Short-Term Objectives

Evaluate the changes made in the previous 18 months, following the initial consultancy.

Assess the potential for further immediate improvements to increase the efficiency of the heat network.

Short Term Review

Over 9.2 million telemetry points were collected across 87 parameters, covering heat production, boiler runtime, and diagnostics, all within the period of November 2023 - April 2025.

This dataset, fed from the HVAC Ventana dashboard (via API) and supplemented with manual consumption records, is stored in an Azure SQL database and visualized using Power BI.

Each tab of the dashboard explores a specific dimension of system performance, such as seasonal trends, LPG reliance, ΔT (flow-return temperature difference), and data quality. Users are encouraged to interact with the visuals to drill into anomalies and compare behaviors across time and major windows.

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Efficiency & Reliability

Sustainability & Cost-Effectiveness

Enhanced Heating Solutions

System Dashboard Overview

This part provides a high-level summary of the Balgair District Heating System’s overall behaviour since 2019. It brings together key indicators including total energy production and consumption, seasonal shifts in network efficiency, and how often the boiler runs at low output.

It is designed to give users a fast snapshot of performance trends before diving into detailed analysis in later sections.

How to Use

Use the Year slicer (top right) to compare across years or focus on specific periods (e.g. 2023–2024).
Use Ctrl for multiselect on the slicers. For example , to select multiple years, hold ctrl and select the years.
Hover over bar charts and line markers to get exact values for biomass and LPG heat outputs and efficiency percentages.

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Key Insight

The seasonal efficiency chart shows how performance dips significantly in warmer months, while the load distribution highlights an unusually high share of time spent in the 0–20 kW band indicating frequent boiler idling. Historically, With 3,042 MWh produced and only 1,736 MWh recorded as consumption, the system’s average network efficiency sits around 56%, pointing to losses worth further investigation

This suggests immediate opportunities for control system tuning and targeted operational adjustments.

Production and Consumption Analysis

In here , the aim was to explore how heat production and consumption vary by year , season and building type, be it the clubhouse or in houses at the Balgair residential scheme.

Key Insight

Higher summer LPG use coincides with low system efficiency. In the production chart, note the clear seasonal shift where LPG overtakes biomass briefly during summer.

Viewer Tip

Filter by building or time to assess usage trends. Compare heat production against seasonal efficiency changes for insight into cost and carbon impact.

Consultancy vs Post-Report System Behaviour

This section contrasts the 2023 consultancy benchmark (based on data from 2016–2023) with updated performance metrics from the post-report period (late 2023 to early 2025). It evaluates changes in fuel mix, emissions, cost exposure, and RHI eligibility using consistent assumptions to enable direct comparison.

The consultancy reported an average network efficiency of 56%, biomass providing 92% of heat, and LPG at 8%, with annual emissions totalling ~19.96 tonnes CO₂e. Their financial estimate placed the total annual system cost at £79,537, driven by biomass fuel (£28,637), LPG (£5,268), maintenance and support services (~£26k combined), with a projected annual loss of £21,843 after RHI and heat sales were accounted for.

In the post-report window, updated telemetry shows a reduction in biomass share to 85% and a corresponding rise in LPG use to 15%. This shift increased annual emissions to 26.4 tonnes CO₂e and contributed to a higher financial loss of £31,345, even though system output remained stable at ~519 MWh/year and boiler efficiencies held at 84%. Network efficiency remains unchanged at 56%, indicating that distribution losses remain the system’s most persistent weakness.

Viewer Tip

Use the “Window” slicer to toggle between report_window (consultant benchmark) and post_report (your updated view).
Hover over the monthly and seasonal charts to explore where efficiency and biomass share dropped.
Focus on LPG Heat Share in summer months—it aligns with the emissions and cost surge.
Use “Heat Production by Period” to confirm that output has remained steady despite cost and emissions shifts.

Biomass heat share fell from 92% to 85%, leading to a 33% increase in carbon emissions and a significantly higher annual operating shortfall. While output stayed constant and boiler efficiencies remained strong, the system’s financial and environmental performance deteriorated due to heavier seasonal LPG use and unchanged distribution losses.

