COHEAT 5G Heat Network Demonstration

COHEAT Ltd
REV2.2 for publication
Principal author: marko@coheat.co.uk
DECC Heat Networks Demonstration SBRI
COHEAT 5G Heat Network Demonstration
Phase 2 Report
COHEAT gratefully acknowledges the support of the following organisations; without whom this project
could not have been delivered successfully:
The Department of Energy and Climate Change ran this SBRI programme to stimulate innovation
that will help address cost and performance efficiency challenges related to heat networks. This
allowed COHEAT to upgrade the 4G Heat Network being installed at Trident Meeting House and
demonstrate the 5G Heat Network concept in operation on a live site.
Climate-KIC is Europe's largest public-private innovation partnership focused on climate innovation to
mitigate and adapt to climate change. Their accelerator programme is delivered by Imperial College in
the UK and has helped COHEAT with both business development activities and €95,000 in funding to
help us towards our goal of decarbonising Europe’s housing stock.
National Grid Affordable Warmth Solutions match-funded Trident Housing Association with
£25,000 to purchase the base 4G Heat Network from COHEAT, provided sage advice on delivering
retrofit energy efficiency measures in occupied buildings, and expedited the gas connection for the
project.
The Energy Saving Trust shared their measurements of domestic hot water consumption in
dwellings so that COHEAT could derive diversity curves from these world class datasets.
Trident Housing Association purchased the base 4G Heat Network, allow COHEAT to demonstrate
world first technology on the network, and jointly manage resident relationships and scheme
administration with COHEAT.
Destination Digital was an ERDF funded programme helping Cambridgeshire businesses purchase
digital equipment and services. COHEAT benefited from £4,000 in match-funding to purchase
sensors, prototyping, and networking equipment to help develop an early version of our Operating
Platform.
DISCLAIMER
It is not intended that the output of this report and it’s appendices should be used for any purpose
other than to assist you in the understanding of the information therein.
In the event that information within this report is used for other purposes you do so at your own risk
and without any responsibility or liability on the part of COHEAT Ltd.
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COHEAT Ltd
Executive Summary
Project Aims
Sharing larger, lower cost, lower carbon heat sources using a heat network is a sound concept.
Modern, low temperature, 4G heat networks offer exemplary technical performance but fall short of the
scalable commercial solution required for them to become the de facto heating solution in the UK.
To become the de facto residential heating solution heat networks need to meet the following brief:
“Heat networks must be available to buy as a standardised package that can be specified,
installed, and operated as easily as individual gas boilers. They must deliver reduced lifecycle
costs without compromising on technical performance or the consumer experience. They must
achieve all this at a scale to suit new build developers and social landlords: 20-250 homes.”
This project sought to dispel the myths used to excuse over-size and over-temperature heat network
designs and show how applying smarter control technology to heat networks can make them more
competitive than individual gas boilers, even for small 20-250 home scale suburban developments.
Key Findings
Smart Heat Networks
A purpose-developed control platform was developed and applied, from utility supplies through to
individual radiators, to a heat network that was downsized to the extent that it relied on this system to
avoid hitting capacity constraints. This worked as expected.
● Smart networks allow up to 50% reduction in installed capacity vs. passive networks1
The same platform was also used to partially automate commissioning (full automation was prevented
by hardware limitations), provide technical service level monitoring, and provide integrated retail utility
metering/billing/payment collection and account management at minimal extra cost. This level of
integration from utility supplies through to individual radiators, including all user interfaces and retail
back office capabilities, and all based on internet is believed to be a world first for heat networks.
● Smart networks can substantially reduce operating overheads and the expertise
required to deploy and operate heat networks; especially for small scale developments
Heat Density
Heat networks are traditionally seen as a solution for large developments in urban areas with a high
heat density. This project has shown that heat networks done well - preliminary figures show
distribution losses of the order just 300-350 kWh per year per home - can be attractive for suburban
areas (59% of UK housing stock and more than 59% of heat demand); for developments less than2
250 homes (the bulk of projects); even where heat density is low (new build and refurbished homes);
and compare favourably against individual gas boilers on both lifecycle carbon and cost.
● The addressable market for heat networks could be larger than previously anticipated
1
Those without active, real-time, management of network load on a network-wide basis
2
DECC publication “The Future of Heating: Meeting the challenge” March 2013 (page 78)
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COHEAT Ltd
Low Temperature Heat Networks
A low temperature heat network (55°C flow temperature) was retrofitted into existing buildings of low
thermal performance (pre 2002 Building Regulations) and operated with DHW delivered at 42°C.
Fundamentally this works, though further work is needed on transient space heating response in order
to satisfy UK consumer expectations.
● Low temperature heat networks are viable for many existing buildings
Sizing
Industry practice results in oversized heat networks that cost more to build and operate less efficiently
than they might otherwise. This project has highlighted where to focus and what to do about it:
● Designing for intermittent heating at design condition is suboptimal but encouraged
○ BREDEM (SAP) needs modifying to account for time/rate of energy use.
● Designing to accepted standards significantly overestimates hot water load
○ A national (UK) standard derived from primary data from a relevant sample of dwellings
is needed that clients/consultants accepting design liability can cite.
Quality of Service
By some metrics (e.g. % heat loss) peak efficiency was achieved on the pilot network the day that a
filter housing split in the energy centre split and the network went cold. (0% heat loss) Clearly this isn’t
an acceptable Quality of Service. Keeping all of the network fully hot, including the DHW heat
exchanger, all of the time, means zero waiting time for DHW to reach temperature and a home that
reheats as quickly as possible. It also minimises heat network efficiency so isn’t an acceptable Quality
of Service either. Somewhere between this and an energy centre failure is a happy medium.
● Given the influence Quality of Service has on heat network efficiency, an appropriate
target should be defined and monitored when evaluating heat network performance
Next Steps
COHEAT are commercialising the outcomes of this demonstration programme; beginning with a“best
of breed Operating Platform for heat networks and extending into the (electronic) hardware
infrastructure necessary to support the full functionality that the Operating Platform can provide.
Wherever possible this is being delivered in partnership with the existing supply chain, with the
intention of creating an open, interoperable, ecosystem of products and services that de-risks the
smart heat network proposition for investors, ensures fair pricing through competition, and offers all
players in the marketplace a sufficient share-of-wallet to promote the delivery of heat networks.
Additional demonstration projects at a meaningful scale will be needed and will likely require external
support. Recommendations for additional research are outlined in the conclusions and include:
● Collect More Data
● Define Quality of Service
● Revisit Radiator and Heating Control
● Promote System Balancing (in the non heat network sector)
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COHEAT Ltd
Aims and Objectives
Sharing larger, lower cost, lower carbon heat sources using a heat network is a sound concept.
Modern, low temperature, 4G heat networks offer exemplary technical performance but fall short of the
scalable commercial solution required for them to become the de facto heating solution in the UK.
To become the de facto residential heating solution heat networks need to meet the following brief:
“Heat networks must be available to buy as a standardised package that can be specified,
installed, and operated as easily as individual gas boilers. They must deliver reduced lifecycle
costs without compromising on technical performance or the consumer experience. They must
achieve all this at a scale to suit new build developers and social landlords: 20-250 homes.”
Technical State-of-the-Art
A 4G heat network sharing heat from a low cost, low carbon, source is state-of-the-art from a technical
and environmental perspective.
A 4G heat network sharing a low cost, low carbon heat supply between more than one home
These networks operate at low flow temperatures to reduce the cost and improve the efficiency of low
carbon heat supplies; which is particularly important for heat pumps, steam turbine extraction , and3
low grade heat recovery from commercial and industrial processes.
They smooth heat demand profiles using a continuous, weather-compensated, space heating control
strategy and instantaneous hot water production in order to avoid co-ordinated re-heat peaks; thereby
reducing the peak capacity required and making greater utilisation of the available capacity.
They reduce capital costs and heat losses using an engineering driven design methodology: keep the
dimensions of pipe and equipment down by right-sizing them to deliver heat at the minimum rate
required, then deliver that heat at the lowest possible temperature, with the largest difference between
flow and return temperatures, and at the highest allowable flow velocities.
This exemplary performance comes at a price. Specifying a 4G network with this minimalist design
approach requires a client with the nerve to defy entrenched (UK) custom and practice that
encourages the opposite. Designing and delivering a 4G network that performs to the specification,
then keeping it performing to that specification, requires specialist labour that is already in short supply
and can’t scale to mass (UK) deployment. UK consumers object to continuous space heating too.
The client also needs a separate retail utility capability (customer account management, metering,
billing, payment collection, and customer support) and for the smaller 20-250 home heat networks it
can cost as much for the client to setup and operate this than it does for the heat network itself.
3
This is how heat is taken from CCGT or nuclear plants, which are very sensitive to offtake temperature.
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COHEAT Ltd
Commercial State-of-the-Art
Individual gas boilers are state-of-the-art from a specifier and consumer perspective.
These highly standardised, volume manufactured, commodity products are suitable for one or more
homes of any type and require minimal skill to specify or install. The latest boilers include enough
embedded intelligence to commission themselves, self-diagnose equipment faults and major
installation errors, and can cope with even the most egregious space heating control strategies to
operate with reasonable efficiency in all applications.
Combined with low capital cost; and well established supply chains that allow the client to walk away
from any ongoing billing, metering, and provision of service obligations; it’s little wonder that gas
boilers account for over 90% of the annual market for heating systems in the UK.
Consumers value the pseudo-choice between different brands and tariffs applied to the same gas
delivered down the same pipe and complain about the marginal fuel costs that the media cover every
winter. More rationally it’s the high cost of maintaining and replacing individual gas boilers, plus their
limited scope for fuel switching and further efficiency improvements to what is a mature solution (poor
national energy security and scope for reducing carbon emissions) that are their biggest weaknesses.
