground cooling, reducing the COP of the GSHP. The theoretical diagram (Fig.3) by Nicholson-Cole and Wood illustrates a gradual decline, with a progressive failure of the ground to recover fully from the heat loss of the previous season, until it reaches a new equilibrium with winter and summer temperatures being lower than in year one – and the heat pump operating more ineffectively than when first installed. Some heat pumps (including this one) have increasingly frequent occasions when the heat pump fails to achieve a satisfactory rate of thermal extraction. This triggers direct 1:1 heating using its ‘Additional Heat’ function. In cold winter periods, this could cause a surge in grid demand when heat pumps (air or ground source) become more commonplace. During the first years of installation (20072009), the heat pump run for 222 hours/annum in ‘additional heat’ mode, equivalent to an additional 900 kWh/annum. Since solar charging was introduced in 2010, it has used none.
Figure 3 – The dark line illustrates declining ground temperatures over several seasons until a low temperature equilibrium is reached. The orange line represents the temperature curve with solar charging (Diagram: author and C. Wood)
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The theoretical shape of the curve is derived by adapting the pattern obtained by frequent measurements of deep ground temperature (Fig. 4). Starting from the end of the Summer, the pattern is of a rapid fall-off once the Winter heating season starts and solar radiation reduces, until a low temperature level is met in February. As the Spring brings warmer daytime weather and reduces the amount of energy withdrawn by the heat pump, the low temperature of the ground experiences a strong delta-T with the infinite surroundings, and external thermal energy is pulled in, elastically. The energy level of the ground recovers slowly because in spring there is still a requirement for evening heating. The curve resembles a long climb-out, drawing energy in from the surroundings until it peaks in late Summer just before the following heating season. The temperature curve below is a record of real temperatures, and has been affected by solar earth charging, so it does not illustrate how the curve would look if there was no charging. It is not possible, with this house, to have the curves for the years 2007, 2008 and first half of 2009, because these were not collected, sadly. In 2012, the author set out to computer model the energy levels in the borehole and establish the curve-shape for the energy level in charged and uncharged boreholes.
Figure 4 - Ground Temperatures from September 2009 to August 2012. For three successive seasons, the summer high has been above 13ÂşC. Twice, the winter low was 5 degrees C higher than when there was no solar charging. (Diagram : author)
ENERGY MODELLING 2.0 The need for a model The solar augmentation project was initially based on a logical hunch, rather than years of preparatory modelling. Based on all of the criteria in 1.0 above, there need be no doubts that an amount of augmentation could have some effect, but there are few precedents to quantify the amount required or the effectiveness. Valuable work has been done in Canada, Italy and Sweden [5],[6], to demonstrate that solar thermal charging of boreholes can improve the performance of ground source heat pumps. These are all for institutions or district heating schemes, and to date, few examples of single houses thus augmented are known. Studies for single dwellings by Trillat-Berdal [6], Chiasson [7] and Elizabeth Kjellson’s PhD [8] have been based on computer models with realistic weather data. In the real world, no heat pump installer or purchaser would be prepared to install a solar augmentation system unless someone else first took the risk of modelling and installing a real-world system to prove that it could work and be reliable. No matter how convincingly a theoretical model is developed on a computer, a real-world working installation would have to follow, to prove that the system can work reliably in real conditions with real plumbers, because a thermal model makes too many simplified assumptions. The operating characteristics and the efficiency of a heat pump are largely determined by the large but low-temperature heat source. The rule of thumb for ground source heat pumps is that the COP is boosted by approximately 3% for each degree (Celsius) that the evaporating temperature is raised, or the condensing temperature is lowered. The SPF (Seasonal Performance Factor) [9] is a way of computing the efficiency over a long period (preferably one typical year), and varies depending on the balance of demand and energy level. If the COP is regularly stimulated by solar gains, then the effect on the SPF over 12 months should be beneficial and quantifiable. Earlier papers from this author about this project 2010, 2011, have reported that solar augmentation has been effective, based primarily on meter readings. For the first 2.5 years of the Peveril house, the ground source heat pump had previously averaged an annual electricity consumption of 5,200 kWh. Following the installation of solar augmentation the GSHP has reduced its
