Searching for Opportunities – Systematic, District-wide Approach

Faced with a portfolio of greenspaces within a district, how can the most promising opportunities be identified?

For green spaces in Scotland, greenspace scotland has developed the ParkPower Dashboard+. Users can view and filter approximately 3,500 green space sites by their suitability for a range of green energy generation technologies. 

For green spaces located anywhere else, this section shows you how to systematically, strategically search for opportunities across your district. 

Getting started - Information inputs

GIS (Geographic Information System) data that documents the geographical extents, internal features and qualities of green space is a valuable tool for building a shortlist of parks and green spaces that may be favourable for ground or water source heat pump installations. GIS data may be held by landowners or by mapping service providers (e.g. Ordnance Survey). It may be free-to-access or you might need to pay a fee.

The GIS datasets that are most useful for assessing green space heat opportunities cover green space boundaries, building locations, water body extents, vegetation types and surfacing materials. They may also include data on land use.

In addition to GIS data, information that may be used to filter or rank green space includes:

• Heat demand mapping (may also be in a GIS format) and/or information about the presence of specific buildings that are likely to represent large heat loads.

• Land and landscape designations that might affect viability (may also be in a GIS format).

• Information about soil types and depths (may also be in a GIS format).

• Information about geology down to 200 metres depth (may also be in a GIS format).

• Information about the depths and temperatures of static water bodies (lakes, ponds) and the depths, temperatures and flow rates of rivers.

• Written details or drawings of recent or planned resurfacing work on sports pitches, grassy areas and hard surfaced areas (relevant for assessing opportunities for near- to medium-term implementation only).

• Information on the existence of park user groups or “Friends Of” groups, and how active they are (relevant for the assessment of opportunities for near- to medium-term implementation only).

Scales to consider

If you are embarking on a systematic search for green space heat opportunities, you may wish to focus on opportunities within a particular range of scales. This decision may be driven by considerations of organisational capacity, budget availability, timescale pressures, emissions reduction targets or the need to contribute to wider strategy development. However, if it is feasible to scope out a wide range of scales - everything from small schemes capable of heating a hundred square metres of floor space up to ambitious whole-park schemes – the knowledge generated will have the potential to deliver against many of the objectives that are common to local authorities and green space owners across the UK. Table 1 outlines the key reasons for including opportunities at the lower and upper ends of the scale.

In the case of very large (greater than 1MW) vertical, closed-loop, heating-only ground source schemes, there may be limits to the amount of heat collector capacity that can be installed even when there appears to be sufficient space (according to rules-of-thumb) to host a larger capacity. These limits are related to macro-scale cooling effects that occur when a large number of boreholes are installed in a space affecting heat conduction from the surrounding earth. Real-world installations rarely deploy more than around 200 boreholes, unless the scheme provides cooling as well as heating (in which case, some or all of the heat extracted in the winter is replenished by the system in the summer).

In addition to the issues around scale, those undertaking opportunity searches may wish to focus on opportunities to heat certain types of building or end user, or to install heat collectors under a particular type of land (e.g. playing fields, where ground works can incorporate heat collector installation at the same time as installing improved drainage). 

10 step methodology for creating an opportunity shortlist

This methodology assumes that you do not have clearly defined objectives for the scale of heat pump project that is installed, nor the type of heat loads that are supplied. If these objectives are defined, they can be used to promote or deselect certain opportunities in the process in addition to the steps laid out in this guide.

Step 1: Establish approximate resource density figures for the district

There will be different figures for the ground heat resource density (how much energy can be extracted per square metre of green space) for horizontal and vertical systems. If significant variation is found across the district, you could divide it into a small number of zones with different average resource densities.

A suitable value must be selected for the capacity factor. If the search includes specific types of building or heat load that are likely to have demand profiles diverging from a “typical” space heating profile (e.g. buildings that are heated 24/7, leisure centres, industrial sites), a bespoke capacity factor figure should be used – see [Internal Link to Module D1]. Otherwise, a value of 20% (1800 hours’ full load-equivalent heat demand) can be used.

Horizontal schemes resource density

The estimation process outlined in module 5.1 should be followed, using a capacity factor of 20% (unless the search has been narrowed to a specific type of heat load which would suggest a different capacity factor). For a very general, non-location-specific estimate for space heating applications, a typical value could be 15 W/m2 (representing: mean ground temperature 10°C, ground thermal conductivity 1.2 W/mK, 1800 hours’ full-load equivalent heat demand, 5 metres trench spacing).

Vertical schemes resource density

The estimation process outlined in module 5.1 can be followed. For a very general, non-location-specific estimate for space heating applications, a typical value could be 55 W/m2 (representing: mean ground temperature 11°C, ground thermal conductivity 2.0 W/mK, 1800 hours’ full-load equivalent heat demand, 150 metres borehole depth).

