Algorithm efficiency in a crude context

Hog fuel is a mix of bark, sawdust, and planer shavings.

With oil prices approaching $50 per barrel and natural gas prices near $6 per million British thermal units (Brus) (MMBtu), the need to reduce energy costs in paper mills is more important than ever.

Acting on any opportunity to improve the efficiency of existing process equipment, with little or no capital investment, is essential. For hog fuel boilers, improved control of the combustion process can happen by reducing the level of excess oxygen, which directly translates into improved boiler efficiency. Here are the operating issues.

Closed loop challenge

Hog fuel boilers are increasingly important in mill power plant operations. There are a number of boiler combustion zone configurations, such as moving grate, fluidized bed, and pile burning, to name a few.

The boilers typically provide three main functions to the operation: steam production, waste incineration, and electricity generation.

Meeting the steam header pressure demand is of primary concern. Depending on the heating value and water content of the hog fuel, it may be necessary to burn supplemental fuel to maintain the boiler in energy balance with the steam production demand.

Furthermore, some hog fuel boilers operate in "batch" mode, as they require daily hog feed outages to permit ash removal from the combustion chamber. Supplemental fuel is necessary during these outages as well. Optimal closed-loop control of the boiler throughout these wide operating modes is a challenge.

In Kraft mill operations, burning black liquor in the recovery boiler generates green liquor and a significant quantity of steam. Available liquor inventories can often dictate the steam production from the recovery boiler.

Package boilers fired by conventional hydrocarbon fuels such as gas and oil typically operate in a "swing" mode or on a demand basis to maintain the steam header at the desired operating pressure.

Advanced control can improve the ability to swing the hog fuel boiler and thereby reduce fuel costs associated with the package boilers. Beyond boiler control, additional major energy savings opportunities exist in the power and recovery area of mills.

Variability in the heat released by the combustion of the hog fuel often makes control of the hog fuel boiler and the entire steam header very challenging for the plant operators.

Hog fuel is a mixture of bark and biomass or sludge from water treatment operations. The heating value of hog fuel can change dramatically, depending upon the water content and the proportion of bark to sludge.

Northern mills can experience quite severe changes in the hog fuel quality during winter months of operation. Stabilizing the bark boiler operation and improving the overall boiler efficiency can by achieved by improved controls.

Matrix of dynamic relations

The overall control objective is to recover as much heat as possible from the flue gas in the face of continuously changing hog fuel feed quality. Achieving this objective results in greater steam production.

A properly designed advanced control scheme can manipulate the split of under-grate airflow to overgrate airflow to minimize the excess oxygen for changing hog feed quality. This excess oxygen minimization can take place while maintaining steam production at a desired target.

The simplified hog fuel boiler schematic has four handles, or manipulated variables, for control: the hog fuel feeders, the over-fire airflow, the under-grate airflow, and load burner or"under-grate air preheat"fuel flow.

Actual hog fuel boilers are fitted with multiple hog fuel feeder addition points as well as multiple air injection points, for both the over-fire and under-grate airflows. Depending on local environmental rules, other control loops may be present to maintain compliance.

This matrix shows the process relationships between the controlled objectives (rows) and the manipulated variables (columns), in an "open loop" or fully manual state of operation.

A plus (+) sign indicates a positive relationship between a pair of variables, and a minus (-) sign denotes a negative relationship. For example, a unit increase in the hog fuel feed rate will increase steam production at steady state, reduce excess oxygen, and increase the combustion bed level.

The heart of a model predictive control (MPC) application is a matrix of dynamic process relationships, which we learn through controlled plant testing, conducted in close collaboration with plant operations. A teamwork philosophy with operations during plant testing and control system commissioning leads to a better understanding of the control objective and ultimately better acceptance by the end user.

The economic opportunity for an MPC strategy is to maximize the efficiency of the boiler operation for changing hog fuel quality and load demand on the header. In practice, this happens by manipulating the split of over-fire air to under-grate air to continuously minimize the excess oxygen, subject to a high carbon monoxide (CO) limit.