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annual power consumption to less than 3,000 kWh. Other conditions (house size, family size, lifestyle) have remained constant. The installation of a 4kW photovoltaic roof has an effect on the electricity consumption of the house, but has no effect on the consumption of the heat pump which has its own independent meter. It has no effect on thermal performance. The annual power generation of the PV roof averaged 3,300 kWh in its first two years. This was contributing 50/50 to the house and Grid. This exceeds the consumption of the heat pump for heating and hot water, enabling the author to claim that the house is net-zero. It seems from this that the SPF improvement is in the region of 40%. The lowest deep ground temperature at the seasonal nadir of 2010-2011 was 5 degrees C warmer than in 2009-2010, so one would have expected only a 15% improvement. There is evidence of an accelerative effect with solar earth charging which boosts the performance beyond 15%. It seems that temperature is not as significant as energy volume. A dynamic model of the energy flows is the next step. 2.1 Modelling – theoretical dynamic or real-world measured? Earth Energy Designer [10] is a well-known modeller for estimating borehole size. However, this energy storage project requires an analysis of an intermittently and seasonally solar charged heat borehole. There are insufficient reliable yardsticks for theoretical modelling of this particular system. Degree days [11] gives a measure of air temperatures, and records of a typical photovoltaic installation for previous years can give one a sample of ‘Sunniness’. Even with this, there are many many unknowns and variables especially with a deep borehole that one cannot visit, that is infinite in size (un-insulated), that may have a variety of soil layers and conductivities below. The soil in the location of the test house is fairly uniform, consistent clay-marl, according to the report of the drillers in 2006. A real-time real-world rig with data recording over several seasons is a means of testing the idea of solar charging. If it would take 3 years of data to prove it with a real-time model, and if the funding is available, then the best time to start is early. While the system is running, one has the benefit of the 3 years of improved performance and cost savings. As it is a first prototype, it is important to take the installation process slowly so that all the system design aspects of the prototype are resolved without too many diversions, errors or abortive costs. It is important to maintain a diary of the decision making, design and build process. [12] In summer 2009, the author set out to build a full scale system, monitor it for a fair length of time, observing its performance in the varied seasons. With data collected over nearly three years, it is now possible to analyse the readings, and develop a model that illustrates the performance with a performance curve, and estimates the energy levels in the earth. This does not eliminate the role of informed guesswork, but the data used is real, so an authentic pattern has emerged. The primary ‘knowns’ are the metered inputs and outputs. The greatest ‘unknown’ is the rate at which ground naturally replenishes heat energy, following a long winter and spring. The model goes some way to establishing a methodology for discovering how to use this unknown.
Figure 5 – The diagram from the modelling project illustrates energy levels, not temperature. Blue is the energy level without solar charging, and the orange zone represents the effect of charging.
In April 2011, the author attempted a modelling exercise for the project, but was defeated by three things: 1, an insufficient length of time of record keeping to produce worthwhile results; 2, an over complicated approach, in attempting to form a 3 dimensional object representing the borehole in its figure-of-eight shape, to make it animate, and to calculate temperature (not energy level); 3, not sufficiently appreciating how important a thermal model is alongside the real-world system.