Overarching Aims
This project sought to dispel the myths used to excuse over-size and over-temperature heat network
designs and show how applying smarter control technology to heat networks can make them more
competitive than individual gas boilers, even for small 20-250 home scale suburban developments.
Overall Approach
Phase 1
The Phase 1 feasibility study sought to understand what the actual loads are on a heat network; what
scope there might be for manipulating these without adversely affecting the consumer experience; and
what the resulting lifecycle cost and carbon emissions might be relative to an individual gas boiler.
Phase 2
The Phase 2 demonstration sought to prove the theory by applying a purpose-developed control
system to a heat network that was downsized to the extent that it relied on this system to avoid hitting
capacity constraints. The base heat network itself demonstrated best practice in hydraulic design.
Phase 2 also sought to demonstrate how the a control system could be used to deliver additional
benefits, such as fully automated commissioning, technical service level monitoring/condition based
maintenance, and integrated retail utility metering/billing/payment collection and account management.
In order to fully appreciate the needs of specifiers, installers, operators, and end users - and secure
the necessary freedom to innovate - COHEAT designed, installed and now operate this heat network,
which was a new network installed to serve 24 existing dwellings and a laundry formerly equipped with
storage heaters for space heating and immersion heated cylinders for domestic hot water.
Phase 3
Phase 3 will monitor performance of the finished network for a complete season in order to provide
defensible lifecycle cost and carbon figures.
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COHEAT Ltd
Specific Objectives
Reduce the capital cost of heat networks
● Improve industry understanding of heat loads to make over-sizing networks harder to justify.
● Show how smart control technology can serve more homes for a given heat network capacity.
● Show how duplicated infrastructure can be avoided by using the exact same operating platform
and data infrastructure for consumer (smart thermostat), retail (metering, billing, payment
collection), and technical (network monitoring, smart control techniques) functionality.
● Show how heat networks can be commissioned flexibly and remotely using software.
● Show that complete heat networks can be built using only standard volume manufactured
domestic and light commercial components; without involving any specialist trades on site.
Reduce the operating cost of heat networks
● Show how smart control technology can continuously optimise the operating strategy of a heat
network in order to improve the efficiency of the heat supply and reduce distribution losses.
● Show how remote, real time, visibility of the entire network and the service levels achieved
within individual home can be provided cost effectively, in order to identify issues before the
consumer does and without resorting to costly phone calls or service technician visits.
● Show that even low heat density sites can be served efficiently by heat networks using low
operating temperatures and the downsized pipework enabled by smart control technology.
Improve the consumer experience of heat networks
● Show how smart control technology can give (UK) consumers the control (time clock with
comfort/night setback) and behaviour (radiators that “come on” and “get hot”) they expect
without compromising the performance of the heat network.
● Show how an integrated operating platform enables advanced user interactions, such as the
option for landlords to pay for frost protection even where a resident’s prepayment account has
no credit, or prepayment systems that don’t cut the hot water off in the middle of a shower.
● Show that radiators with 55°C flow temperatures and domestic hot water delivered at 42°C are
considered hot enough by (UK) consumers and are safe.
Applicability
The demonstration of smarter control technology applied to heat networks is applicable to both new
and existing heat networks. A new network could deploy every innovation outlined above to benefit
from reduced capex/opex and improved UX.
An existing heat network could be retrofitted with a variety of smarter control technology; from just the
(cloud based) operating platform and regular M-Bus heat meters, which can be provided cost
effectively and brings reduced opex benefits optimisations enabled by remote, real time, visibility of the
entire network and the service levels achieved within individual home; through to the (cloud based)
operating platform plus full data backbone and electronic controls for the existing hydraulics, which
brings the full suite of reduced capex/opex and improved UX benefits. Whilst downsizing existing
pipework is unlikely to be economic, the smarter control technology can the capacity on existing
networks to serve more homes without upgrading the pipework or energy centre to reduce capex.
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Technical Solution
Base Heat Network
The hydraulic design of the base heat network and energy centre used to demonstrate the technology,
other than their having been downsized on the assumption that there’s never any need to deliver
space heating and hot water simultaneously, is as per any modern 4G heat network.
This means direct connected space heating using radiators and domestic hot water delivered via
instantaneous plate heat exchanger inside a heat interface unit (SATK 20305 HIU):
Hydraulic layout for an individual dwelling, showing fast acting 2-port control valves for space heating and hot water
Heat is supplied by a 12 kW air source heat pump and (oversized) 125 kW gas boiler via a 1,000 litre
buffer vessel and a 3.5 m3
/hr circulating pump for the entire network. The overall layout is as below:
Network live viewer, showing two mains serving 12 homes each (24 total) plus laundry and a future office on 2nd main
Headline facts and figures
● Location: WS10 7PS, UK
● Design condition: -6°C
● Network flow temperature at design condition: 55°C
● Network differential pressure at design condition: 400 kPa (reduced to 40 kPa at each dwelling)
● Space heating: Radiators sized for 55/35°C at design condition. (5 per dwelling)
● Domestic hot water: Delivered at 42°C via instantaneous plate heat exchanger sized for
55°C/35°C on the network side and 10°C/42°C on the potable side at 35 kW peak. (55°C/25°C
at 25 kW) (SWEP E8T 30 plate)
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COHEAT Ltd
Site layout for the Meeting House heat network
Sizing and Hydraulic Design
COHEAT made the effort to size the base heat network correctly, including calculating hot water
diversity factors using raw UK data that’s been freely available from the Energy Saving Trust since
2008 but not taken up by the heat network industry until now. Whilst not the innovative step that this
project was demonstrating, the methods used to size the network will nevertheless improve industry
understanding of heat loads, and are covered in the following appendices:
● Appendix 2 - State of the Art (including design guidance)
● Appendix 3 - Estimating Loads and Flowrates (including hot water diversity analysis)
● Appendix 4 - Design Temperatures and Pressures (including impact of smart control tech)
Left: 20 mm ID PEX twinpipe heat mains being installed by non-specialist labour without the aid of handling machinery.
Right: Energy centre showing gas boiler with 35 mm OD pipework and the 22 mm OD heat mains to the left of it. Each heat
main serves 12 homes, over a run 150 metres in length, with enough spare capacity to connect the 300 m2
office in future.
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COHEAT Ltd
Operating Platform
Understanding and improving how heat networks perform required the following:
1. Visibility of what the network is being asked to provide
2. Visibility of what is happening on the network
3. Visibility of what the network is delivering within the home
4. Control over how the how the system delivers what it is asked to provide
No suitable platform capable for doing this was available commercially so COHEAT had to build one
before any research work on control strategies could begin. The architecture looks like this:
Platform architecture showing relationship between 3rd party services, cloud based Operating Platform performing non
real-time critical tasks and (right of Smart Grid Controller) the local real-time control system running over a robust backbone.
The Operating Platform is integrated with every sensor and actuator used to deliver heating and hot
water; every interface that a user or operator interacts with; and 3rd party data feeds such as weather
forecasting, payment collection, and SMS messaging services.
It is all built on internet technology rather than building/process automation technology. Redundant4
ring Ethernet as a data backbone, with an ARM System on Chip running Linux in every home, and
utilising the same type of authentication, encryption, messaging, and database technologies
developed and made freely available within the last decade by the likes of Google and facebook.
These are now considered robust enough for banks and governments (online banking) to use them.
The controller is aware of what the network is being asked to provide through the user interfaces. It
has full visibility of what is happening on the network and within the home with sensors down to
individual room and radiator level. It has full control authority over every actuator in the system, except
for safety valves and differential pressure control valves, so can implement any control strategy in
order to deliver what it has been asked to provide. This integrated platform runs the network
technically and all the retail operations too: metering, billing, prepayment, portal/apps for the consumer
(the touchscreens on the wall are essentially apps), portal/apps for the operator (the operator console
is all web based), payment collection and suchlike.
4
Mission critical functions run on the local network (intranet) with the internet used for optimisation/management
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Visibility of what the network is being asked to provide
Heat interface units notify the network of hot water requests in real time. Consumers use an in-home
touchscreen to tell the network what their heating requirements are on a room by room basis.
User interface and excerpts from the operator interface showing heating requirements and every touch/button press
Visibility of what is happening on the network and being delivered in the home
Every single sensor and actuator used to deliver space heating and hot water is visible in real time and
recorded for subsequent analysis. The 24 homes and laundry currently generate some 4 million data
points each day. This includes sufficient in-home/in-room data showing what the network delivered vs.
what the consumer asked for in order to make a judgement on the success of any control strategy.
Left: Excerpt from live network viewer showing space heating active in four properties, including flowrate and flow/return
temperatures. Right: historic domestic hot water flow rate and position of 2-port control valve for one property
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Left: Radiator with electronic valve and return temperature sensor. Right: Room sensor measuring temperature, humidity,
light level, door/window closure status, and providing a local room temperature boost button with visual feedback. These are
wireless devices but were supplied with mains power to facilitate radio algorithm testing without draining batteries.
Control over how the how the system delivers what it is asked to provide
The platform is able to control every single pump, valve, and setpoint in the system electronically in
order to implement any strategy for meeting space heating and hot water requests from consumers.
