Seminar - Become a BTU Tracker: Leverage Data Analysis for Energy Conservation
On Thursday, August 15, 2019, Lisa Zagura and Julianne Rhoads, senior analysts at Cimetrics, hosted a webinar titled "Using Big Data Analysis to Increase Sustainability and Comfort in Buildings." The webinar was part of the International Institute for Sustainable Laboratories (I2SL) High-Tech Talks series and focused on a strategic approach to achieve energy savings and prevent or mitigate large-scale operational issues.
The presentation began by discussing the importance of data quality and reliability on outcomes. It then delved into typical high-value controls, mechanical, and operational faults, and how they can impact building performance and energy consumption.
The heart of the webinar revolved around the application of big data analysis in lab buildings. The speakers emphasized the collection and integration of large volumes of data from various building systems, including HVAC, lighting, and laboratory equipment. This data, typically sourced from sensors, meters, and Building Management Systems (BMS), was integrated into a centralized platform to enable comprehensive monitoring.
Using big data analytics techniques, the system identifies patterns and anomalies indicative of equipment faults or inefficiencies. Machine learning models can learn normal operational behavior and flag deviations in real time, enabling proactive maintenance before faults escalate.
The webinar highlighted implementing automated Fault Detection and Diagnostics (FDD) tools tailored for lab buildings, which can pinpoint specific issues like air handler malfunctions, temperature irregularities, or excessive energy consumption. This detailed diagnostic information helps facility managers rapidly address problems.
By analyzing historical and real-time data, the system uncovers opportunities for energy savings, such as optimizing HVAC schedules, balancing airflow, or adjusting setpoints to reduce consumption without compromising lab conditions.
The webinar concluded by emphasizing the importance of continuous monitoring and feedback loop, which drives continuous operational improvements and energy reductions over time. User-friendly dashboards and reports were demonstrated as essential tools for facility managers to understand issues quickly and prioritize actions effectively.
In a case study, the speakers used BMS data from a 1.2 million square foot healthcare facility to demonstrate fault detection and data analysis procedures. The examples provided focused on air handlers and laboratory ventilation equipment, but the techniques were applicable to zone devices and plant equipment.
Julianne Rhoads, who has identified and helped to implement over $2 million in annual energy savings in more than 35 buildings, shared her experiences and results from implementing these big data strategies.
For I2SL members, free webinar registration was available by providing their membership username and password. Non-participants could still register for the webinar to receive a recording of it afterward. Forgotten usernames or passwords could be reset using the online form.
The webinar was a testament to how combining big data from multiple sources with advanced analytics enables early fault detection and targeted energy-saving measures in complex lab environments, resulting in improved building performance and reduced energy costs. The webinar was indeed an enlightening session for those interested in energy efficiency and building management.
- Big data analysis, as discussed in the webinar, involves collecting and integrating large volumes of data from various building systems like HVAC, lighting, and laboratory equipment, enabling proactive maintenance and identifying patterns indicative of equipment faults or inefficiencies.
- Data-and-cloud-computing technology plays a crucial role in this process, as large volumes of data are sourced from sensors, meters, and Building Management Systems (BMS) and integrated into a centralized platform to facilitate comprehensive monitoring, machine learning, automated Fault Detection and Diagnostics (FDD) tools, and user-friendly dashboards.