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In July 2012, the house was visited by Prof Ala Hasan [13], who encouraged the author to make another attempt. A wholly new start was made, with the intention of achieving a 2 dimensional curve based solely on energy level. 2.2 Modelling – curve shape and energy volume The diagram above (Fig.5) sums up the entire modelling project. The curve shape is similar to the temperature curves shown earlier (Figs. 3 and 4), with the characteristic steep fall-off in early Winter and the long climb-out during Spring and Summer. The model represents energy levels in the borehole, based on data collected from meters at daily intervals over nearly three years. The blips in the curve faithfully illustrate some of the variations in weather that Nottingham has experienced during the past three years. Energy volume is a more valuable entity to model than ground temperature. Temperature varies more frequently depending on thermal capacity and conductivity of the store. During the long summer of solar thermal charging, the ground does not get ‘hot’, it reaches a stable temperature and the volume that exists at that temperature gets larger, until eventually, surplus heat gets lost to the surroundings. In a short heating cycle, the heat pump is boosted by a higher temperature in the source, but over a period of a whole Winter, the more important requirement for the heat pump is the volume of energy available. Starting from a base of 12ºC, A cup of tea at 70°C has less thermal energy than a 300 litre water tank at 18°C. The 3,600 cubic metre underground store at 13.7ºC has vastly more. If the heat pump demands energy, it lowers its ground loop output temperature, thus increasing the delta-T, and thereafter drawing more energy from the larger volume. The temperature immediately around the pump is temporarily lowered, but after a period of rest, the local energy volume will restore the temperature. 2.3 Modelling – choice of software – program or spreadsheet? The software chosen for the modelling was GDL (Geometric Description Language), the parametric programming language of ArchiCAD [14], one of the leading BIM architectural packages (Building Information Modelling). GDL [15] is used by ArchiCAD specialist users for constructing objects, using a scripting language which describes forms, shapes, surfaces, text and more. GDL uses a long established syntax which originated as a form of BASIC in the 1980s, but developed its own culture thereafter. The energy model must be capable of reading in a long data file, storing the numbers into arrays, applying algorithms, and then organising the results into curves and polygons. GDL does not run independently, it has to be used when the environment of ArchiCAD is running. The author is a long established user of GDL, having used and taught it for 14 years. He has written two books [16], which for 1999-2004 were the central teaching resources for GDL, in several languages. Some experts in Excel might be able to perform the same modelling, but for the author, a traditional programming approach comes most easily. The data is first prepared in a spreadsheet, and is then copied and pasted into a datafile that the program can read. The program is capable of building a chart with more options for titling, colour and other qualities than with Excel. With the hindsight from the programming process, a version of the algorithm could be applied in an advanced spreadsheet with resulting charts. The data is already in a spreadsheet, and additional columns could contain formulae to show gradually accumulating energy levels. It would be better to do this for weekly intervals to avoid over loading the spreadsheet or charting routine. The algorithm permits a parametric approach, whereby one can tweak some parameters to compare with known or expected curves, or build in additional parameters such as a percentage for system losses. 2.4 Modelling – data collection The volumes of data collected over three years is enormous, although being collected manually at daily intervals is less voluminous than that from a data logger. The illustrations are small glimpses of the format of the data. Another tabbed page in the spreadsheet reads the meter reading columns and creates a clean spreadsheet purely of the data required for the model. The cleaned up spreadsheet includes columns of commas, so that the entire spreadsheet can be copied as a large text file with tabs and commas, and pasted into a data file that the GDL program can read. The GDL routine that reads in the data ignores the tabs, using only the commas to separate the numbers. The numbers for the dates and meter readings are stored in arrays. With perhaps 330 readings a year, an array of 1000 is enough for 3 years. There need be no practical limit to the array size, It could store data for three years, or twenty years or more than a human lifetime.
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Figure 6 – Metering records: daily meter readings are taken of every significant meter, and weekly readings are also recorded. The modelling program reads the dates and interpolates daily averages.
Figure 8 – GDL file: the columns from the cleaned up spreadsheet are copied and pasted into the GDL data file, as numeric text, with comma separation.
Figure 7 – Preliminary data conversion: the second page of the spreadsheet reads numbers from the metering spreadsheet, and inserts commas between each number.
Figure 9 – GDL script: the arrays are declared, the data file is opened, and the data is streamed into the array and given a variable name, such as ‘gshpmeter[k], daynum[k]’.
2.4 Modelling – inputs and outputs Primarily, this stage of the model only has to know three things per time interval: 1. The electrical energy used by the heat pump, 2. The thermal energy injected into the borehole, 3. The day-number, so that the data can be formed into a timeline. Even if a few days are missed out due to holidays or absence, the data includes the year, month, day, and a computed ‘day-number’, so that correct interpolations are always made, and variations in month-lengths are considered. The model would work just as well if only a once-weekly reading was taken, although it would not have such fine levels of detail in the ‘blips’ of the curve if variations occurred in weather or heating demand. The model hypothesizes a theoretical bulb of energy in and around the borehole, and it needs to consider three things: 1. The thermal energy extracted by the heat pump from the borehole, 2. The thermal energy injected into the borehole,
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3. The amount of energy that the borehole draws in from or loses out to the infinite surroundings. (This is the difficult bit.) When the author first considered the model in 2011, the shape considered was the same as the real ‘figure of eight’ twin borehole. The calculation of the changing volume and surface area was of a 3 dimensional complexity that defeated the more purposeful task of calculating the energy flows. If the Peveril house had a single borehole, the recommended depth would be 85-100 metres. For the model, a simple cylinder of that depth is enough to establish the principle. The theoretical cylinder also has a constant depth (e.g. of 85-100metre), but of varying radius depending on its energy level (Fig.10). The depth is constant because the borehole does not change depth as the energy volume changes. Only the radius changes because the energy that may be lost or gained relative to the infinite surrounding is next to the borehole, not below it. Therefore the changes in volume are proportional to the square of the radius because the cross sectional area is PI*(R^2).