Left: Fully networked heat interface units. Middle and right: Fully networked energy centre. (all three before insulation)
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Smart Control Techniques
The following techniques were proposed in Phase 1 and demonstrated on a live network in Phase 2:
Purpose Control technique or feature
Avoid network capacity constraints and
mitigate their impact when they do occur;
meaning that more customers can be
served using smaller pipes, pumps, and
heat sources
● Hot water priority
● One in, one out
● Network constrained space heat optimisation
Reduce energy costs and emissions by
optimising network operating
temperatures, pressures and space
heating strategies to improve utilisation of
pipes, pumps, and heat sources
● Network shutdown and pressure control
● Network operating cost optimisation
Improve the user experience and reduce
commercial capital/operating costs by
using the control infrastructure to deliver
additional non-control benefits
● Full individual room zoning and automated
commissioning
They were delivered in the following packages:
● Service prioritisation (including hot water priority and one in, one out)
● Network shutdown and pressure control
● Network cost optimisation and constraint mitigation (covers network operating cost optimisation
and network constrained space heat optimisation)
● Individual room zoning and automated commissioning
Service prioritisation
4G networks use hot water priority for single homes. A heat interface unit can prioritise domestic hot
water service over space heating, just like a combi boiler with a diverter valve does.
5G networks behave as a single system and can implement service priority across the entire network
or parts or it, rather than just within a single home. This is illustrated below for hot water:
Hot water priority; showing how 5G control can prioritise hot water over space heating on a branch wide basis
On a typical network branch serving 10 homes this technique will reduce the peak capacity required
by 50% as outlined in Appendix 4. This is implemented using a Real Time Planner (RTP) module.
How does this work?
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The RTP module receives requests to deliver heat. These might be (pre-planned) space heating
requests from a module that converts room temperature requests into a space heat delivery plan.
These might be (unplanned) hot water requests from a heat interface unit that has detected flow on
the hot water circuit. The RTP module takes these requests, prioritises them according to a set of rules
that always have a defined answer and that can be computed quickly with a complexity that linearly
with network size, then issues a new plan to the network in order to implement these. This happens so
quickly that it is imperceptible to a consumer.
The supervisor view in the operator portal shows the live status of the RTP module:
Network supervisor view showing live status of RTP module. This expandable tree structure mimics the layout of the heat
network and shows the services requested and the services authorised in priority order. In this example:
● Flat 11 is requesting comfort space heating, there is capacity on that heat main and the network, and this request
has been authorised.
● Flat 22 is requesting hot water, there is capacity on that heat main and the network, and this request has been
authorised. The RTP rule for this network is set to block space heating for a dwelling any time there is a hot water
demand in that flat, so requests for space heating in that dwelling will be blocked whilst hot water is being drawn.
● Flat 20 is requesting comfort space heating, but the billing system has blocked this service because the credit
balance is insufficient. Space heating that is necessary for frost protection would still be authorised because this is
billed to a separate (landlord) account.
A rule has been set so that a request for hot water is always prioritised over any request for space
heating. As elements of the network reach capacity the RTP will first de-authorise space heating in
order to serve hot water loads. In the absolute extreme, if an element of the network reaches capacity
due to hot water loads only, then the RTP will implement a one in, one out policy: the last person to
turn on a tap will wait a few seconds for the first person to finish using theirs before heat is available.
(we are talking about extremely statistically unlikely events: 1 in 1,000 or rarer) This is more
acceptable that a shower running cold so you can design at lower capacity and hit it more often.
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A rule has also been set so that a request for a large amount of space heating is prioritised over a
request for a small amount of space heating. If an element of the network reaches capacity those
properties that are a long way from their temperature target will receive a greater share of the capacity
than those that are close to their temperature target. A similar rule could be set based on temperature
difference (target vs actual) or absolute temperature (room vs 20C) etc as desired. The RTP is more
flexible than than relying on pipework (differential pressure) to dictate service priority at peak and is all
about making hitting a capacity constraint less undesirable and more acceptable to do more often.
Network wide hot water priority has by far the largest impact on sizing (halving it in critical areas) and
associated capex and heat losses. Many other rules can be implemented in the RTP module to suit an
operator’s needs though, such as automatic service priority for vulnerable consumers based on data
from the retail database: the only restriction is that the rules are determinate and compute quickly.
Network shutdown and pressure control
4G networks make sure that there is enough differential pressure available at every HIU to deliver the
peak rated flowrate at any time. (ideally only just enough differential pressure at the index HIU, based
on feedback from a remote differential pressure sensor at the index point within a consumer property)
Much of the time the differential pressure capable of delivering the peak rated flowrate at an HIU isn’t
necessary and is wasteful in terms of pumping energy, but 4G networks can’t do anything else
because the system doesn’t know when the HIU requests heat or what flowrate is required.
5G networks know when there’s a request for heat, what flowrate this will require, and what differential
pressure at the index HIU will guarantee this flowrate is achievable. A real time control loop was
combined with a rule in the RTP module that:
● Controls pump pressure to achieve a defined differential pressure at the index HIU
● Sets the pump to idle if no service is required for a specified period
Available pump capacity over a 24 hour period in spring. 100% is “pump set to idle” and 0% is “pump at maximum.” Note this
real time control loop runs in software within the Operating Platform, over the Ethernet based data backbone, rather than
using dedicated wiring as is customary when linking index dP sensors to a pump control unit. (more infrastructure saving)
Differential pressure is typically 0 kPa, 50 kPa, or slightly above 50 kPa at the pump. Events needing the full 400 kPa have
been simulated but have yet to occur in operation; occasionally 200 kPa is required. It proved impossible to reduce
differential pressure below 50 kPa, even when only trivial flow rates were required, due to mechanical stiction in the
differential pressure control valves within the HIUs. This prevented further pump optimisation below 50 kPa.
Using this strategy the pumping energy on the network has been measured as 0.4% of heat energy
delivered to the homes. This compares favourably with traditional heat networks in spite of the smaller
than standard pipework and a single high pressure pump (sized for the limit case) working well below
its optimal efficiency point for the overwhelming majority of the time. Jockey pumps would help further.
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Bypass Flows
The same system can be set to control the bypass flows that are used to ensure that hot water is
available from the network within a reasonable amount of time. At times of low heat demand water in
the flow pipe of a heat network cools. If it takes too long to clear this volume of cool water before hot
water arrives from the heat network then the waiting time for hot water at a tap can be unacceptable.
4G networks aren’t aware of when there’s likely to be a requirement for hot water or when the last
demand on the system was and how far away the hot water in the flow pipe of the heat network is
likely to be. They typically keep portions of the network hot at all times using bypasses in order to
guarantee that hot water arrives from the heat network within a reasonable time. “Riser bypass” is
considered best practice in apartment buildings, where risers are kept hot but low volume laterals and
branches are allowed to cool. “HIU bypass” is often necessary in suburban settings, where all of the
network is kept hot at all times due to the pipe lengths and volumes involved. This is particularly
wasteful where the time at temperature for space heating season is otherwise short, and where space
heating demands are modest, such as in lower energy new build housing and milder (UK) climates.
5G networks forecast when there’s likely to be a requirement for hot water based on historical demand
patterns and can also use extra information, such as a smart thermostat that’s in comfort mode rather
than night setback or away/holiday mode. The 5G network also knows when the last demand on the
system was and could calculate how far away the hot water in the flow pipe of the network is likely to
be based on the cooling rates of pipe elements. The 5G network can use this information to adopt an
intelligent bypass strategy, keeping as much of the network as cool as possible for as long as
possible, whilst still ensuring that the waiting time for hot water at a tap remains acceptable when it
matters.
On this particular network: a happy consequence of downsized pipework that has a very low volume;
plus low operating temperatures and good insulation that means pipework cools slowly; a loop-through
pipe layout that keeps homes as close to the heat main as possible; occasional draw-offs throughout
the day that keep this warm; and fast acting electronic control valves in the HIUs with control loops
that “purge” the cool water very quickly compared with proportional mechanical valves; was that no
deliberate bypass flows were necessary on the pilot network to satisfy consumers. This is unlikely to
be the case on most networks and further R&D will be necessary in order to develop intelligent bypass
strategies. The platform is capable but there was no need for bypass at all on this occasion. (unusual)
Network cost optimisation and constraint mitigation
4G networks use a continuous space heating strategy. Flow into each the radiator follows the
difference between room temperature and TRV setpoint, a simple control mechanism that
automatically follows the weather conditions as (passively) buffered by the thermal mass of the
building. Keeping homes warm 24/7 smooths out space heating load profiles and minimises the peak
network capacity required by eliminating reheat peaks. This increases in overall heat use compared
with intermittent heating, and more importantly doesn’t satisfy (UK) consumers who expect time
control of their space heating and radiators get hot to the touch.
A 5G network will select the most appropriate space heating strategy for any given circumstances
using model predictive control. (MPC) This advanced method of process control has been in use in
chemical plants and oil refineries since the 1980s because it can anticipate future events and take
control actions accordingly; whilst handling constraints, such as limits on control variables, in a direct
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and natural way. It involves repeatedly solving a constrained optimisation problem, using predictions of
future costs, disturbances, and constraints over a moving time horizon to choose the control action.
MPC process flow (recommended reading: Predictive Control: With Constraints, Jan Maciejowski, ISBN 0201398230)
The model predictive controller for the heat network takes into account:
● An estimate of current state based on historical data (measurements and estimates)
● A physics model of the system (including heat emitters and building thermal mass)
● Consumer heating schedules (demands)
● Cost of consumer discomfort (deviation from demand)
● Weather forecast
● Hot water demand forecast (reduces the capacity likely to be available)
● Cost of operating the network (cost of flow/return temperature and flowrate)
● Constraints on control variables
At an instant in time the model predictive controller will follow the process flow above to calculate a
plan for control actions that represents the least-cost solution over a finite time horizon. This is the
most appropriate heating strategy, given what it “costs” to operate the network vs. what it “costs” to be
uncomfortable.