Implications on Annual Cost And the Environment

Metric	Consultancy (2016–2023)	Post-Report (2023–2025)
Biomass Share of Heat	92%	85%
LPG Share of Heat	8%	15%
Heat Output	519.3 MWh/year	519.3 MWh/year
Network Efficiency	56%	56%
CO₂ Emissions (Total)	19.96 tonnes/year	26.4 tonnes/year
LPG Emissions Share	72%	77%
RHI-Eligible Biomass Heat	412.3 MWh	380.9 MWh
RHI Payments (Tier 1 + 2)	£29,067.15	£28,267.22
Heat Sales Revenue	£28,888.18	£28,888.18
Estimated Operating Loss	£21,843	£31,345.16

KEY INSIGHT

Pre- and Post-HIU Window Analysis

Here, we evaluate the impact of Heat Interface Unit (HIU) upgrades that began in January 2025, as recommended in the 2023 consultancy report. Using telemetry data, we compare system behaviour before and after the intervention—focusing on ΔT performance and boiler load distribution.

ΔT, the temperature difference between flow and return, is a core indicator of heat transfer efficiency.

Viewer Tip:

Use the HIU_Window slicer to compare Pre-HIU vs. Post-HIU performance.
Hover over the ΔT line chart to inspect month-by-month system recovery.
Zoom into daily data granularity for further analysis on boiler responsiveness.
Study the Load Distribution visual to track changes in runtime behaviour across power bands.

Before the upgrade, the system averaged just 7.4°C, well below optimal. Post-upgrade, this jumped to 15.5°C, bringing the system in line with design expectations and signalling improved energy transfer across the network.

Boiler performance also improved. During Jan–Mar 2024, 34% of boiler runtime was spent idling (<20 kW). By Jan–Mar 2025, this dropped to 22%, while the optimal load range (60–150 kW) increased from 52% to 61%—reducing inefficiencies linked to short-cycling and low-output operation.

These improvements are expected to reduce LPG reliance, especially during peak demand periods. However, due to the lack of manually reported LPG consumption data for this window, we were unable to confirm the reduction quantitatively. This will be re-evaluated once updated fuel usage data from Enviroenergy is integrated into the dashboard but it is expected to support better boiler operation and, once fully validated with heat consumption data for these month , we are expected to reduce dependency on backup LPG heating.

Real-Time Diagnostics and Trend Monitoring

This section converts near real-time telemetry, previously limited to the HVAC interface, into a historical diagnostic tool. While the original dashboard supports moment-by-moment monitoring, it offers limited export functionality, making it difficult to review system behaviour over weeks or months.

By repurposing this telemetry data into structured Power BI charts, we enable zero-cost, retrospective monitoring of key parameters such as flow and return temperatures, pump speeds, buffer tank behaviour, and biomass combustion characteristics.

This allows Fintry Development Trust to validate the effects of engineering interventions (e.g. HIU upgrades), monitor seasonal system stress, and benchmark network-wide performance over time.

Viewer Tip:

Use filters to explore performance across seasons, weekdays vs weekends, or specific months.
Hover over the flow and return temp charts to track how heat delivery improved or degraded over time.
Review pump speeds (P3 and P4) to detect underperformance or overloading across distribution circuits.
Compare burning chamber vs flue gas temps to assess changes in combustion stability.

For example, flow/return temperature trends show improved network recovery in early 2025, correlating with the HIU replacements. Burning chamber and flue gas temperatures help assess whether reduced idling and improved ΔT are impacting combustion efficiency. Pump speed variations and buffer tank stratification offer further insight into hydraulic stability and storage utilization.

This tab unlocks previously inaccessible operational history. It transforms near real-time telemetry into actionable trends, at virtually no cost, allowing us to continuously track system behaviour over time, validate upgrades, and diagnose inefficiencies that would otherwise remain invisible.

Data Quality and Sensor Reliability Audit

Before running any serious analysis, we needed to answer one foundational question: which telemetry data can we actually trust? This section presents a full audit of all HVAC-linked sensors, highlighting the most reliable metrics and flagging those with persistent gaps, flatlines, or invalid values.

Each sensor was analysed by month using a custom scoring framework that evaluated:

Expected vs actual reporting days
Reading frequency (target: 288 per day for 5-minute intervals)
Flatline percentage (days with no variation)
Missing/invalid entries
Final usability score = clean, complete, non-flat readings

The resulting metrics were then aggregated to determine monthly reliability and long-term sensor performance across 84 parameters. This helps Fintry identify sensors worth trusting for analytics—and those that need inspection, repair, or replacement.

