Energy Management

Your questions answered: Improve industrial facility energy management: a process-based approach

Presenters from the Oct. 13, 2020 webcast “Improve industrial facility energy management: a process-based approach” addressed questions not covered during the live event.

By Ram Kaushik October 19, 2020
Courtesy: Schneider Electric

With new standards and aggressive initiatives for continuous energy management and sustainability reporting, industrial facilities are seeking ways to gain improved energy use. Isolating areas of energy waste and improving energy management capabilities enables facilities to achieve efficiency, cost savings, improved operations and sustainability. However, with so many disconnected processes, equipment and systems in an industrial facility, achieving a holistic and integrated energy management program is challenging.

This presentation demonstrates an approach that integrates the machine assembly system closely with the facility energy and power management system (EPMS), leading to improved process energy efficiency. Selected project deployments and their associated returns on investment also are discussed.

Ram Kaushik, U.S. offer manager, Digital Power Division at Schneider Electric tackled unanswered questions from the Oct. 13, 2020 webcast: Improve industrial facility energy management: a process-based approach.

Question: Do you plan to start using regression analysis and CUSUM?

Ram Kaushik: Yes. Definitely. Regression analysis and tracking of cumulative sums of energy efficiency gains are a key part of the modeling tools we are incorporating into our tools.

Q: How do you define the degree of detail that should be applied for the initial process survey to avoid expending more in the survey effort than the actual energy savings?

Kaushik: Great question. No magic bullet here, but some best practices are to quickly identify what “not” to waste time on, – e.g., low energy consumers, fixed cost energy, etc. Also, identifying the “how” is important, e.g., can we get access to process state data through the simplest low-tech methods or will it take a lot of effort?

Q: Any reason you do not use recommendations of international performance measurement and verification protocol (IPMVP)?

Kaushik: Great question. Yes, no problem there. We can certainly use IPMVP for the measurement and verification (M&V) reporting methodology as part of an ISO-50001 program.

Q: As presented, one of the most important savings is getting from the process optimization. In this matter, does Schneider provide specific technical support to process optimization in different industries?

Kaushik: Yes. We do advise thorough energy audits, site walkthroughs and consulting services. It is important to emphasize that for us to be successful, we need strong committed stakeholders at the customer organization who understand their processes and systems well.

Q: On one slide, you noted energy meters versus power quality meters. Why the difference?

Kaushik: Good question. Lower cost energy meters may suffice for some applications, but at key electrical points (mains, critical processes, etc.), this is insufficient. We need to measure important power quality metrics like harmonics, transients, etc. This is not “directly” related to energy savings, but we should stress that poor power quality can easily dissipate what we save through energy efficiency programs. We find this problem at a lot of customer sites, so this needs more educated customers for sure.

Q: What is the first step to integrate the correct solution?

Kaushik: A good site assessment to identify the top energy consumption processes or machines, identification of key performance indicator (KPI) metrics and the state of the plant in terms of metering infrastructure.

Q: Where can I find information on the monitoring hardware for implementing energy management?

Kaushik: I will speak for Schneider Electric, but many other vendors have similar sites.

Q: Legacy systems may have many challenges to incorporate the latest artificial intelligence (AI), machine learning (ML) and Industrial Internet of Things (IIoT) products. How can this be handled?

Kaushik: Excellent question. We struggle with this aspect ourselves in our projects because this is always a tradeoff. Replacement with the latest technology is not always feasible. The key is to focus sharply on how much data is just enough. Retrofitting with hardware may be necessary in some cases, but as long as software can get access to the data needed to calculate the KPIs we need, it is good enough for a start. We can always iterate again to add data, but it is important to start somewhere and not get overwhelmed with complexity at the very beginning.

Ram Kaushik
Author Bio: Ram Kaushik is U.S. Offer Manager at Schneider Electric’s Digital Power division. He has more than 25 years of experience in technical and business roles in engineering, information technology and software development.