Different consumers could, in principle, express different discomfort cost functions in order to express
their preference for being comfortable vs. saving money. Consumers could also, in principle, express
their preference for saving carbon vs. saving money using an appropriate cost function and the MPC
would take these into account when deciding how to run the heat network. The platform is available
and capable of this, but developing such optimisations are firmly in PhD not proof of concept territory.
The plan is calculated on a room by room basis and will have will exploited the thermal mass of the
heat emitters and the building fabric. When complete - if complete - the plan is transferred to the RTP
module for execution. There is no guarantee that a viable solution to the optimisation problem will be
found: this is a challenging nonlinear MPC application and solvers can and do fail. In this instance a
backup planner will supply a via plan to the RTP for execution. (a standard proportional heating control
is used for this network; controlling setpoints well but not offering optimum-start/pre-heat functionality)
What’s the typical result of all this?
● If the weather is mild and the room temperatures aren’t far off setpoint, the radiators “turn on”
just before the comfort period just as a (UK) consumer expects.
● If the weather is cooler or the room temperatures are further off setpoint, the radiators “turn on”
earlier to make sure that the room is warm in time and (UK) consumers value this feature.
● As conditions become more extreme the heating becomes ever closer to continuous, but is
mindful of the increased cost of heat from non-baseload sources and makes allowances for
capacity that is likely to be unavailable due to hot water use; and will increase network-wide
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flow temperature only as when this is necessary to meet an actual consumer request rather
than to ensure that any consumer request could be met. (these two are subtly different)
Example - single room MPC output
The series of charts below best illustrates the output from the MPC. They show the output for one
room over a period of 3 hours into the future.
The first chart shows the
predicted temperatures of the
radiator (the mean water
temperature, the flow temperature -
- fixed to 70 degrees in this
example - and the return
temperature). It also shows the
temperature of the wall mass.
The second chart shows the
predicted temperature of the
room, the requested temperature
of the room, and the outdoor
temperature.
The 4th chart is the flow rate into
the radiator and the series of
control inputs that we should
follow to achieve this profile. The
spike on temperature step
change shows need for more
research work on input
conditioning and cost functions.
The other charts show power
being delivered to the radiator
and the costs that the model is
seeking to minimise.
Example network and heat main MPC output
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Each chart shows (second graph) in blue the estimate of total flow (l/min) given by the prediction, in green the estimated hot
water power (kW) (from the hot water forecaster), and bottom graph (blue) the ‘cost function’ that the control is seeking to
minimise for this network. These are shown for the whole network and each of the two heat mains separately.
Hysteresis control
Left: temperature schedule requested; right: room temperatures resulting from simple hysteresis control. The rooms do not
reach the temperatures requested by the user within the period set by the time clock - very common in UK homes.
Model predictive control
Left: primary flow into the property in response to the same temperature schedule request. The predictive controller can be
seen pre heating (at a reduced rate that makes use of the base load heat source/results in low return temperatures) before
ramping up the rate to achieve setpoint, having determined that using the peak heat source/increasing return temperatures
had a lower cost than discomfort from failing to achieve the temperature requested. Note that during the comfort period the
room temperatures are much closer to the setpoint and more stable than in the simple controller. The “noise” on the flow rate
is cascade control (pulse width modulation) of a control valve plus TRV on/off but shows poorly when rendered on the graph.
Full Individual Room Zoning
Full individual room zoning is being able to set time and temperature schedules for each room
independently and remotely. This is increasingly common in the consumer heating control market.
Traditionally, as the systems should be designed and operated:
TRVs installed at high level are used to control the target temperature in each room on a zone. An (optional) central
hysteresis thermostat can then REDUCE the temperature in all rooms on that zone, approximately proportionally, to save
energy at night and when the building is unoccupied. The hysteresis thermostat is not used to control comfort temperature.
Traditionally, as the systems are designed and operated in practice:
TRVs are installed at low level as token/decorative features to meet a regulation. These are all set well above the desired
room temperature and are therefore permanently fully open. A central hysteresis thermostat is used to set the comfort
temperature in one room, with the heat distribution between rooms dictated by radiator size and flow balance only.
This is a real problem for heat networks and is often down to poor specifier/installer/user education. This situation is not
helped by mis-selling of Nest/Hive type controls that are really only suitable for controlling comfort temperature on systems
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COHEAT Ltd
without any TRVs, and the disconnect between how the Building Regulations compliance guides assume controls are used
vs reality. (regulations should specify controls that are in theory less effective but are simpler to use/impossible to abuse)
Any greater degree of control, such as independently varying the times that individual rooms are
heated, independently varying the target temperatures over time, or the facility to set these remotely,
requires electronic controls in each room.
Automated Commissioning
Commissioning is ensuring that the right amount of water flows through each part of the network at all
times. Commissioning is required at both network (HIU) level and individual room (Heat Emitter) level,
and ensuring that this is done is of increasing interest in heat networks at the moment.
HIUs
The latest electronic HIUs are continuously self-commissioning to a large degree: local controllers can
consistently achieve the setpoints programmed into the unit. No data connectivity and/or poor fleet
management systems means that programming these is still a local, manual, task and reprogramming
these in service is impractical.
COHEAT successfully demonstrated automated, database driven, remote Heat Interface Unit
commissioning. The platform continuously monitors the performance of the unit and modifies the
setpoints programmed into the unit based on user/administrator account driven service levels and the
operating conditions of the heat network. A vulnerable consumer requires a different hot water setpoint
in a particular home? A change in network flow temperature calls for modified hot water control loop
parameters for optimal response vs stability? This can all be done remotely via the platform - thanks to
central databases driving the setpoints based on customer metadata or network operating points.
Heat Emitters
Commissioning at individual room level is still a manual process requiring a technician to limit the
flowrate through each heat emitter by setting a valve in an appropriate position for a certain room and
flow temperature. This relies on the consumer not then compromising up how the system operates by,
for example, putting a towel on the radiator or setting a TRV to a higher temperature than the central
hysteresis thermostat. These two extremely common behaviours will both turn a radiator with a TRV
into an unintentional network bypass. Mechanical return temperature limiters can be installed on each
radiator in addition to TRV and the presetter or balancing valve. This will prevent most gross overflows
due to gross hydraulic imbalance and consumer behaviour but is now three controls per radiator to
purchase, install, and commission correctly.
COHEAT installed wireless electronic actuators on every TRV body and had intended to use these for
both full individual room zoning and automated commissioning: the idea was to set flowrates for each
radiator automatically by commanding a valve position. In practice challenges were encountered with
this approach and are discussed under the lessons learned section.
Integrated Retail and Technical Solutions
The following features were proposed in Phase 1 and demonstrated on the live network in Phase 2:
Purpose Control technique or feature
Improve the user experience and reduce
commercial capital/operating costs by
using the control infrastructure to deliver
additional non-control benefits
● Shared infrastructure for integrated consumer,
retail, and technical functionality
● Remote, historic and real time, visibility of the
complete operating business
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● Advanced consumer interactions
An architecture that avoids duplicated infrastructure by using the exact same operating platform and
data infrastructure for consumer (smart thermostat), retail (metering, billing, payment collection), and
technical (network monitoring, smart control techniques) functionality has already been outlined. This
allows a richer consumer experience than would otherwise be possible. For example:
By reading the full complement of technical data from a standard M-Bus heat meter at high frequency5
one can see individual hot water events and verify that an acceptable quality of service (response
time) was delivered. Combining this with room temperature data and temperature requests from
thermostats it’s possible to identify space heating issues before the consumer does. (or ‘cold’
consumers whose rooms are hot, probably have the flu, and require a doctor not a service engineer)
Standard M-Bus heat meters and temperature sensors are under-utilised by many operating platforms
Interrogating the heat meter data allows bills to be generated in real time and itemised; so that
consumers know where and when their money went (heating vs. hot water); and a landlord can pay for
some types of usage, such as network bypass and frost protection regardless of credit status.
5
Only some meters are capable of this; and some when powered by battery or M-Bus; others on mains power
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Screengrabs from user interface showing itemised billing and how sharing the output from the forecasting module allows
instant, personalised, feedback at the point of use as to the effect that making changes to your heating schedule will have
and how this compares with your peers. (these personal to the home not the usual vague approximations based on the
building stock at large, and are therefore more accurate and more believable for consumers)
Progress Against Plan
COHEAT planned to develop, demonstrate and evaluate the benefits 5G controls on a new heat
network, scheduling the 5G Heat Network Demonstration around the heating season and a previous
plan to deliver a 4G heat network for Trident Housing Association at the Meeting House pilot site.
Work Packages
The work packages proposed were as follows:
WP0: Programme management (weeks 1-47)
● Includes internal governance process and regular steering meetings with DECC PMO
WPa: Base network installation (weeks 5-13)
● Not SBRI funded but included for context. Includes deployment of 5G control hardware. WP1 included only the
incremental cost for upgrades to hardware required for 5G control.
WP1: Hardware delivery (weeks 1-30)
● WP1.1 - 1.4: detail design and manufacture of 5G capable energy centre, HIUs, and networked consumer heating
controls in conjunction with subcontractors
● WP1.5 - 1.6: installation of heat pump and onsite deployment of 5G user interfaces
WP2: Basic 5G controls (weeks 1-30)
● WP2.1 - Foundation Controls: network data infrastructure, actuator controllers and 3G fail-safe mode. Onsite
demonstration of data collection for Condition Based Maintenance.