Viewer Tip:

Use the filters to explore reliability by sensor category, month, or specific parameter.
Review the Data Quality Over Time line chart to identify when overall system reliability improved or dropped.
Hover over the Bottom 5 Metrics chart to find problematic sensors affecting key subsystems.
Click on sensor categories (e.g. Buffer, LPG Boiler, Control & Demand) to isolate trends in each group and evaluate if recent replacements made an impact.

For instance:

Sensors like O₂ actual, ismaBMTemp, and district flow temps achieved 80–100% usability and are safe for time-series analysis and system diagnostics.
Others, like water meter, biomass backflow temp, and burning chamber temp were <10% usable due to flatlines or constant nulls limiting their value in trend tracking or consumption calculations.
Even where HVAC visuals display values, long-term analysis often reveals these were static or corrupted—especially for metrics like biomass hopper contents that intermittently drop to 1% without cause.

Going forward, we can use this to guide future sensor replacements, validate control logic inputs, and prioritise system repairs ensuring future analytics are grounded in dependable data.

Recommendations and Strategic Follow-Up

This dashboard builds on the 2023 consultancy report, which flagged key issues in Fintry's district heating system: high network losses, rising LPG use, and system losses.

Since then, targeted upgrades like the HIU replacements have improved some aspects (ΔT, boiler cycling), but emissions, LPG reliance, and cost issues remain. These recommendations aim to help Fintry sustain gains, address inefficiencies, and guide future engineering actions using evidence-based diagnostics.

System Control & Network Efficiency

The HIU and valve replacements in January 2025 have improved heat extraction at the household level. This is clear from the rise in average ΔT from 7.4 to 15.5 degrees and the shift in boiler load distribution, with less time spent at low output levels.

However, we can’t yet confirm their impact on overall network efficiency, since the latest consumption data from Enviroenergy isn’t available for this period.

To reduce heat losses across the 1,053-metre pipe network, we recommend trialling lower flow temperatures—closer to 70 degrees—alongside reduced pump speeds. This would help cut convective losses to the ground and could also reduce electrical costs associated with pump operation. The Real-Time and Pre/Post HIU dashboard tabs are already set up to track how return temperatures respond to these changes.

This approach follows established low-temperature network design principles and could help Fintry reduce thermal and operational inefficiencies without major infrastructure upgrades.

Fuel Cost & Emissions Management

Since the HIU upgrade, we’ve seen improvements like better ΔT and less boiler idling. However, LPG use has gone up. Biomass share dropped from 92 percent to 85 percent, and estimated annual CO₂ emissions rose from about 20 to 26 tonnes. Financial losses also increased, now exceeding £31,000 per year despite steady output.

To support local tracking, we’ve built an Excel tool that lets users enter fuel and cost data, apply emission factors, and automatically calculate RHI revenue, heat income, CO₂ breakdowns, and overall losses. This can reliably cover performance from 2024 through January 2025.

We recommend using this tool monthly to monitor actual system performance and guide budgeting decisions. Once updated Enviroenergy data becomes available, use it to verify fuel split by property and track trends into 2025 and beyond.

Data Quality and Telemetry Reliability

A major limitation to deeper analytics has been sensor quality. Several probes—particularly the hopper content sensor, backflow temperature, and water meter—show <10% reliability, with many flatlining for weeks at a time or spiking to unrealistic values like 1% in the middle of normal readings.

These distort the picture and make it difficult to trust certain metrics. We recommend prioritising replacement of these sensors. In the short term, noisy signals like hopper telemetry should be excluded from decision-making visuals entirely.

The Data Quality tab in the dashboard lets us track sensor performance by month, so it can also be used to confirm whether replacements are actually improving reliability.

Emissions/Cost Calculator

Document below lists out the rationale behind the calculations of emissions and runnning costs.

It also provides a template for making future calculations as future calculation change

Data Update

Telemetry data: Production data in dashboards is current up to April 2025, automatically updated via API

Manual consumption and cost data: Available up to January 2025
Further updates will be added once full consumption records and cost breakdowns are received.