Figure 10 – 3D representation of the borehole: Left as a single cylinder than can expand and contract outwards but not downwards. Right, as the actual figure-of-eight twin interlocking boreholes. Figure 11 – Dialog box with some of the parameters that can be tweaked to assist the algorithm. See section 2.5.
The electrical energy used by the heat pump can be converted into an estimate of the thermal energy withdrawn from the earth. The algorithm of the model has to make an assumption about the COP of the heat pump. In reality, COP varies hour to hour, based on workload and temperature of the source, but for the model, one has to apply a constant, such as an SPF (seasonal performance factor) that represents the average COP of the heat pump during the time of the test. If the assumed COP/SPF is 3.0, then a 2.0 kWh electric reading for that day is taken as 6.0 kWh in total, which is interpreted as a withdrawal of 4.0 kWh from the borehole. The figure of 4.0 goes into the array. The next input to consider is the amount of energy that is drawn back to the ever-changing energy volume of the borehole zone. This energy comes from the infinite surrounding which is assumed to be in the temperature range of 12º-12.5ºC. If the energy bulb is comfortably large, but at a temperature of 13º-13.5º, the delta-T with the surroundings is so small and the surface area to volume ratio so small that there is little elastic tension to pull energy in or lose energy out. At the depth of a heat pump’s winter season, in February, the energy bulb immediately around the borehole pipe’s is between zero and 5ºC, the surface area to volume ratio is very favourable for pulling energy in from
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the vast surroundings and energy will flow in. The author considers the analogy of elasticity, the tendency or the willingness of an object to return to its previous shape when deformed. 2.5 Modelling – significant parameters The algorithm is seeking to recalculate the energy volume and hence the radius of the energy bulb, at each time interval. For this, more assumptions are needed, which the model must be told. (Fig.11) These cannot be known precisely because the mass is un-insulated and there are unknowns. One benefit of a parametrically scripted model is that you can test alternative figures and examine the results.
• The Peak Energy Volume: is the point beyond which you get energy losses if you push more solar energy in. It is also the maximum energy level that the volume will try to swell elastically back to if the volume has shrunk to the extreme of winter. It is higher than the earth would reach if there were no solar charging. This is matter of judgement and guesswork, but a starting figure was 10,000 kWh. This guess was based on an estimate that the active borehole volume is 3,300 cubic metres of clay, having a thermal capacity of 0.5 kWh/ cubic metre/ deg K, and a 6 degree range before the energy volume is stressed elastically. The model is parametric, so if this guess is wrong, the curve shows it, and one can try a revised figure. At the peak energy level of summer, in early September, the surrounding ground has also been recharged naturally, so the delta-T between the borehole and the surrounding is small – reducing the risk of losses from the energy volume at the end of summer. • Starting Energy Volume: The model starts in Autumn 2009 with a peak summer energy volume that assumes that no solar charging has been applied for the previous three years. This is nominated at 84% of the peak energy volume, at 8,400 kWh. The assumption works well in the model. • COP: The assumption for COP of the heat pump has been discussed above. The model’s algorithm provides a choice to calculate two curves, one based on the Sunbox not existing, and the other with the Sunbox working. As the electrical figures are actual meter readings from the heat pump with the Sunbox working, this introduces a slight inaccuracy, because the figures for the electrical consumption should ideally be what they were in 2008. It is one tweak too many to try to fabricate a set of electrical consumption figures assuming that no augmentation has taken place. • Recharge Adjust Factor (RAF): A key parameter for this model is what might also be explained as the ‘index of elasticity of thermal conductivity from the surrounding mass’. As with elasticity, an inverse square law is considered for this. As one is squaring quantities in thousands with every day’s iteration, and then dividing, this RAF figure is in millionths, but how many? Not enough, and the volume never recovers, and shrinks to nothing in the second year. Too much, and it swells far too quickly to the peak. The expectation is that the curve has some resemblance to the temperature curve. Running the program until the curve appears authentic, it appears that a range of 35-50 millionths gives stable results. • Sunbox system losses: It is unrealistic to expect every kilowatt hour recorded by the meter to find its way to the borehole, so the algorithm must reduce the energy stored in the borehole. This is a parameter that the user can adjust. • Sunbox uprate: The present Sunbox is 4 square metres of collector. What would happen if additional collectors are added? The solar capture can be increased by a percentage. One way to judge these parameters is to run the model with no Sunbox influence and examine the curve. As the heat pump is 5 years old, one would expect the highs and lows to be similar each year, perhaps declining slightly. With practice, one gets the curve of the uncharged energy volume to balance. Then, by permitting the model to include and display the influence of the Sunbox, one can see the effect of solar augmentation. 