● WP2.2 - Foundation UI: user interface which allows simple collection heating schedule required for 5G
optimisations
● WP2.3 - Supervisory controller: implementation and onsite demonstration of a controller with network wide
prioritisation. Onsite demonstration of Hot Water Priority and One In, One Out, and early version of Network
Shutdown control techniques
● WP2.4 - Hot water forecasting: statistical analysis of historical hot water usage to forecast the demand by property
for a given time period
● WP2.5 - Space heat forecasting: combination of building physics model, weather forecasts and user space heating
schedules to forecast space heat needs by property
● WP2.6 - Constraint based predictive control: applying a constraint based model predictive controller (MPC) to the
demand forecasts to optimise space heat delivery for each home. Onsite demonstration of Network Constrained
Space Heat Optimisation
WP3: Advanced 5G optimisation (weeks 23-47)
● WP3.1 - Cost based predictive control: improve the MPC to optimise the entire network based on operating cost
of delivery. On site demonstration of Network Operating Cost Optimisation, Network Shutdown and Dynamic
Temperature and Pressure Management.
● WP3.2 - Pump management: using the MPC outputs to optimise pump operation. Trade off deadheading vs.
start/stop for multi-pump system. Improves Network shutdown.
● WP3.3 - Advanced UI: using 5G controls to give meaningful and real time feedback to the consumer on the impact
of the their heating choices. Onsite demonstration of Integrated Metering and Account Management.
WP4: eTRV integration (weeks 9-43)
● Installation of individual room eTRVs and temperature sensors. Extension of 5G cost based controller and UI to use
additional sensors and valves to improve the onsite demonstration of Network Operating Cost Optimisation. On site
demonstration of Automated Commissioning.
WP5: Report and forward planning (weeks 1-47)
● Documentation of design, lifecycle analysis, and final report setting out next steps and the investment case for
commercialisation. Energy monitoring throughout pilot.
WP6: Performance evaluation (weeks 40-47)
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● Energy Saving Trust evaluation of the 5G heat network’s energy performance, using a system boundary that enable
direct comparison with their condensing boiler and heat pump field trial datasets.
As Planned
The original plan called for a 3rd party contractor to handle the installation and commissioning of the
base heat network in gas-fired 3G mode; whilst COHEAT and 3rd party development partners
developed the hardware and software from TRL6 to the TRL7 required to demonstrate the innovations
on a live heat network.
This was not ideal: having a pre-existing heat network and/or a technology already at TRL7 available
would have been preferable and was what the funding was intended for. The timescale and resourcing
were ambitious but the concept of applying smarter control technology to heat networks to make them
more competitive than individual gas boilers, even for small 20-250 home scale suburban networks,
had merit. DECC therefore allowed COHEAT to attempt delivering both elements (heat network and
technology) in parallel to meet the 11 month window, for which we are extremely grateful.
This gave approximately 4 months to design and install a base heat network that functioned, 4 months
to implement innovations, and 3 months of heating season during which to assess their effectiveness.
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As Delivered
Installation of the base heat network, which was not funded by the Heat Networks Demonstration
SBRI and not in the slightest bit novel, had the largest adverse impact on overall project delivery.
COHEAT had arranged for a contractor to remove the old electric heating systems and install standard
radiators/pipework within the flats up to the HIUs, including all quantity surveying, procurement, and
installation including management of labour on site. In the event the tradesmen provided built an
excellent rapport with the residents in this occupied retrofit installation - which endures to this day - but
COHEAT had to handle quantity surveying, procurement, management of labour on site, and indeed
physically remove storage heaters and install pipework in order to meet the agreed heat-on date.
This was an invaluable experience as far as understanding the needs of installers and challenges in
occupied retrofit, but consumed COHEAT’s limited labour resources and delaying the complete
delivery of WP1 by ~8 weeks. (plus deferred heat pump installation) The project never fully made up
the knock-on effect of this lost time: less data was gathered than COHEAT would have liked and the
LCA is lighter on data than we would like as a result. DECC’s extending the project monitoring through
31/03/2017 with Phase 3 addresses this.
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Technology Readiness Level
5G networks entered and exited Phase 1 at TRL6: prototype subsystems had been tested in a
relevant environment. The Phase 1 study refined estimates of the benefits that applying 5G control
techniques at the heat network design stage could provide. By applying the most promising of these to
a real heat network, Phase 2 ended at TRL8: actual system completed and qualified through test and
demonstration.
Equipment Installed
The demonstration network comprises the following equipment:
Within each home
● A Network Interface Unit to:
○ Create a redundant ring Ethernet network
○ Power all of the sensors and actuators within the home
○ Read all of the sensors and command all of the actuators within the home
○ Run real time local control loops
○ Exchange encrypted messages with network controller
● A Heat Interface Unit with:
○ A direct connected space heating circuit
○ A plate heat exchanger for hot water
○ A modulating valve to control primary flow through the space heating circuit that can be actuated remotely
○ A modulating valve to control primary flow through the heat exchanger that can be actuated remotely
○ Sensors to measure:
■ Primary flow and return temperature
■ Primary flow rate
■ Primary differential pressure (index homes only)
■ Domestic hot water flow rate
■ Incoming domestic cold water and outgoing domestic hot water temperature
■ Domestic cold water consumption
● A user interface with:
○ Touchscreen capable of displaying web pages
○ An LED to provide feedback
○ Wi-Fi (for use as Wi-Fi hotspot only, showing the heat network infrastructure providing data connectivity)
Within each room
● A modulating valve to control the flow through each radiator that can be actuated remotely
● Sensors to monitor:
○ Temperature
○ Humidity
○ Light level
○ External door/window closure status
○ Radiator return temperature
● A user interface with:
○ A button to signal a request (boost)
○ An LED to provide feedback
Within the energy centre
● A buffer vessel with:
○ Temperature sensing at 20 levels
● A main network pump with:
○ Remote start/stop
○ Remote control of absolute discharge pressure
○ Electricity meter
● Heat mains with:
○ Heat meters
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COHEAT Ltd
○ Differential pressure sensor
● A gas boiler with:
○ Remote call for heat
○ Remote control over flow temperature
○ Gas meter
○ Heat meter
○ 3-port valve to select supply location from buffer vessel
● A boiler circulator pump with:
○ Remote control over differential pressure
● An air source heat pump with:
○ Remote call for heat
○ Remote control over flow temperature
○ Heat meter
○ 3-port valve to select supply location from buffer vessel
○ 3-port valve to select feed location into buffer vessel
● A heat pump circulator pump with:
○ Remote control over differential pressure
● A control system with:
○ Electricity meters
Monitoring Data Collected
A large volume and variety of data was collected as part of this project. Appendices 5 and 6 detail the
type of physical/system measurements that one would expect to see on a district heating system.
These measurements are:
● Partially complete from 01/10/2015
○ No heat pump/heat meter, boiler heat meter, or buffer vessel sensors installed
○ Room sensor data very sporadic
● More complete from 15/12/2015
○ Heat pump/heat meter, boiler heat meter, and buffer vessel sensors installed
○ Room sensor data still very sporadic
● Largely complete from 20/03/2016
○ Room sensor data is good at this point but becomes more sporadic as time goes on due to the room
sensor code getting lost in an endless loop (not resolved - but reset when the opportunity arises)
In addition, every consumer interaction with the system (screen click/button press/topup) is recorded,
as is a variety of software related data (every message sent/received, system temperatures and
resource usage etc) used for the purpose of debugging the operating platform.
There are major limitations extrapolating the data collected to annual performance: (1) the control
strategies were changing right up to the end of March and (2) the performance of both the network and
the heat pump will change with the weather and network load. Further monitoring for a full year of
operation is necessary to provide defensible numbers for network performance. Furthermore, the
nature of the site (sheltered housing for young adults with a low income/low threshold for
comfort/appetite for heat, a high official void rate, and an even higher unofficial void rate) also means
that the heat loads are abnormally low compared with general needs housing. The demonstration
therefore represents a worst case scenario for distribution losses vs delivered heat.
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Key Findings
This project was about:
● Estimating what the actual loads are on heat networks; what scope there might be for
manipulating these loads without adversely affecting the consumer experience; and predicting
what the lifecycle cost and carbon emissions might be relative to an individual gas boiler.
● Showing how a purpose-developed operating platform could be used to manipulate loads on a
downsized network in real life whilst delivering additional benefits such as fully automated
commissioning and integrated retail utility metering/billing/payment collection and account
management to tackle the non-technical costs associated with delivering heat networks.
Estimating Loads
Appendix 3 details how to estimate the actual loads on heat networks. Common errors in space
heating strategy and perverse regulatory incentives are discussed, followed by a piece of work to
determine peak design hot water loads and the data that needs to be gathered to calculate these.
● Designing for intermittent heating at design condition is highly suboptimal yet common
○ BREDEM needs to account for time/rate of energy use to avoid encouraging this.
● Designing to even the Danish DS439 standard significantly overestimates hot water load
○ A national (UK) standard derived from primary data from a more relevant sample of
dwellings will improve understanding and allow clients/consultants accepting design
liability to cite it without fear of their professional indemnity coverage being invalid.
Estimating Performance
COHEAT estimated what the lifecycle cost and carbon emissions of a 5G heat network might be,
assuming designs as per Appendix 4 and a challenging low energy density (new build or renovated)
suburban environment, then compared this with individual gas boilers.
● A 5G heat network is expected deliver a 40-70% reduction in CO2e emissions for useful heat
at the same or lower lifecycle cost as vs. individual gas boilers
System Boundary
5G heat networks deliver useful heat at the point of use. Space heating is only useful if it is controlled.
