Expert in BMS performance Analytics -- 2

Project Overview

We are developing an AI-powered analytics tool for heat network performance optimisation, using data from Building Management Systems (BMS), heat network controllers, and plant-level telemetry.

We are seeking a freelance specialist with strong experience in communal/district heat networks, BMS data, thermal plant controls, and network performance analysis to help us validate, interpret, and enhance our analytics features.

This role is for someone who deeply understands how primary/secondary circuits behave, how thermal losses occur, how low-carbon plant is controlled, and how data can be translated into operational improvements for heat networks.

We will start with a 8-hour pilot project to test your skills and suitability for longer-term work.



Responsibilities



1. Heat Network Data Interpretation & Insight Generation

Analyse heat network datasets (flow/return temps, delta-T, flow rates, energy meters, tariff meters, HIU performance, plant runtime logs, alarms, setpoints, weather comp, pump logic).
Identify performance issues such as:
High return temperatures
Poor delta-T across HIUs or plant
Pump over-circulation
Faulty stratification in thermal stores
Sub-optimal sequencing of boilers/CHPs/heat pumps
Sensor drift or control failures
Translate findings into clear, actionable recommendations for operators and into optimisation logic for our AI.


2. Validation of Our AI Recommendations

Review our current heat-network-specific AI outputs.
Evaluate accuracy, relevance, and operational value.
Suggest improvements to:
KPIs (e.g., network delta-T, plant efficiency, primary/secondary balancing)
Alert rules (e.g., abnormal return temps from specific risers/HIUs)
FDD logic (short cycling, pump curve mismatches, heat loss detection)
Optimisation pathways (flow temp reset, pump modulation, tariff-aware optimisation).


3. Heat Network Control & Plant Knowledge

Validate and enhance assumptions around:

Primary & secondary flow control
Variable temperature vs constant temperature systems
HIU behaviour & diagnostics
Thermal stores and buffering
Heat pumps, CHP, gas boilers, and sequencing logic
Pump modulation and differential pressure control
Weather compensation logic
Common field issues (air in system, blocked strainers, stuck 2-ports, incorrect HIU commissioning)
Highlight typical real-world failures and how the platform should detect, diagnose, or recommend interventions.



4. Collaboration & Reporting

Deliver findings in a structured format (template provided).
Communicate clearly with our product/engineering teams.
Be available for short video walkthroughs of findings.


Deliverables (Initial 8-hour Pilot Project to test skills)



1. Heat Network Data Review

We will provide 7 days of representative plant and network data.

You will produce a summary report containing:

Key findings
Operational and efficiency issues
Specific optimisation suggestions (plant sequencing, flow temp reset, circulation adjustments, HIU behaviour insights)
Recommended KPIs/alerts


2. KPI and Rule Suggestions

Propose at least 10 revised or new heat-network-focused KPIs, such as:

“Delta-T degradation from specific HIUs/zones”
“Return temperature consistently above target during low load”
“Primary pump over-circulation vs demand”
“Heat pump COP deviating from expected curve”
“Thermal store stratification failure”
“Boiler short-cycling condition”
“Abnormal network heat loss pattern”


3. Dashboard/Report Feedback

Provide suggestions for improving how our platform presents heat-network insights:

Plant overview
Network delta-T and flow maps
HIU-level performance views
Efficiency, loss, and balancing indicators
Daily/weekly operator priorities


4. Optional: Data Visualisation

(If you have experience with Power BI, Python, Niagara exports, or similar tools.)



Required Skills



Technical & Domain

Experience with heat network controls and plant operation
Ability to read and interpret:
Heat network trend logs
HIU performance data
Metering data (kWh/Wh, flow rates, temps)
BMS and SCADA exports
Exposure to systems such as Trend, Siemens, Schneider, Honeywell, Johnson Controls, Niagara, BACnet
Understanding of FDD, continuous commissioning, or optimisation methods for heat networks


Analytics

Comfortable extracting insights from noisy or incomplete data
Experience with Excel, Power BI, Python, or BMS/SCADA export tools
Ability to produce clear, defensible findings rooted in engineering fundamentals


Communication

Able to translate complex technical behaviour into actionable steps
Strong reporting/documentation skills
Clear communication with our product team and non-technical users




Pre-contract requirement:

Provide a detailed case study showing where you used heat-network or BMS data to deliver actionable insights (not design work).

Include raw data snippets, your method, and how you reached your conclusions.



Initial contract: 8-hour engagement

Expected hours: 8 total

Location: Remote (UK/EU time zone preferred but not essential)

High likelihood of repeat work: Yes — we will continue scaling our heat-network analytics and will need ongoing expertise.



How to Apply

Please include:

A summary of your experience with heat networks, plant controls, BMS data, or HIU performance analysis.
Examples of past work (heat network diagnostics, KPIs, dashboards, optimisation reports).
At least one detailed case study based on real operational data.
Your hourly rate or fixed price for the pilot.
Tools/platforms you are comfortable with (Niagara, Power BI, Excel, Python, BACnet tools, heat-network controllers, metering systems).