Electrical equipment and appliance manufacturing
Managing energy across multiple facilities
An energy model to normalize baseline energy use and track energy savings resulting from improvement projects
A uniform methodology to measure and verify energy efficiency improvement at the facility and corporate level to help inform business decisions
Uniform Methodology To Measure Energy Efficiency Improvement
Schneider Electric developed a robust methodology for measuring energy use at its facilities in support of its corporate-wide energy savings targets. The methodology relies on a predictive modeling technique that adjusts baseline energy use to control for factors that impact energy consumption such as production and weather changes. As a result, Schneider is able to develop more accurate metrics to track progress against its goals. To date, the company estimates cumulative energy savings exceeding 30% throughout North America against a 2004 baseline for the sites in the program. Under DOE’s Better Plants Challenge, Schneider has achieved a 16% improvement from a 2008 baseline.
Like many large companies, managing energy activities across Schneider Electric’s multiple plants and sites proved challenging. There are several barriers involved, most notably large swings in energy data. The metrics barrier was particularly difficult to overcome as Schneider energy managers noticed large swings in raw energy data as production levels and weather changed from month-to-month and year-to-year. These “swings,” in many cases, were larger than the impact of energy-saving efforts. It was obvious that some kind of normalizing was necessary. Through the process, Schneider’s leadership now understands the importance of energy efficiency as an operations tool, much like safety, quality, and customer service.
Schneider Electric first set formal energy efficiency targets in 2004, when it asked its facilities to reduce energy use per employee by 10% over a three-year period. To drive the needed energy improvements, Schneider’s top management transformed an existing network of Facilities Managers into Energy Champions and challenged them with the objective of developing action plans to meet the targets. A few Facilities Managers received energy management training and began to share this knowledge throughout the company, resulting in broader internal subject matter expertise. Within one year, this network of Energy Champions worked with Schneider Electric’s internal experts to develop the predictive energy model for analyzing and tracking energy improvement projects and results. Four years later the team established best practices shared within the company. People who are passionate and willing to standardize and proliferate the processes are essential.
To help disseminate the energy model and best practices, the company centralized the Energy Managers (EM- formerly referred to as Energy Champions) of North America into one common reporting structure. This allowed the EM group to create energy-saving objectives for each direct report. Through the process, the group accepted the measurement and verification methods. The company developed a regression analysis tool (the energy model) to find the best correlating factors for each site that explained the variation in energy usage. The group also focused on increasing the energy project list to ensure that there were projects underway to meet objectives, and verifying that the expected savings aligned with modeled results after completion.
Implementing the energy model did require overcoming some challenges, such as educating plant management staff on energy-conserving principles and modeling methodologies. Another challenge was fine-tuning the results for variables too complex to include in the model, such as added shifts or overtime to accommodate short-term production increases. Change management is never easy. It is important to have education in place and consistent methodologies.
To support and monitor progress towards Schneider Electric’s energy goals, the Facilities Team tracks electric and natural gas consumption at facilities using a predictive modeling technique. This technique adjusts baseline energy use to changes in factors that correlate with energy usage, such as weather or production levels.
Schneider Electric developed a standard six-step approach to normalize energy data at each site and determine energy savings:
Tools & Resources
Schneider Electric now uses the Department of Energy’s EnPI multi-variable regression tool to normalize energy data and accurately measure and verify the value of energy savings from energy actions. The tool allows each site to be modeled individually in order to accurately depict and model energy data based on variables relevant to each site.
Most sites showed a strong correlation between heating degree days (HDDs) and gas consumption. Many sites showed a good correlation between cooling degree days (CDDs) and electricity consumption. Some manufacturing sites with significant painting processes may show a strong correlation to pounds of steel processed. In some cases, quadratic equations were used to account for non-linear relationships. Many variables were considered to identify those most statistically relevant. Statistical indicators such as p-value, R-squared, T-statistic, and standard deviation were used to analyze each variable. Schneider’s experience indicates that selecting the best model for a facility and the most relevant variables is often an iterative process.
Savings for the sites in the program have exceeded 30% compared to 2004. The company estimates that the average payback of energy projects is less than three years. Use of the energy model has been central to achieving these savings. The model is updated monthly and is a basis for monthly conference calls to review model results, track progress towards goals, and adjust planning for the next 12 months. These monthly discussions, based around the model, guide decisions on energy projects.
Results from Schneider Electric’s energy model are analyzed in monthly meetings held by energy managers to ensure accuracy. The results are compared to expected savings associated with energy projects and actual energy consumption as a validity check. The meetings also help focus and drive actions toward meeting annual energy goals and are used to educate staff on how to leverage best practices. This doesn’t happen in a silo. To truly be successful, the Schneider Electric community must continue to share across the enterprise and evolve to ensure continuous improvement. The energy program puts the same rigor into the process as is used to approach the award-winning safety program and other imperatives.
The chart below shows cumulative energy performance improvement since 2008 measured three different ways across the 34 U.S. facilities Schneider has enrolled in the Better Plants Challenge. The baseline period equals 100%, so the 84.37% shown under “normalized” data equates to about a 16% improvement in energy performance. This is the data Schneider reports publically through the Better Plants Challenge and other sources. For validation purposes, it also compares the normalized figure to a bottom up calculation (referred to below as “project list”) that sums the estimated savings from all the energy saving projects implemented across the company. Additionally, it checks a third data point, which is the “raw,” or absolute energy consumption at all sites. These checks are useful in providing additional confidence in the normalized results. Schneider is looking for the numbers to be in general agreement with one another—it does not expect them to be identical. If the metrics are not all moving in the same direction—for example, if the normalized data is showing an energy performance improvement while the raw data is showing an increase in energy consumption—Schneider takes that as a cue to investigate the data further. So far, Schneider has found that the numbers generally align with one another, and the metrics show greater convergence over time.