How Can Energy Savings Be Accurately Determined?
Achieving meaningful energy savings requires a structured approach that starts with a thorough understanding of a building’s existing energy performance. The key lies in establishing clear principles and systematically mapping the current situation. From a technical perspective, this involves conducting a comprehensive assessment of the building, considering factors such as the year of construction, total square footage, floor layouts, and the types of installed systems, including heating, ventilation, and lighting.
Only by gaining a precise understanding of a building’s current state can opportunities for energy savings be effectively identified. By leveraging real-time data and insights, organisations can make informed decisions about optimising energy efficiency.
The Role of Sensors in Energy Optimisation
When smart sensors and IoT devices are integrated into a building’s infrastructure, they provide invaluable real-time data that enables continuous monitoring and performance optimisation. These sensors track various metrics such as temperature, occupancy, humidity, and energy consumption, allowing for a data-driven approach to reducing waste.
A crucial step in achieving measurable energy savings is accurately recording baseline energy usage. Establishing a well-defined reference point ensures that the impact of specific interventions—such as adjusting heating schedules, upgrading insulation, or implementing automated lighting controls—can be effectively measured. This approach ensures that energy reduction strategies are both targeted and impactful.
Case Study: The Smarter Buildings Pilot Project
The Smarter Buildings pilot project has been actively monitoring energy meters and sensor data for over six months to identify inefficiencies and unlock energy-saving opportunities. The findings from this initiative have provided valuable insights into energy usage patterns and cost-saving measures.
Benchmarking: A Crucial Perspective
To assess performance, the energy consumption data from the Smarter Buildings pilot site was compared with Statistics Netherlands (CBS) benchmarks. One of the most striking findings was the high gas consumption and its associated costs. A secondary benchmark analysis, which examined both gas and VGM (service) costs, revealed that service costs were 64% higher than the benchmark average. In contrast, electricity consumption and costs were significantly lower than the benchmark values.
Annual Costs per m² (EUR, ex VAT):
| Category | Benchmark | Smarter Buildings Pilot |
|---|---|---|
| Electricity Costs | €6.69 | €5.10 |
| Electricity (kWh/m²) | 55.05 | 31 |
| Gas Costs | €5.06 | €14.15 |
| Gas (m³/m²) | 12.95 | 21 |
These insights provided a starting point for further investigations into potential energy-saving measures.
Electricity Usage: Heatmap Analysis
To gain a deeper understanding of electricity consumption, a heatmap was generated to visualise hourly usage over a typical week. The analysis revealed a conventional office usage profile, with energy consumption peaking during business hours (9:00 AM to 7:00 PM) and dropping to around 25% during nights and weekends.
However, an unexpected anomaly emerged—at 1:00 AM, electricity consumption unexpectedly doubled from its baseline level. This raised a critical question: what was causing this surge in energy use during off-hours? Investigating and addressing such anomalies presents an opportunity for incremental but meaningful energy savings, even in buildings where electricity consumption is already relatively low.
Gas Consumption: Identifying Waste with Scatterplots
Gas consumption was analysed using scatterplots that compared usage against outdoor temperatures. Ideally, colder weather should correlate with increased gas consumption as heating systems compensate for lower external temperatures. However, the analysis revealed a significant variation in gas usage that did not align with temperature fluctuations.
A red-circled data cluster in the scatterplot highlighted instances where gas consumption remained high even during warmer periods. This pattern suggested energy waste due to unnecessary heating, which not only increased costs but also compromised indoor comfort levels.
Optimising boiler operations, adjusting heating schedules, and implementing more precise climate control strategies presented clear opportunities to reduce gas consumption and associated costs.
Measure to Manage: Unlocking Quick Wins
By systematically establishing clear baseline principles, energy-saving opportunities can be effectively measured and leveraged. Quick wins—also known as “low-hanging fruit”—often yield rapid improvements with minimal investment.
For instance, addressing inefficiencies in heating and cooling schedules, optimising lighting automation, and identifying energy wastage during off-hours can collectively contribute to substantial cost reductions. The Smarter Buildings pilot project demonstrated that proactive energy management can significantly decrease service costs while enhancing overall building performance and sustainability.
Conclusion
Accurately determining energy savings is a multi-step process that requires data collection, benchmarking, anomaly detection, and targeted intervention. By leveraging real-time monitoring tools, advanced analytics, and strategic energy management, organisations can unlock substantial cost savings while contributing to sustainability goals. The insights gained from the Smarter Buildings pilot project underscore the importance of a data-driven approach in identifying inefficiencies and implementing effective energy-saving strategies.