Step 2: Create a register and green space records

Obtain or create a list of all parks and green spaces in the scope of the assessment.

Decide on an information record/storage structure. You could create a folder for each park if there are likely to be separate GIS files or several site-specific documents for each park. Depending on the number of parks and the demand for a readable/printable document, you could collate information in an Excel file or Word document with a row or heading for each park.

Parks that are nominally separate but adjacent or very close to one another should be combined into a single record, so that opportunities involving more than one park can be considered.

Step 3: Obtain GIS data 

Arrange access to GIS data for all parks in the scope of the assessment. Ideally this data will show:

• Park boundaries

• Vegetation cover and hard surface type

• Sports pitch/court boundaries

• Water bodies

• Individual trees (if not in a densely wooded area)

• Building use type

• Areas affected by human burials

• If the GIS data does not show all of these features, a combination of satellite imagery and site visits can fill in some of the gaps

Sources of green space GIS data with nationwide coverage include:

• the Ordnance Survey OS Open Greenspace dataset (which is freely available to access and download);

• the OS Greenspace MasterMap Layer (available only to organisations covered by the Public Sector Mapping Agreement (PSMA) or the One Scotland Mapping Agreement (OSMA));

• Greenspace Information for Greater London (GiGL): open spaces feature on the open, browser-based Discover-London product (under “Sites to Visit”). GiGL’s proprietary data records various features of open spaces in Greater London. The level of detail is similar to the OS Greenspace MasterMap layer, but covers some different features while omitting others.

Step 4: Validate and convert GIS data (if required)

A GIS specialist will be able to verify that the GIS data is in a suitable form to enable resource areas to be accurately estimated. If the data is not in a suitable form, they will be able to adjust settings or perform conversions so that it is straightforward for a non-expert user to accurately calculate areas and measure lengths in the units that they are expecting.

Key aspects to check include the Coordinate Reference System and the measurement units. Measurements can be validated by checking a known distance in real life or on a trusted map against the equivalent in the GIS model – features with strict dimensions like tennis courts can be very useful for this.

Step 5: Optional processing of GIS data

If the user has the capability and the GIS program has the functionality to enable manipulation of the GIS data, some useful refinements are explored below.

Removal of unsuitable land use or landform types

If the dataset marks areas of land as having certain relevant characteristics, unsuitable areas can be removed from the layer to improve visual clarity and facilitate calculations. Areas to remove could include:

• Allotments

• Bowling Greens

• Caravan Parks

• Cemeteries

• Private Gardens

• Woodland

• Scrub

• Beach

• Landscaping features like mounds and ditches

Buffering around trees

If data showing the locations of individual trees is available, land areas that are too close to trees can be excluded from the search. Tree locations are most likely to be recorded as “point” data (rather than lines or polygons). Exclusion zones around trees can be created by:

1. Creating a layer of polygons that include the areas within a certain radius of each individual tree. If data on tree species and age is available, different radii could be applied to different trees in depending on the extent of their likely root zones. Otherwise, an ‘average’ radius of 5 metres if younger trees dominate, or 10 metres if mature trees dominate, can be used for the purposes of opportunity evaluation.

2. Subtracting this new buffer zone layer from the original green space polygons.

Importing locations of buildings of interest

Loading datasets showing the locations and footprints of certain types of buildings alongside green space datasets could help with your search for promising ground and water source heat opportunities. Building categories to include could be:

• Buildings within green space (if not included in the green space GIS data)

• Local Authority-owned buildings (including housing)

• Other public-sector buildings

• Community-owned or community-run buildings

• Buildings connected to existing heat networks (if any)

Importing heat map data

Where heat mapping data is available in a GIS format (for example, Scotland’s Heat Map or the HOTMAPS tool, this can be added as a layer in the GIS programme to help you indentify large heat loads or zones of concentrated heat load (e.g. areas of high housing density) that are close to parks and green space areas.

Step 6: First approximation of suitable land area and heat resource

One-by-one, inspect the GIS data for each green space, looking for single areas or groupings of areas that appear to be open space and unaffected by any constraints that have been built into the analysis in previous steps. The minimum total area to record should be 250m2. Where there is uncertainty, findings can be validated by comparison with free online satellite imagery (although it should be remembered that satellite imagery can be several years old and sometimes mislabelled).

Roughly quantify and record the area (in square metres or hectares) of potential ground source opportunities in each green space. For large green spaces, just record the area of the largest agglomeration, but note that much smaller opportunities may also exist. Where the GIS data is fragmented or complicated to work with, aim to capture the area with an accuracy of ±50% or better.

Sports pitches and courts – including tennis courts – can be included as ground source opportunities. (In-use bowling greens are not suitable). Hard-surfaced areas such as car parks, plazas and parade grounds can be included.