2.6 Modelling – The algorithm A loop runs from the start to the end of the time line, progressively recalculating the energy volume (with and without recharging) at each time interval, usually one day. It merely adds the energy extracted, the energy injected, and computes from the difference between the energy volume at that moment and the peak energy volume an amount of energy that it will elastically pull in from the surrounding. Borehole depth is a fixed number, so from this, it calculates a value for the changing radius of the energy volume. These figures are stored in a two dimensional array rad_result[2][k]. From here, it is a matter of drawing out the lines and coloured polygons to demonstrate the curve-shape.
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Figure 12 – The algorithm is a few lines, in a loop that repeats for each time interval. A future version of this could be adapted for use in a spreadsheet. Diagram: author.
2.7 Modelling – Two-dimensional diagram The hard work has been done, and it is comparatively easy to draw out the curve. In addition, there are texts for titling and captioning. There are horizontal and vertical lines to mark key moments, such as dates of the original Sunbox installation, and a month in 2012 when the Sunbox had a leak and was not working. With any programming task, one is encouraged to avoid ‘spaghetti’ by defining each task as a distinct subroutine. Each point’s location is PUT into memory, and then a polygon POLY2 is drawn, getting the numbers from memory with a GET() statement, resulting in the coloured polygons.
These diagrams are not the entire algorithm, they are screen captures of the programming interface, capturing key parts of the code. Both diagrams: author
Figure 13 – a screen capture of the executive script for the 2D drawing showing how it is organised tidily into a set of subroutines.
Figure 14 – a screen capture of part of the routine that draws out the polygons, using data stored in an array.
Figure 15 - The final two curves, illustrating energy levels over time, with and without solar charging. Diagram: author
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2.8 Modelling – Weather interpretation The final line (orange polygon) shows the augmentation effect of solar earth charging. Both lines act as a visual diary of seasonal weather in the UK. 2010 had a very cold spring, a reasonably good summer and a very cold autumn-winter, with the coldest December on record. With ground source heat pumps, there seems to be an inertia of about 2 months, whereby the lowest energy level is during February when the heating is still on, but sunlight has not yet been strong enough to restore energy levels. 2011 had a very mild spring, a good summer and a very mild autumn-winter, so the energy level rose as a combination of reduced depletion, and increased solar charging. In 2012, the rainy and cold spring lasting well into July is revealed by a set of wobbles in the graph until air temperatures stabilised and the heat pump no longer required energy for house heating. Has the temperature of the ground risen significantly? It does not exceed 14ºC. It is much higher than this during the day; often the daytime ‘return’ temperature from the deep borehole is 1620ºC. We always measure the ground temperature at midnight, with no input or outputs of energy, after several hours of ‘rest’. What appears to be the case, circumstantially, is that the temperature gradients flatten out, and the energy level in the ground increases by widening, filling an enlarged radius at just below 14ºC. It may also be that with successive years, the reserve of energy deep down is built up, making the borehole more resilient if one particular winter is colder than usual. This guess can only be converted into certainty with another two years of monitoring, and another real-world installation, with buried thermocouples. A NOTE ON THE SYSTEM 3.0 Solar sources – Sunbox , vacuum tubes The existing Sunbox can be characterised as ‘Low-Temperature, High-Volume’. It will chug happily for 10-16 hours a day taking advantage of a 3-4 degree delta-T, and store 8-16 kWh/day even in bright conditions without direct sunshine. The author is frequently questioned by visitors and critics as to the possibility of using industry-standard products to achieve the same end. Can a ‘High-Temperature, Low-Volume’ technology work to provide energy to a borehole? Since April 2012, the author installed two square metres of Varisol evacuated tubes [17], to add to the existing solar circuit. These are high performance vacuum tubes which produce high temperatures providing there is some sunshine.