Hot water is only useful when it enters the distribution pipework inside the home:
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Cost of Heat
Heating equipment needs financing, designing, building, operating and maintaining. The lifecycle
cost of useful heat includes these costs and the cost of billing and support for retail consumers:
The [total] lifecycle cost of heat must consider all of costs outlined above
Lifecycle Analysis (LCA)
A lifecycle analysis was built as a Microsoft Excel workbook in order to explore the key drivers of cost
and carbon emissions associated with heating. It considers three technologies, which can have a
low/medium/best case for each input variable, and allows three scenarios to be created:
Excerpt from the Lifecycle Analysis spreadsheet’s Input “Assumptions” tab
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Where a technical calculation is required to justify an input variable this is calculated in a standalone
sheet. (this includes working fluid specifications, load profiles and system sizing information)
Excerpt from the Lifecycle Analysis spreadsheet’s “Calc - Generating Heat” tab
The output “GHG and Cost Analysis” tab takes the scenarios and calculates the lifecycle cost and
carbon emissions in terms of £/MWh and kg CO2e/MWh for a particular scenario, and is presented in
the same format as the Cost of Heat illustration shown earlier:
Excerpt from the Lifecycle Analysis spreadsheet’s Output “GHG and Cost Analysis” tab
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The output “Scenario Analysis” tab will compute all three scenarios for all three technologies and
generate a chart for lifecycle cost and carbon emissions including breakdown by area:
Lifecycle analysis showing £/MWh and kgCO2e/MWh for useful heat
The assumptions behind the scenarios depicted above are extensive and can be explored by studying
the LCA workbook in detail. The key assumptions that were varied in these scenarios were as follows:
Scenario 5G Heat Network Individual Gas Boiler 3G Heat Network
Expected
Homes use
6,000 kWh/yr
£2,000 contribution
50 Homes
10% cost of capital
No RHI
12-monthly service
5-yearly breakdowns
10 year life
82.5% efficient
500 Homes
6% cost of capital
£6,000/home build cost
60% CHP @ 38% elec
Scenario 1
Homes use
6,000 kWh/yr
20 Homes
10% cost of capital
No RHI
10-monthly service
4-yearly breakdowns
8 year life
78.5% efficient
250 Homes
10% cost of capital
40% CHP @ 34% elec
Scenario 2
Homes use
9,000 kWh/yr
50 Homes
6% cost of capital
2.5p/kWh RHI
24-monthly service
6-yearly breakdowns
15 year life
86.5% efficient
1,000 Homes
6% cost of capital
80% CHP @ 40% elec
Justification of Counterfactual for LCA
Why choose 20-50 home developments with low energy density that consume 3-9,000 kWh of heat
per year? This is the toughest scenario, both technically and economically, for a heat network to
compete with individual gas boilers.
The answer is because these scenarios represent what we believe is the mass market for heat
networks, after the “easy wins” in large scale urban redevelopment and rehabilitation of existing heat
networks are taken, as the following charts illustrate:
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Technical
Annual gas consumption for homes (and
approximately 2 million businesses) using
under 72 MWh/year via Ofgem TDCVs.
The present-day mass-market is 7-13,000
kWh/year; equivalent to a heat demand of
5.6-10,400 kWh/year at most.
Heat loads will fall over time as housing
stock is improved: so 3-9,000 kWh/year is
the domestic heating market of the future.
The social housing (smaller) and new
builds (more efficient) markets are already
3-9,000 kWh/year at a density of around 35
homes per hectare.
Addressing these mass-market heat loads allows economic replacement of 1 million individual gas
boilers in the low deployment case and 10 million in the high case; saving 1-10 MtCO2e/yr by 2040.
Commercial
Buyers for 25% of the annual UK domestic heating system market are single decision makers who buy
more than one heating system at a time. They are social landlords who buy 250,000 boiler
replacements (English Housing Survey: 16 yr replacement cycle) and developers who buy 145,000
boilers for new homes (DCLG: 2013) each year.
These decision makers tell us that their priorities are: the lowest lifecycle cost of heating for social
landlords and lowest capital cost for developers. They also tell us that they need packaged solutions
for heating 20-250 homes at a time and this fits DCLG planning data, with the average development
being 55 homes in size:
Even larger developments are usually built out or refurbished at 50-100 homes/phase. A modular
solution that is suitable for 20-50 homes at a time will cover virtually all developments and
refurbishment projects; leaving individual home solutions to cater for the balance.
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Discussion of Insights from LCA
Very low distribution losses make 5G networks suitable for a wide variety of developments. Even
suburban homes to the passive house standard that consume just 3,000 kWh/year at a line heat
density of 0.2 MWh/metre/year can be served economically and efficiently by 5G networks. At around
6,000-9,000 kWh/year and 35 homes/hectare, which is the “difficult to decarbonise” low density urban
and suburban sector the commercial and technical case for 5G heat networks is excellent.
Efficient hybridisation of gas boilers with heat pumps provides the primary efficiency savings vs.
gas boilers. By running heat pumps for baseload at very low temperatures and relying on gas boilers
for peaking the 5G network can obtain seasonal COP of over 4 from air source heat pumps. The
hybridisation would require minimal, if any, reinforcement of the electricity grid; the LCA shows a 5G
network can supply 65-85% of annual heat demand using a maximum of 0.6 kWe per home.
A 5G network’s efficiency is not sensitive to network layout and heat load within the limits the target
market imposes: losses are an order of magnitude smaller than heat deliveries. Nor is it sensitive to
heat load profile or heat source efficiency within the limits informed by the Phase 1 Feasibility Study.
Competing gas boilers efficiencies are similarly unaffected by heat loads.
A 5G network’s commercial viability is sensitive to current assumptions and unknowns. Heat load,
developer contribution, cost of capital, and renewable subsidies/carbon taxes have the largest impact.
Competing gas boilers are sensitive to heat load, maintenance, and life expectancy.
Heat load per home dominates individual gas boiler costs. Heat load per energy centre dominates
5G network costs. Serving a larger number of more efficient homes improves the economics of 5G
networks, which earn their financial return by reducing the maintenance and capital replacement cost
vs individual gas boilers.
At commercial cost of capital, 5G heat networks should perhaps be built with even lower cost, shorter
lived, components to optimise for overall lifecycle cost: halving or doubling 5G heat losses has little
effect on the economic or environmental case.
Embodied Carbon
Note: DECC has requested that an additional evaluation is carried out on the embodied carbon
associated with the installation of the proposed technology vs. the counterfactual. In the case of a 5G
heat network this would mean embodied carbon in the entire individual gas boiler supply chain vs. the
entire heat network supply chain. This is a very substantial piece of work.
The current version of the LCA does not yet consider embodied carbon. A cursory examination is
sufficient to show that for long life assets the operating phase dominates the CO2e emissions (an
example for the distribution pipework is included in the LCA to show that it represents <1% of the
lifecycle CO2e emissions), and as these are likely to be similar/equivalent for both 5G heat networks
and the counterfactual individual gas boilers (plastic gas pipe = plastic heating pipe; gas boiler = heat
interface unit etc) they were considered inconsequential as far as the lifetime carbon per unit of
delivered heat is concerned and could therefore be neglected. A cursory estimate of embodied carbon
for both solutions will be added to the LCA for Phase 3. This will be evaluated to the nearest order of
magnitude in order to discount embodied carbon as immaterial and will be included for completeness
only. (refer to other references if firm figures on embodied carbon is of principal/material interest)
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Interim Results
Operating Platform
A purpose-developed operating platform is currently being used to manipulate loads on a downsized
network in real life whilst delivering additional benefits such as fully automated commissioning and
integrated retail utility metering/billing/payment collection and account management to tackle the
non-technical costs associated with delivering heat networks. Bar the documented issues with
automated commissioning (radio/radiator valves) this was successful, with even the initial predictive
control algorithms having proven surprisingly resilient in production, and is now being commercialised.
Hardware Performance
For the period between 27/03/2016 and 31/03/2016 when fairly complete room temperature data and
radiator flow control finally became available, the headline figures are as follows:
Gas boiler efficiency 89.5% gross (40 kW @ 50-60F/40-50R)
Heat pump COP 3.6 (10 kW @ 35F/30R to 45F/40R)
Distribution losses 11% (equivalent to ~300 kWh/home/year on
homes using 3,000 kWh/year with 10
metres of heat main per home)
Pumping cost 0.4% (kWh(e) per KWh(th) delivered)
Compared with the LCA the boiler efficiency and heat pump COP are at the low (poor) end of initial
estimates. Distribution losses and pumping cost are at the low (good) end of initial estimates. This is in
spite of abnormally low heat loads due to the nature of the residents and an effective void rate - empty
properties and those without prepayment credit - of 30-50% as previously outlined.
Raw electricity usage for all 24 flats and the energy centre is as follows:
Item Consumption
(kWh/day)
Type of Use Per flat (kWh/year)
Main pump 1.0 Basic network 17
Boiler 0.15 Basic network
Boiler circulator 0.05 Boiler heat 11
Energy Centre
Controls
0.7 Boiler heat
Heat Pump 26.0 Heat pump heat 410
Heat Pump Circulator 1.0 Heat pump heat
Server and Internet 3.2 Operating platform 140
Heat Main 1 3.0 Operating platform
Heat Main 2 3.0 Operating platform
32

COHEAT Ltd
The base electricity use compared extremely favourably with individual gas boilers - 10x lower - and
the benefits of central pumping and direct connected space heating circuits are clear to see.
The relatively high electricity use for the operating platform reflects no effort having been made to
optimise these prototype designs for electricity consumption, yet is still comparable with individual gas
boilers (175 kWh per home per year) even in this “no effort made” scenario. More efficient user
interfaces (touchscreens) and reductions in stepper motor holding currents would make a significant
dent in the electricity consumption of heat mains, and a local full blown rack mount server would be
wholly unnecessary in a production design.