Record the area of any ponds or lakes larger than 1,000m2.

Using the register set up in Step 2, create an initial long-list of green spaces that have some ground or water source heat potential. Then calculate a maximum heat supply potential for each:

It may be worth recording qualitative reasons for rejecting those sites that have not made it onto the long-list, e.g. lack of open space, extensive mature tree cover, presence of burials etc.

Step 7: Optional creation of heat demand search zones in GIS

If you have the capability and the GIS program has the functionality, create buffer zones (to roughly define accessibility for heat supply) around each green space on the initial long-list. These buffer zones should be 20 metres, 50 metres, 200 metres and 400 metres from the boundary of the green space (or - if recorded as a separate polygon within a larger green space area - the area of ground or water source heat potential). Fewer buffer zones can be mapped for sites with maximum heat supply potential of less than 250kW, as detailed in the table below:

Adjust the visual rendering of these zones so that the base map can be seen but the boundary of the zone is clear.

Step 8: Search for heat loads

Considering the green spaces on the initial long-list one by one, note down the presence of buildings representing heat demands that could be supplied from a green space heat scheme:

Google Maps and Open Street Map are useful information sources to supplement locally held GIS and other data. The owners and managers of green space may hold information about in-park buildings, including energy bills from which heat demands can be inferred.

When recording the presence of potential customer buildings, lump together approximately homogenous smaller users e.g. residential properties, shops, offices. For the purposes of estimating the likely size of heat user, consider housing blocks to be one building.

Step 9: Ranking long-list opportunities

Ranking the opportunities, which now link greenspace heat potential to buildings that could use heat from green space, will be a somewhat subjective process. As yet, the opportunities have not been assigned firm characteristics in terms of capacity, number of connections, likely capital cost or likely financial and non-financial benefits. The requirements and preferences of the organisation which might develop a green space heat scheme have not necessarily been defined in measurable terms.

If the number of sites on the long-list is relatively small, it may be feasible to carry out a preliminary matching exercise that seeks to identify those buildings or groups of buildings that score highly in terms of the ratio between the heat demand and the distance from the green space heat resource - while remaining within the limits imposed by the size of the resource. Proximity is important because of the high cost of laying pipework, especially in the urban environment, and to a lesser extent due to heat loss from the pipework. 

That score can then be used to rank the opportunities presented by different greenspace areas. Although this matching could be done by specialist software, for this shortlisting step an approach that combines intuition and trial-and-error is adequate.

If the number of long-list sites is too large to carry out the matching exercise, rank the opportunities in a rough, qualitative way considering:

• The greater the magnitude of the biggest individual heat demand, the stronger the opportunity

• The greater the total size of the identified heat demands, the stronger the opportunity

• The greater the number of identified heat demands, the stronger the opportunity

• The closer the heat demands to the green space, the stronger the opportunity

This technical ranking could be refined by considering other requirements and preferences for characteristics of shortlisted opportunities. Perceptions about the likely ease of project delivery, availability of information and political palatability could be influential.

Considering the time and resource available to investigate further, an appropriate number of opportunities should be selected to feature on the shortlist.

Step 10: Supplementary research to refine the shortlist

Additional written resources, data and organisational/human knowledge may suggest green spaces that should be removed from the shortlist:

• Park Management Plans may provide information about buildings or facilities that might provide heat load, planned building projects that could create or affect a heat load or planned groundworks or resurfacing projects that could be leveraged.

• Natural or cultural heritage designations or environmental protection designations may preclude schemes being installed at certain sites, e.g.:

  • Nature Reserve

  • Site of Special Scientific Interest (SSSI)

  • Conservation Area

  • “London Square” or similar designation outside London

  • Groundwater Surface Protection Zone I (Inner Protection Zone)

• Information about the depth of a water body (direct measurements could be made if no information can be found) could exclude some opportunities: a minimum depth of 1 metre is required, but ideally at least 2 metres.

• Barriers to connection (other than distance) between the green space and the potential heat user buildings may exist, such as rivers, large buildings, terraced houses, dense woodland, steep slopes and cliffs. Depending on the size and position of the barrier, crossing or going around it may be prohibitively expensive.

• Geological conditions may also be a factor – flooding of former mines may provide a future resource for heat, with the Coal Authority calculating that the constantly replenishing water within these mines could provide all of the heating requirements for the coalfields population. British Geological Survey also has resources about sub-surface temperatures, but payment is required for this data. In the absence of this, rules of thumb estimates can be used.

Footnotes:

1. This is a very approximate resource density for water source heat pumps. In practice, the water depth, temperature, inflow/outflow rates and several other important parameters will have a strong impact on the amount of heat that can be extracted from a water body.

next >