Figure 16 - Vacuum tubes, 15 in number closely spaced, totalling 2 square metres. The advantage of the Varisol is that they have a mini-manifold head detail so that by connecting them in series in a modular way, you can have any number in an array, at 70mm intervals. They would be better if vertically oriented.
Figure 17 – The only effective way to use the tubes is with a heat exchanger. If the tubes are used directly with the ground loop, the tube nodules get chilled by cold glycol, and the controller turns off the pump before the warmed liquid has had time to reach the borehole. The controller can handle two pumps.
Tubes are normally installed in a pressurised closed circuit, providing high temperature energy to a water tank. In this installation, they are heating a metal heat exchanger, with daily temperatures of 22-30ºC. The solar controller is set for indirect heating to a swimming pool via the heat exchanger. There is enough of a human and technical story in the problem-solving process of the installation of the vacuum tubes to justify another paper, but this paper is confined to 12 pages, so can only cover the thermal modelling in detail. In brief, the low-temperature high-volume low-complexity solution, the Sunbox, is approximately 4 times as productive. 3.1 Solar sources – the addition of PV-thermal During September/October 2012, the author is planning to fit 2.7 sqm of PV thermal panels on the south roof of a house extension, currently under construction. This will have its own metering,
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controller and pump, and will be monitored and compared with the Sunbox and the vacuum tubes. As PVT is midway between high and low temperature, the author is looking forward to writing up the comparisons of performance. The PV power produced will be off-grid electricity, to power the pumps and controllers in the solar systems. Figure 18 – Schematic Circuit diagram of Peveril Solar house solar system. Sunbox top left, Vacuum tubes top right, and proposed PVT panels bottom left.
CONCLUSION 4.0 The accelerative effect of solar earth charging The metering of the systems proves that there has been a great reduction in electrical consumption of the ground source heat pump, annually from over 5,000 kWh to less than 3,000 kWh. The improvement was expected to be approximately 15%, based on the fact that the deep ground temperature in the lowest part of the winter is 5 degrees warmer than the time before the solar charging was installed. This expectation is following the commonly used rule of thumb that COP is improved by 3-4% for each extra degree C in the energy source. In Winter 2009-2010, the lowest night time deep earth temperature was 4.8ºC. In the following two winters, the deep earth temperature never went below 10ºC, despite much more severe winter conditions in December 2010. Considering the volume of soil in the borehole, this temperature difference represents thousands of kilowatt hours of benefit from the solar charging.