The eagle eyed reader will spot a boiler quoted as operating at 40-45°C inlet and 50-60°C outlet
temperature. The high inlet temperatures are due to preheating the buffer vessel using the heat pump.
The variable outlet temperatures are due to the boiler’s inability to fire on demand and reach a stable
outlet temperature within a reasonable time, forcing it to be operated at a higher temperature than we
would like in order to guarantee at last 50°C to the heat mains at all times. The same reader will also
spot a heat pump quoted as operating from 30°C inlet temperature and upwards. This is due to the
issues with radiator valves and the limited balancing achievable using the original lockshield valves
that are still fitted to 12 of the 24 properties.
Thus far the assumptions in the Phase 1 LCA appear correct: the network is performing as predicted.
These interim results show that even low heat density sites can be served efficiently by heat networks
using low operating temperatures and the downsized pipework enabled by smart control technology.
Consumer Acceptance
Do consumers accept domestic hot water delivered at 42°C? In the main yes. Thus far only one
request has been made for hotter water and at the kitchen tap only. In homes with dishwashers this
would be a non issue. In homes without this could be served with a “boost” button on the user
interface: it is entirely possible to deliver at 45-48°C with a primary flow temperature of 50C, provided
that the flow rate is relatively low, as it would be at a kitchen tap.
Do consumers accept 55°C space heating flow temperatures with radiators? In limited circumstances
yes. When presented with pure time-clock heating controls with no predictive/optimum start capability
consumers will complain that the home takes too long to heat up and this is the fault of the radiators
that “aren’t hot all the way to the bottom.” When presented with time-clock heating controls with
predictive/optimum stat capability the reheat period is generally a non-issue.
The exception is when the consumer wants to “boost” the heating and here having radiators that
“aren’t hot all the way to the bottom” is perceived as a fault. This says a lot about how poorly the
majority of individual gas boilers that form the consumer’s benchmark are commissioned.
COHEAT had anticipated this and had intended to “fast fill” radiators using the electronic actuators if a
boost request was received - a radiator that quickly fills completely with 55°C water is considered hot
and has the reheat performance of a radiator 70/40°C - but were unable to do so due to limitations
with the radio/radiator valves. Further work on radiator valves and control strategies to appease the
UK consumer is needed in order to avoid spending more on handling phone calls from consumers who
do not appreciate the benefits of operating radiators at 55°C flow temperatures. Some consumers also
complain that radiators become cool once the setpoint is reached, but this generic failure to
understand what a thermostat is for applies equally to all heating systems not just 5G heat networks.
33

COHEAT Ltd
Issues Encountered and Lessons Learned
Utility Supplies
Installing a new commercial gas supply took 3 days. The paperwork to install a new commercial gas
supply took 3 months. This would have taken far longer had it not been for the efforts by National Grid
to expedite this on our behalf. Installing a telephone line took 30 minutes. Persuading the (private)
Post Office to give the 15 year old building a postcode and waiting for BT OpenReach to update their
postcode database so that the Broadband provider could actually book an installation took 30 days.
Fortunately mobile telcos are now able to compete with BT OpenReach.
There are too many parties performing too many sequential, batch-processed, administrative tasks in
these regulated industries. This is a barrier to the rapid, efficient, deployment of infrastructure at scale.
Contractors digging holes, laying cable/pipe, and filling holes back in again are pretty quick and slick.
Procurement
Buying screws and radiators is straightforward. Competition in the marketplace means that anybody
can quickly access good service and fair terms. Buying heat network products and services can be
slow (negotiating price on application is a waste of time for what are often commodity products), risky
(proprietary components and fittings cannot easily be substituted when a supplier fails you on service
level), and fair terms can be completely inaccessible. (ranging from extreme price-gouging on small
orders to outright refusal to supply new entrants and/or products sold in other parts of the EU)
COHEAT did find manufacturers and service providers prepared to offer good service at fair prices,
even to small accounts, but we were also failed by suppliers on more than one occasion and wasted a
lot of effort on suppliers who had no intention of offering fair terms. Relationships with OEMs (not
distributors) and information sharing/collective bargaining will help address market power imbalance.
Occupied Retrofit
Installation of the heat network presented challenges ranging from Japanese Knotweed and a surprise
capped mine shaft through to an aborted installation due to a pair of promising young gentlemen
who’d been released from prison the day before and elected to steal a car to joyride into a wall and
steal cash for hard drugs to help celebrate this...in the flat that COHEAT were due to retrofit that day.
Choice of male friends aside; the residents proved very accommodating, especially as word of shiny
controls and endless hot showers spread. (market pull from solutions that consumers want in their own
home greatly aids access to properties) The good relationship that the contractors built initially
endures to this day. Construction sites are nevertheless challenging environments to work in so avoid
this where at all possible by “spending extra” to fabricate even the most basic of assemblies offsite.
Radiator Valves
COHEAT needed the capability to set a flow rate through a radiator remotely. COHEAT had assumed
that thermostatic radiator valves (TRVs) were proportional control devices and simply replacing the
sensing element with a linear actuator would achieve flow control. This was a the largest single
oversight on our part but one that we were able to work around using the controls.
At first glance textbooks (excerpt courtesy of TA Hydronics) suggest this type of proportional
behaviour over 0.5 mm of valve stroke:
34

COHEAT Ltd
TRVs are designed to function in conjunction with a balancing (lockshield) valve or presetting orifice.
This limits the maximum flow through each radiator and ensures relative flowrate is balanced between
radiators during reheat conditions when the thermostatic element is fully open. The flow limitation can
also be used to set absolute flowrate so that at a given differential pressure the radiator receives
exactly the right flowrate to match the desired heat output.
The limitation sets the flowrate when the room is a long way from setpoint and the controller is
saturated. The “linear” region of the valve sets the proportional gain when the room gets close to
setpoint. There is always an error with pure proportional control. This error reduces as the gain is
increased. To achieve close control of room temperature setpoint TRVs are designed with narrow
P-Bands and as it turns out often simply oscillate between “on” and “off” positions due to high gain
control instability and hysteresis in the mechanical systems. (i.e. they’re hysteresis controllers not
proportional controllers)
What is the valve stroke likely to be and is it realistic to expect any proportional control?
Let's take a big radiator: 1200 x 600 mm Type 22
Let's operate this at 70/40°C for ~1450 W at a flowrate of 41 litres/hour, or 55/35C for ~930 W at a
flowrate of 40 litres/hour.
Let's run it at a dP of 15 kPa. If we pipe them in 15 mm copper the pressure drop < 20 Pa/metre so we
can reasonably ignore it for runs < 50 metres, and the pressure drop across the radiator itself is also
negligible.
Kv = flow/(SQRT(dP)) = 0.11
This is a small valve. A Dafnoss type 013G0373 is one of the smallest TRVs available on the market.
An except from its datasheet is show below:
35

COHEAT Ltd
This says that for Kv = 0.34 the valve stem moved 0.5 mm. The largest radiator at full output will be
preset to approximately 4.5, so the full stem travel of from zero flow to the maximum flow encountered
in the largest radiator in the system at full output is of the order 0.3 mm.
Because return temperatures drop as the heat load reduces, the deltaT increases and a realistic
flowrate for much of the heating season in an entire new build apartment apartment is <10 litres/hour.
This is a Kv of under 0.04 for the entire apartment. Stem travel to achieve this is under 0.125 mm.
Even with these small valves the precision required to achieve meaningful open-loop flow control was
beyond the capabilities of the low cost actuator heads specified by COHEAT.
In practice COHEAT actually installed “standard off the shelf” TRVs which had even higher Kv values
and absolutely behaved as on/off valves. The radiators were therefore commissioned manually by
adjusting lockshield valves to achieve a maximum flowrate as measured by the heat meter. This
balanced relative flows between the radiators and the 5G controls could then use a combination of
master flow rate into the dwelling controlled by HIU, plus on/off control of each radiator, to set the
average flow rate into each radiator over time as required to implement full individual room zoning.
This is less than ideal and requires further R&D if true automated remote commissioning at individual
room level is to be achieved at low cost. “Assisted-commissioning” might be a more accessible goal
where data from the HIU is used to help set then verify a manual control valve.
The best commercially available solution at present is a low kV TRV body that’s integrated with the
radiator and preset offsite to the flow rate for that size of radiator. You can then control the comfort
temperature using one of:
● Vapour filled head (e.g. Danfoss RA2000) - consumer/maintenance proof
○ Provides robust independent temperature control (but not independent time control)
● Local electronic head with built in sensor (e.g. Danfoss Living Eco) - fully flexible but a maintenance liability
○ Requires batteries, wireless pairing etc that make it unsuitable for social/rental housing
● Remote electronic head and local sensor - fully flexible and robust but costly upfront
○ Use remote electronic zone valve(s) on UFH manifold plus room sensors for time/temperature control
● Nothing - rely on presetting valves for hydraulic balance plus central thermostat and open-plan living
○ Embracing single zone time/temperature control is a sensible approach in well insulated builds
With direct connected space heating there is then no need for the primary valve in the HIU to
modulate. Indirect connected space heating still requires a precision modulating primary flow control
valve with sufficient control authority to modulate primary flow at the rates encountered, but at the time
of writing no indirect HIU comes close to the performance of a direct HIU at single-dwelling scale.
36

COHEAT Ltd
Sensing and Radio
COHEAT needed the capability to set a flow rate through a radiator remotely and to sense conditions
within the room.
