Editor’s Note: This article originally appeared in the July 2006 issue of Chemical Processing. A recent investigation revealed that this article was never posted to the Web site.Finding a way to coordinate the various steam and power generating facilities within the vast Eastman Chemical plant at Kingsport, Tenn., has been a key factor in reducing fuel costs while keeping up with plant demand. Until 2004, utilities operated more or less independently. Waste and inefficiency seemed to be unavoidable with an intricate, dynamic process.
The utilities site is comprised of four powerhouses with 17 boilers and 19 steam turbine generators capable of delivering an average of 3.6 million pounds of steam and 176 megawatts per hour to meet the demands of chemical process units and offices across this 1,000-plus acre site. Coal is the main fuel in the powerhouse boilers, except in three gas-fired backup boilers.
The powerhouse boilers also burn some waste materials produced in the process plants, such as bio-sludge, waste gas, and liquids. These types of wastes can complicate boiler operations because sometimes their heating quality can vary. A complex system allows boiler steam down from one level to another level through the turbine generators, pressure-reducing stations, and equipment turbine drives. The exhausts from these portions of the system can be switched between headers as explained in Figure 1.
Figure 1. Flow diagram highlights the complexity
With so many choices to be made, operators had an extremely difficult time managing the system economically. During a typical shift, they coordinated steam generation between four powerhouses operating with a wide range of equipment. Loads varied continually (Figure 2). Equipment operates in different ranges of efficiency. Balancing the amount of power produced internally with purchased power added another level of complexity. Managing the regulatory limits on NOx, a significant challenge during the warm months, posed a headache for the operators. The system was so convoluted that it was difficult for anyone to determine the best solution to the power puzzle at any given time. It was a Rube Goldberg system. The accepted practice was to make all the power we could because equipment runs most efficiently at 100% capacity. This wasn’t always the most economical solution given the dynamics of the system. The operators had guidelines on how to run their equipment but these were based on outdated calculations made using fixed fuel prices.
We knew that achieving utilities savings required a powerful new data analysis tool and a thorough understanding of the steam and power generating system. This effort required assembling a team of plant engineers and control specialist to develop a working model of the system. The complexity of the process led us away from a control system to an advisory system. Our first decision was the selection of the platform. After a period of searching, we chose Emerson’s AMS Suite: Real-Time Optimizer. Our decision was based on its track record of delivering significant benefits with complex systems. This real-time, online optimization system is capable of feeding decision-makers a continuous stream of economic information calculated from process variables. Once the optimization system was in place, we felt that it challenged many of our long-held beliefs — leading us to previously unforeseen process improvement opportunities.
Figure 2. Screenshot of optimum cost and baseline
Our first step was to create a reliable process model of the utilities infrastructure and electrical distribution network. This model encompasses the full range of possible operating modes within the power plant. All equipment is included in the model covering each item’s entire operating range. Online monitoring is configured to recognize performance degradation. Live process data are key inputs to the real-time optimizer, which receives updates every few minutes. The AMS Optimizer compares plant operation costs and automatically generates optimum loading instructions. Operators can then adjust performance parameters for each boiler and power-generating unit to maximize efficiency. The optimizer also monitors overall efficiency.
For example, the optimizer may recommend purchasing power as a means of reducing overall energy costs. If changing conditions make in-plant generation of electricity more cost-effective, our decision-makers are immediately informed of the opportunity. Wise “make or buy” decisions are the biggest drivers behind our documented savings, and we frequently purchase power when the optimization system reveals the economies of balancing out what we don’t produce internally.
One powerhouse is control central where the operators monitor the easy-to-use optimizer interface, a Graphical User Interface (GUI). The GUI displays an up-to-date summary of costs and operating conditions. Operators in the other powerhouses also have access to the GUI, which provides instructions to control their boilers for the production of power. Our goal is to minimize costs while meeting the demand for power and steam from throughout the plant.