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Solar earth charging: Peveril Solar House • CIBSE Liverpool April 2013 : Paper 73

• Arch. David A Nicholson-Cole (w. Prof S Riffat). • • Architectural staff in the Dept of Architecture & Built Environment, University of Nottingham

• Peveril Solar house, Nottingham • Solar heated all year round, by storage • Net-zero, due to balance of annual PV generation

and GSHP consumption • Project running from Aug 2009 to now: four winters • Multiple solar sources tested - 2 Sunboxes, PV, Tubes • Sunboxes : black Chillers inside Solarium

Sunbox is an array of black panels contained in an insulated solarium connected to the ground loop. The Peveril Solar house in Nottingham is entirely solar heated, all year round, with Net Zero performance for heating and hot water. The PV roof generates as much power as the heat pump consumes in a year. This is a hybrid retrofit, achieved on a well insulated British developer house. The solar project has been going for four years now, principally to research interseasonal solar charging. It uses solar heat to recharge the borehole and this augments the ground source heat pump. The Sunbox is a 4 square metre array of swimming pool panels contained in an insulated polycarbonate and ETFE solarium. An additional Sunbox of 2 sqm was installed in December 2012, on the lean-to roof. The entire system has been hand built by the author, an architect who often wishes he was an engineer. (60 seconds)

Solar earth charging: Virtuous Pentangle • Net Zero balance, thanks to energy storage • PV generates 3,200 kWh • GSHP uses 3,200 kWh • Solar stores 2,500 kWh • Net-zero made possible by solar thermal augmentation of borehole used by GSHP • Three solar thermal systems: 2 Sunboxes & Tubes

• Real-time, Diurnial

Electricity Grid

Sunbox + Tubes 6 m2

The Earth

and Interseasonal charging • GSHP previously used 5,200 kWh annual, now it is 3,200 kWh. • Accelerative restorative effect of solar charging - nearer to 40% improvement, not 15% expected

PV roof 4kW

Solar House 120 m2

Borehole Clay+Limestone 3600 m3

GSHP 2kW normal 6kW gross

•Accelerative Effect - TIME plays a part. • Energy restoration after each GSHP heating cycle is in real time • Leaves borehole better prepared for next heating cycle.

The Virtuous Pentangle diagram illustrates the interactions of the system. The Photovoltaic roof is an installation of 4 kW facing East, but it is enough to bring in 3,200 kWh annually. Before 2009, the heat pump used an estimated 5,200 kWh/year. With solar charging, it is now maintaining an annual consumption averaging 3,200 kWh/year, thus the house is Net-Zero. The deep ground temperature at the lowest point of the year is 5 degrees warmer than in previous winters. One might expect a 15% improvement to the seasonal performance factor. The real improvement is measured at 40%. This may be due to the accelerative effect of solar charging. After each heating cycle, the delta-T between Sunbox and Groundloop is larger. Frequently the system will perform immediate restoration of energy levels in the borehole, making it more ready for the next heating cycle. (60 seconds)

Solar earth charging: Ground chilling • Borehole chilling effect

worsens over several years.... • ... also depends on conductivity of soil, borehole depth, shading of building surroundings, other heat pump users, rate of extraction etc • Temperatures of deep earth can be measured

• Note: Curve shape:

• steep winter fall-off • long slow summer climb-out.

• Energy Volume •more significant than Temperature

• The model in this paper is

Above: Regular chilling of ground until a new low equilibrium achieved - without augmentation, GSHP becomes inefficient and uses ‘additional heat’. Left: deep ground Temperature curve over four winters. Characteristic shape is steep fall-off in early Winter, and long slow climbout during Spring, through to late summer.

Below: The curve of Energy Volume in the Model. This paper sets out a methodology for displaying Energy Level.

searching for Energy Volume Deep boreholes for ground source heat pumps are at risk of progressive chilling. They are dependent on decades worth of slow natural solar charging. A house with high demand for heating or hot water will cool the ground enough to lower the temperature to a point where the heat pump is struggling. It may seek ‘additional heat’ by one-to-one electrical heating. Ideally, the ground recovers during the summer. If the house is surrounded with other houses covering the ground or using heat pumps, or is situated on east-west streets with tree shading, then deep ground temperature will not recover fully. It will level off at a new lower equilibrium, making seasonal performance of the heat pump much worse. The curve shape of ground temperature reveals a steep falling off in early winter, with a long and slow climb out during spring and summer. Temperature is one way of guessing the energy level in the ground, but it is not a precise indicator of the true volume of energy. The Energy Volume is the only thing that matters, as temperatures vary in rings around the borehole pipes. (70 seconds)

Solar earth charging: Need for a Model • Project started in 2009 • based on logical hunch - knowing there is a

benefit, not knowing the numbers or system design • Real world - Peveril installation is testing Sunboxes (and Tubes) in one inhabited building • Each monitored several times a week • Combination is too complex for existing spreadsheets to forecast or model. • Theoretical model is needed: • to understand energy flows of existing • to predict future system. • For this to progress to replicability, it needs credible track record of both modelled and installed examples • Human & Architectural and Technical factors also need to be researched. • July 2012, author set out to write Thermal Model using Geometric Description Language (GDL), a programming system within ArchiCAD.