Mains powered actuators with hardwired room sensors would have made the pilot simpler but were
rejected as a commercial dead-end: running mains and data cables to each and every radiator is
unrealistic. Furthermore developing with these would not have furthered our understanding of the
control strategies needed to work around wireless devices that aren’t in constant communication.
Many electronic radiator control valves are now available. Almost all of these receive a room
temperature request via radio then implement a local heating control strategy in order to achieve the
set room temperature. This design makes it impossible to set a flow rate directly and the major
manufacturers proved not in the slightest bit interested in collaborating or exposing lower level control.
OpenTRV are a company developing open-source hardware and software to control radiators better,
improve comfort, and save energy. The FHT8V is a low cost commercially available radio controlled
electronic radiator valve actuator that OpenTRV have reverse engineered the communication protocol
for. OpenTRV had built circuit boards and software that could drive these actuators via radio in order
to develop heating control strategies for electronic radiator valves. These OpenTRV boards could also
measure room temperature, humidity, light level, multiple switches, and one-wire temperature sensors.
COHEAT worked with OpenTRV to develop a room sensor (REV9 board) and electronic radiator
control valve based on a lightly customised version of their basic circuit board and an FHT8V.
REV9 room sensor and FHT8V radiator valve actuator
There were concerns about the scale of the deployment: 14 base stations and 120 sensors, each of
which was effectively a base station for the 120 radiator valves, was by far the largest OpenTRV
deployment to date and the hard-coded protocol between REV9 their paired FHT8V module runs at
low baud rates leading to substantial risk of message collisions. These concerns were proven valid.
In addition: the prototype REV9 boards arrived late; a high proportion of boards required rework; a
hardware design error made them prone to brownouts; and as of March 2016 we were on firmware
version 5 having accessed almost every flat 5 times to perform the updates. The “£50,000” work
package has consumed well over two man years between COHEAT, OpenTRV, and Cambridge
Prototypes in addition to £15-25,000 in hardware, travel, and subsistence.
It was worth it in order to understand the challenges involved in deploying radio based solutions and
develop both an operating platform and control strategies to deal with bad data gracefully. COHEAT
will never use radio based solutions for any critical heat network infrastructure in future though.
37

COHEAT Ltd
Improvement over time
COHEAT installed 120 REV9 boards across the site which communicated with 14 base stations, one
in each pair of Flats. By the the middle of October - 90% of devices were not communicating with their
base stations every day. With significant work between COHEAT and OpenTRV this has been
improved to 15% by the end of March with an average time between readings of less than 5 minutes.
The performance of the majority of boards on an individual basis has also improved.
This box chart shows the
range of the daily number
of messages received from
each individual Rev 9 board
for the month of October
2015. During the entire
month, 85% of boards
communicated at least
once. Apart from the first
few days when there were
a handful of radios on site,
no single board managed to
communicate every day.
This box chart shows the
improvement by the end of
March 2016. During this
period 85% of boards
communicated at least
once. (the remaining 15%
are in flats we were unable
to access) 75% of boards
are communicating
regularly on a daily basis.
(the irregular 10% were
communicating with an
unreliable base station)
Further details are included in Appendix 7 - Fun With Radio.
38

COHEAT Ltd
Tractability of Computations
Cost based heating optimisations using Model Predictive Control has been demonstrated for single
dwellings. (Nest, Tado, etc use this in production) These are generally of the form “when do I start
heating, and at what rate, in order to meet a tradeoff between primary energy use and indoor comfort.”
Complete heat networks have a more complex cost model with a larger number of variables that need
to be optimised. Computational complexity does not scale linearly with number of variables for Model
Predictive Control and even at just 121 zones solving a complete cost based optimisation in a single
model starts becoming intractable. To address this COHEAT developed an architecture for tackling the
problem that still allows network-wide optimisation but scales linearly in computation time with network
size. The solution is believed to be novel so details are redacted from this public-facing report.
Approaches from academic institutions with research interests in this area would be welcomed, as a
there is a significant amount of development work remaining in this area.
Costs – Budget vs Actuals
Budget overruns were accommodated through extensive unpaid overtime (4,500 hours budgeted vs
~7,000 hours worked, the value of which is indicated below) and Director loans into the company to
cover external expenses.
Line item Budget Actual Variance
Phase 1 - labour £28,650 £28,650 -
Phase 2 - labour
(paid)
£182,320 £182,320 -
Phase 2 - labour
(unpaid overtime)
- £101,300 (£101,300)
Phase 2 -
materials
£74,700 £94,350 (£19,650)
Phase 2 - travel
and subsistence
£2,000 £8,000 (£6,000)
Phase 2 -
subcontractors
£82,840 £75,065 £7,775
Phase -
overheads
£8,000 £8,000 -
Per Appendix 1 £450k would have been a more realistic budget for a project of this scope. This would
be equivalent to a day rate of £500/day inclusive of labour/material overruns vs. the £265/day charged.
39

COHEAT Ltd
Dissemination Activities and Peer Review
COHEAT adopted a continuous dissemination and peer review model for this project; setting up a
targeted, open, working group for district heating, organising public and private project
demonstrations, and presenting key learnings at events attended by district heating practitioners.
The ‘dhc-discussion’ Mailing List
COHEAT started the dhc-discussion mailing list for ultra-targeted dissemination and peer review:
https://groups.google.com/forum/#!forum/dhc-discussion
This is the electronic equivalent of a never-ending panel discussion between government, heat
network operators, equipment manufacturers, landlords, developers and other interested parties. It
now counts the technical leads from every major heat network operator in the UK, all the major heat
interface unit manufacturers throughout Europe, a number of major house builders, and every active
Phase 2 Heat Networks Demonstration SBRI participant amongst its (open) membership.
COHEAT has shared project failures and successes as they happened, sought and given technical
advice, and proposed collaborative approaches to improving standards in the industry via this list. This
bitesize, conversational, approach to dissemination has proven helpful by presenting a low barrier to
documenting findings whilst they’re fresh, quickly identifying which elements of the project are of most
technical and commercial value, and indeed helping us to understand/resolve issues as encountered.
With 200 separate discussion topics to date, some of which run to over 100 responses, dhc-discussion
is probably the most active technical working group on district heating in the UK at present. COHEAT
attributes this to the list’s open-membership/discussion policy: with no membership/conference fees;
minimal time commitment; and no moderation or discussion venue loyalty to a political position, paid
members, or commercial interests; it eliminates many of the barriers to productive exchange of ideas.
Public Events
A full day public overview and onsite demonstration of the 5G Heat Network was held at the pilot site
in Birmingham and sold out with 40 industry specialists and potential clients in attendance.
COHEAT also presented 15-20 minute overviews of the 5G heat heat network demonstration; key
lessons in data driven design (highlighting the importance of bypass flows, secondary system hydronic
balancing, and the right-sizing heat networks using actual load data rather than over-sizing using
legacy standards); and next generation instrumentation (using high frequency metering data to
measure Quality of Service to allow flow temperatures and bypass flows to be safely reduced without
compromising the consumer experience) at key events as follows:
● 5G heat networks (project overview) - RegenSW - September 2015
● Key lessons in heat network design (data driven design) - Energy4Power - November 2015
● (project overview and data driven design) - Arup lunchtime briefing - February 2016
● (data driven design) - Ecobuild - March 2016
● COHEAT 5G Heat Network Demonstration Day - April 2016
● (project overview and data driven design) - House Building Federation - May 2016
● Next generation instrumentation (measuring Quality of Service) - All Energy - May 2016
● (data driven design) UK District Energy Association AGM - June 2016
● 5G heat networks (design 101 and lessons learned) REMOURBAN briefing - June 2016
40

COHEAT Ltd
Private Events
COHEAT has given private tours of the pilot site (>6) and private presentations in person (>20), to a
number of potential clients and competitors/collaborators. The identities of these are covered by
non-disclosure but all were targeted and either commercially or strategically important.
Future Plans
COHEAT will continue to disseminate our technical research findings through the [dhc-discussion] list,
and via the appendices of this report, whilst ramping up more commercial marketing activities as
elements of this work are commercialised.
Public Events (planned)
2nd International Conference on Smart Energy Systems and 4th Generation District Heating
Aalborg, September 2016
Speaking slot. Disseminating the learnings from Phase 2 of this SBRI report.
Ecobuild Exhibition
London, March 2017
Dedicated stand. Releasing full-year operating results for Phase 3 of this SBRI project.
Open Standards
COHEAT are developing a number of open standards in conjunction with key stakeholders in the UK
and European district heating markets. One that we hope to release for public consultation in early
2017 is A structured cabling specification for heat networks - an excerpt is reproduced below:6
Foreword
This document outlines a structured cabling specification for the instrumentation and control of
heat networks at block level. The specification is designed to future-proof heat networks by
providing a clear, phased, upgrade path from M-Bus through to the Ethernet connected field
devices that the author believes will represent the future through to at least 2050.
Use of Document
The primary aim of this document is that specifiers and manufacturers for the UK market
contribute to and adopt this specification in order to accelerate the deployment of smarter heat
networks.
● It focuses on the structured cabling infrastructure that is prohibitively costly to change
once installed. (software functionality is cost effective to change after the event)
● It aims to avoid legacy technology lock-in by outlining a solution that is both cost
effective today and can support both legacy and future communication requirements.
● It aims to avoid a plethora of incompatible pinouts and terminations by, somewhat
arbitrarily, agreeing on some now.
The secondary aim of this document is to encourage those specifying heat networks - both
clients and operators - to consider protecting themselves from technology/vendor lock-in at the
design stage.
6
To be made available at Ecobuild 2017 and via dhc-discussion list
41

COHEAT 5G Heat Network Demonstration

COHEAT 5G Heat Network Demonstration

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