Challenge: Boost Efficiency of the Efficient

A top-performing dry-mill ethanol plant in Watertown, SD, sought even greater improvements in energy and yield. Glacial Lakes Energy LLC (GLE) operates this plant, which processes over 17 million bushels of corn annually, yielding 48-million gallons of ethanol and 140,000 tons of dried distiller grains (DDG).

By Staff January 1, 2006
AT A GLANCE
  • Multivariable predictive software

  • Energy savings 2-4%

  • Yield improvement 1%

A top-performing dry-mill ethanol plant in Watertown, SD, sought even greater improvements in energy and yield. Glacial Lakes Energy LLC (GLE) operates this plant, which processes over 17 million bushels of corn annually, yielding 48-million gallons of ethanol and 140,000 tons of dried distiller grains (DDG). GLE, formed in May 2001, by Glacial Lakes Corn Processors—an over-825 member cooperative—is highly committed to running the most efficient operations possible.

In fact, its South Dakota plant was named one of the U.S.’ most energy-efficient ethanol plants according to performance surveys of like-design facilities. With performance metrics high in the top quartile of energy efficiency for dry mill plants, additional improvements based on current infrastructure posed a challenge for the plant. It sought an advanced process control (APC) solution, aiming to further reduce energy cost per ton by 2-4% and increase yield by 1% on its dry-distiller-grains dryer.

GLE first conducted a benefits evaluation to understand the potential value of Pavilion Technologies’ APC solution: a targeted energy optimization and control approach to the plant’s DDG dryer, syrup evaporator, and thermal oxidizer. Analysis demonstrated that Pavilion’s dryer-control application—a multivariable, predictive, control-and-optimization software solution—could deliver the GLE-desired results, advancing the company’s leadership position in the DDG feed and fuel ethanol marketplaces.

The software claims to be the first commercially available dynamic, non-linear, multi-variable model predictive controller (MPC) and is widely applied in complex, multi-variable manufacturing environments. It combines steady-state optimization with model predictive control and manages process setpoints and transitions—creating significant operational efficiencies and recurring cost savings. Predictive control technology enables continuous optimization to drive installed equipment to its highest performance. By controlling the DDG moisture, it enables GLE to deliver even higher quality products and retain its high market share in the competitive DDG-feed marketplace.

Competitive edge

With the APC implementation, GLE expected to reduce moisture variability and increase DDG yield by 1% during all operating seasons. Plant analysis indicated a reduction in DDG energy cost as well as providing an additional margin of assurance with emissions limits.

GLE’s TO (thermal oxidizer) natural-gas flow and hotbox temperature vary from fall to spring.

GLE plant manager, David Culver, explains that APC continuously drives performance towards the highest return on every level. “Energy savings are significant even to the highest performing plants,” he says, “and I see several plant areas that could benefit from Pavilion’s APC solutions. With APC on our dryers, our operators can focus more on the fermentation process, which is where much of our profit is made or lost.” Culver added, “[GLE] has consistently shown good return to our shareholders through driving the highest efficiency from our people and facilities. We anticipate that the APC will add to our operational efforts and enable us to outperform peer facilities.”

Key benefits expected were:

  • Reduce energy cost 3%;

  • Increase yield 1%;

  • Reduce moisture variability;

  • Increase customer satisfaction; and

  • Achieve greater emissions control.

Update

At press time, in early December 2005, GLE had achieved project benefits in five months and expects project payback in less than six months. Results include:

  • Reducing energy cost (per gallon basis) by some 4%;

  • Boosting yield by 1%;

  • Lowering product variability; and

  • Improving thermal oxidizer emissions control.

Based on the first project’s success, GLE inaugurated a second control project for its distillation and molecular-sieve process to increase yield and reduce costs. The four-month project has achieved:

  • Added capacity of 3-10%;

  • Yield improvement of 0.1-0.2%; and

  • Energy use lowered 1-2%.

In response to the cited results, Culver said, “In just a year, we’ve seen an excellent return on investment from [the projects]. We control the distillation columns and molecular sieve processes, which are challenging to manage optimally and yet critical to achieving our operating objectives—more, high quality ethanol for less. Furthermore, we are able to continuously reduce our energy use. And in today’s marketplace being able to produce more ethanol at higher yields equals real money.”


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