Above: Circuit diagram for three solar systems together. Below: Website for the project, with every thought and work stage recorded.

In 2009, the author proceeded directly with a real-world, real-scale, real-time inhabited installation. Life is too short to spend three years monitoring the “Before” condition, thus losing all the benefits of the PV feed in tariff and the energy saving on the heat pump operation. Logic says that it would work even if the numbers are unknown. Funding was available, so the project began. It has been running for four winters and there is enough metered data to analyse the performance. We now know that it works. A theoretical model is now required for understanding the energy flows. In 2011, the author tried to write a thermal model and gave up. In 2012, the author tried again, and set out to write the script for a model, using Geometric Description Language, a programming language within ArchiCAD software. (60 seconds)

Solar earth charging: Re-defining Borehole • Real borehole is twinset - 48m deep, 5m apart,

overlapping - ideal for solar charging. • For Modelling purposes, regard the Energy Level as a Virtual Volume: a single deep cylinder, approx 85-100m deep. • As volume increases, can only expand outwards, not downwards. • Therefore: Volume is proportional to square of Radius. • Imagine energy volume expanding and contracting as inputs and outputs occur. • When energy level is low, earth energy sucked in from infinite surrounding mass. • Surface area to volume ratio changes with expansion/ contraction, proportional to square.

• Assume a consistent

thermal conductivity of the earth. • Borehole cluster better for solar charging

Above: Real boreholes Left: virtual borehole

It was necessary to picture the Energy Level in the borehole as a Virtual Volume. The real borehole is a twinset of overlapping cylinders. An attempt to write the model in 2011 failed because the twinset is too complex for a first attempt. Defining the Energy Volume as a single cylinder of fixed depth means that as the Volume changes, only the Radius changes. This changes the surface area to volume ratio beneficially. One can calculate the inputs and outputs in kilowatt hours and add these to the energy volume. When the volume is small, the delta-T is high, surface area to volume ratio is large and it has a stronger elastic pull on the energy around. When the volume is very large, the reverse applies, there is only a small loss to the infinitely large surroundings. For a model one has to assume consistent thermal conductivity, although in the real world, earth has layers and varied materials. For a real new-build solar charging installation, a cluster of shallower boreholes would be better, because the zone between nurses the energy volume. (70 seconds)

Solar earth charging: Data Collect Fig 6. Daily monitoring of all electric and thermal energy meters in a large multi-tabbed spreadsheet See it at:

Fig 7. Another tabbed page reads relevant columns from the first page, places in new columns with separating commas

For Data collection, Electric and solar thermal energy meters are read almost every day. These figures are stored in a giant multi-page spreadsheet. If a few days are missed out, the days between are interpolated. Another tabbed page in the spreadsheet reads relevant columns from this and places the meter readings into new columns. The readings are separated with commas. (30 seconds)

Solar earth charging: Data Convert Fig 8. Readings are copied and pasted into field of a GDL data-file as numeric text with comma separation. PUT statement tells it to read the data into memory

Fig 9. GDL script reads file and places all data into ‘Arrays’ in memory, with significant names like ‘daynum’, ‘gshpconsume’, ‘sbinput’ etc.

On the left, this data is copied and pasted into a text field of a GDL data-file. On the right, The GDL script of the energy modelling program declares the arrays that will be used, reads this file. The data is linked to the time-line. The data is stored into Arrays as dates, day numbers and energy flows, inward and outward. So that I can remember what is going on, the arrays have logical names like ‘daynum’, ‘gshpconsume’, ‘sbinput’, ‘month’, ‘day’ (40 seconds)

Solar earth charging: defining Parameters GDL allows one to build a ‘parameter table’, to display to the user some of the constants required.

•Peak summer energy volume: the

maximum charged level beyond which energy will leak away.

•Starting date and energy volume - in this case 8400 kWh in Aug 2009.

•SPF of heat pump: average COP.

Reading in the electric consumption, the algorithm determines how much energy needs to come from the earth.

•System loss: all systems have losses

in pipework, and in top part of borehole, and liquid left in pipe after pump stops.

•System upgrade: What happens if the solar panel area is increased?

