District Heating systems are
transforming and User Performance
is becoming critically important
High temperatures and losses
Single / Few heat sources
Lower temperatures
Multiple, different types of sources
Users of District Heating
dictate temperature
requirements:
Forward temperatures often have unnecessarily high margins.
Return temperatures are often higher than desired,
leading to higher heat losses and lower heat source efficiency.Impacting overall system efficiency.
District Heating
companies want to:
Identify underperforming users with dominant negative impact on system efficiency.
Take direct action in negotiating improved behaviour or even directly “throttle”
the system to reduce negative impact.
How do you maximise the
performance of your
heating customers?
How do you unlock and visualise user data?
How do you define actions with positive RoI?
How do you start with active user control?
How do you use data and controls to optimise the system end-to-end?
How do you get started? Where and when?
Integrate data and insights
in one platform to improve
your users performance
Create insight on heat demand
and heat transport in the
entire network
Visualization of all measurement points in a network; up to thousands of sensors in one real-time overview
Intuitive heat maps to quickly view bottlenecks and opportunities
Zoom in and compare user performance for temperature, flow and pressure
Live and historical analysis by full network replay mode
The Gradyent Digital Twin
captures all meter data in one
interactive intuitive visualization
View patterns and anomalies for the full network, revealing where and what to improve
Dedicated dashboards that support analyses of hundreds or thousands of users
The Digital Twin rates and optimizes each remotely controllable (user) substation individually in real-time, resulting in an optimal valve setpoint that can be used to improve total network performance.
Forward temperature analysis reveals under- or overheated or customers
Analysis on the heat flows in the entire network show which users can do with lower forward temperature, or where contractual obligations are at stake
Return temperature analysis shows bad delta T’s and bottlenecks
Studying delta T per user shows where performances are bad, causing large flows in the network, resulting pressure bottlenecks and low network efficiency
Live dashboards for each customer show which users are deteriorating the network efficiency
Automated identification of worst performing users
Deteriorating the full network performance.
Dashboards per individual user
That provides full detail over current and historic performance.
Benchmarking to other users
Of the same type and the averages of the full network.
Deliver actionable insights
for campaigns on improving return temperatures
Let’s upgrade your District Heating grid
Ready to optimise, decarbonise or grow your grid? We would love to set up a call, a meeting or give you a personal demo of our real-time Digital Twin Platform.
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know about Gradyent
and District Heating?
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