Figure 19 – Plan view of twin boreholes illustrates how the region immediately around the pipes may be warmer or cooler than the surroundings. It also show that with twin boreholes, the regions of over lapping circles could result in a cold zone if solar charging does not occur, but conversely can result in a comfortable ‘nursing’ effect, retaining energy between the pipes. (Diagram: author)
Figure 20 – Schematic section: Theoretical thermal contours. The region immediately around the pipe will have warming and cooling fluctuations immediately around the borehole pipes, even during a single day, as the GSHP comes on and then rests, and solar energy is pumped down intermittently, depending on weather. Short term local warmth or local chilling will affect performance. (Diagram: author)
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An improvement in annual consumption of 40% needs some explaining. Watching the system as it performs, there is evidence of a short term effect that is greater than that revealed by daily or weekly readings. After a heating cycle by the heat pump, the glycol is cooled enough for there to be a good delta-T between the borehole and the temperature in the Sunbox. For a period after a heating cycle, the Sunbox circuit is very busy. In effect it is performing a rapid restoration of energy level, and it continues until the borehole is close to the temperature it was before the heating cycle. Even on Winter days, in daytime, the air temperature may be 10-12ºC in the Sunbox, enough to provide a rapid recharge for the borehole which may temporarily have been lowered to zero or 2-3ºC. • In the Equinox, the effect is very palpable, with warm daytime temperatures charging the borehole before the cooler evening. With the good insulation of the house, the heating is turned off at 10pm, so it does not have to draw energy from the borehole all night.) • In the Summer, there is a continuous dumping of energy to the borehole during the day, with borehole temperatures rising to 16-18º on good days. When the heat pump comes on for hot water purposes, it finds an immediate resource of higher-than-expected warmth, it completes the hot water heating cycle very quickly, and the borehole temperature may still be higher than 12ºC and there is rapid restoration to the daytime summer temperature. The model assumes daily energy quantities injected or withdrawn, over a period of years, but it is clear that the accelerative effect brings in a factor of Time that further reduces energy consumption. 4.1 Conclusion - where next with modelling? The model described in the paper is using data from nearly three years of real-world real-time observation and recording and producing a chart of what has happened in the past. A future development would be to adapt the modelling algorithm for an un-built installation, and predict the future. A key idea has been established using a real-world experiment, that of quantifying the RAF the Recharge Adjust Factor, or the ‘index of elasticity of thermal conductivity from the surrounding mass’. The source data set could be constructed by using Degree Days and PV records. The model could make assumptions about the heating demand of the GSHP from the degree days for previous typical years. It could do the same for the likely solar capture from the solar panel or sunbox by combining degree days and PV capture. Although it could not provide guaranteed figures, it could indicate a trend, and provide criteria to help the designer to establish appropriate sizes for store and solar thermal panels. This is a direction for future research. Acknowledgements The author would like to acknowledge the support of Dr Ala Hasan of the Aalto University, Finland, and of Professor Saffa Riffat of the University of Nottingham, UK.
References Full details and reporting of the project are visible at http://chargingtheearth.blogspot.com [1] ‘Domestic Solar Earth Charging: Carbon Zero hybrid retrofit achieved by balancing PV with solar earth charging for augmentation of heat pump’. D Nicholson-Cole, CIBSE/ASHRAE Technical Symposium, London April 2012. [2] DECC (Dept of Energy and Climate change) pages and publications on Energy policy to 2050. http://www.decc.gov.uk/en/content/cms/what_we_do/lc_uk/2050/2050.aspx [3] Veissman Technical Guide 08/2006 p19 [4] Active House concept explained http://activehouse.info/vision [5] Anneberg residential area evaluation: Anneberg, Stockhom, Sweden http://www.ateik.info/northsun2005/pdf/plenar/Magdalena_presentation_North_Sun.pdf [6] Drake Landing Solar community, Okotoks, Alberta, Canada. http://www.dlsc.ca/how.htm [7] Trillat-Berdal, V., B. Souyri, et al. (2007). "Coupling of geothermal heat pumps with thermal solar collectors." Applied Thermal Engineering 27(10): 1750-1755. [8] E. Kjellson, 2004, Solar Heating in Dwellings With Analysis of Combined Solar Collectors and Ground Source Heat Pump, Report TVBH 3047, Dept. of Buildings Physics, Lund University, Sweden, 2004, 173pp [9] http://www.engineeringtoolbox.com/heat-pump-efficiency-ratings-d_1117.html [10] Earth energy Designer (http://buildingphysics.com/manuals/eed.pdf) [11 Degree Days on line calculator] http://www.degreedays.net/ [12] Diary of the process http://chargingtheearth.blogspot.com [13] Prof Ala Hasan, Aalto University, Helsinki, Finland (president of the Nordic affiliate of IBPSA, the International Building Performance Simulation Association) [14] http://www.graphisoft.com/products/archicad/ [15] http://www.graphisoft.com/products/archicad/parametric_objects/ [16] GDL Cookbook (2001) D. Nicholson-Cole, Marmalade Graphics, Object Making with ArchiCAD (2001, 2004) D. Nicholson-Cole, Graphisoft [17] Varisol tubes http://www.kingspansolar.com/products/varisol.aspx
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