•Borehole depth: a constant that

allows the Radius to be a variable. The GDL front end allows one to build a parameter table, to display to the user some of the constants required. Peak summer energy volume is the maximum charged level beyond which energy will leak away, and towards which the winter shrunken energy volume wishes to expand. Starting energy volume is whatever you estimate at the start of the timeline. In this case it was August 2009. The Seasonal Performance Factor of the heat pump is the COP averaged over the year. By reading in the electrical consumption, the algorithm can determine how much energy is pulled in from the earth each day. System losses must be allowed for because they really occur, whatever the meter tells you. There are losses in the pipework, and in the top part of the borehole, and warm liquid is left in the pipe after the pump stops. A System upgrade allows one to consider what happens if the solar panel area is increased. The Borehole depth is a constant that allows the Radius to be calculated at each time interval. (80 seconds)

Solar earth charging: Recharge, Algorithm Recharge Adjust Factor • The most useful discovery of the model - a technique to quantify natural recharge which occurs all the time, not only in summer. • Think of as: “index of elasticity of thermal conductivity of soil as energy is brought in from the surrounding mass”. • Large numbers are involved, so the R.A.F. for this model is in the region of 35x10-6. • Method: View the graph without charging; get the peaks and troughs to level nicely in accordance with weather records; the RAF is then correct.

• The main algorithm is this short loop. • Running through the timeline (daily intervals over 4 yrs), algorithm incrementally adjusts Energy Volume based on inputs and outputs, and then calculates the elastic Recharge from the surroundings. • Algorithm fills two arrays with values for RADIUS, one that allows solar charging and one that assumes zero charging.

For the author, the most useful finding has been discovering what is called Recharge Adjust Factor : it is a means of quantifying the natural recharge process it is an elastic process of pulling external energy in as the energy volume shrinks with each time interval during winter. The recharge adjust factor works best with a value of 35 millionths for this particular installation and soil condition. The algorithm calculates two energy levels at each time interval, one with solar charging and one without. From this, two values for Radius of the Energy Volume are stored in an array. (40 seconds)

Solar earth charging: Forming a curve

• The array contains daily figures for theoretical Radius of the Energy Volume. These are converted into 2D polygons

Above: Final Curve, Vertical black lines show significant moments on the timeline. Dates are printed along the baseline. Right: Subroutines to draw out diagram. Far Right: Most of the drawing routine.

The array has been filled with values for the RADIUS of the Energy Volume. These can be converted into a 2D graph. Vertical black lines show the significant moments on the timeline. Dates are printed along the baseline. The whole program is a series of subroutines, so that I can come back to it a year later and have some chance of editing the code if it needs more features adding. (30 seconds)

Solar earth charging: Model results, colour

•Dual Energy Curve Shape is the end result of the process •Compare with the Ground Temperature curve Above: Final chart, Blue is Uncharged, and Red is the cumulative effect of charging relative to Weather. Weather: 2009 there was no charging, 2010 was cold, 2011 was very warm, 2012 rainy, 2013 Spring is v cold.)

•Graph can show the energy level

without charging, with charging, or in this case with both options displayed. • Tweak parameters if necessary.

Conversion of the line into a coloured polygon makes it easier to compare the benefits of solar charging. With two values, the graph can display the result blue without solar charging, red with solar charging, or in this case with both options displayed in colour. If the curve looks unstable, parameters may need adjusting. For example, if it is shrinking to nothing, or expanding evermore, the constant parameters such as Recharge Adjust Factor and Peak can be modified. At the end of the process, one is trying to establish a Curve Shape, not quantify precise energy levels. The Energy Curve Shape here demonstrates the pattern of behaviour over four seasons relative to Weather and can be compared with the Ground Temperature curve. (50 seconds)

Solar earth charging: Conclusions 1. Solar capture: Sunbox is more effective! • Low-temp, large-volume collector (Sunbox, 2400kwh/yr) proved more effective, versatile and simple than hightemp collector (Tubes, 350kwh/yr). • If starting again and South Roof, would do it with PVT (Photovoltaic-thermal) 2. Accelerative Effect: take note of this: TIME factor contributes more than bland annual input / output figures. Immediate restoration of energy level takes place after a heating cycle. 3. Modelling: Useful exercise, but where next? • Understanding natural recharge rate has helped. • Could use typical Degree Day and PV data • Re-write the algorithm to read typical year data and forecast solar panel area based on different house-size, GSHP capacity and borehole size. • Adapt it to clustered boreholes. Read all about it! Website is:

Thankyou! Conclusions: ONE. The Low temperature high volume Sunboxes are many times more effective than High temperature low volume method of Vacuum tubes. PVT is Low temperature high volume and should be considered in future. TWO. The improvement in heat pump performance from the expected 15% to 40% may be due to the Time factor - immediate restoration of energy levels occurs immediately after a heating cycle by the heat pump. THREE. The Energy Volume Modelling has been useful in developing a methodology, using past data on the existing house, borehole and solar systems. For the author, the method for calculating the daily rate of natural recharge was a pleasing discovery. Someone else in this room may also have discovered this. Please email the author. The next phase could be to make it applicable to another house, borehole and solar system, by using annual weather statistics from a typical previous year. Degree Days could be used to forecast heat pump demand, and PV records could be used to make an index of ‘sunniness’. This would help to estimate the required capacity of the heat pump, borehole and area of solar panels for future installations. Please read the website for more news of this project. If you have been, thankyou for listening. (90 seconds)

DNC article for CIBSE Liverpool April 2013  

DNC article for CIBSE Liverpool April 2013, including lecturers notes

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