Energy Management: First Steps Toward Greater Efficiency, Part Two

A primary source of power for many manufacturing operations, particularly in the process industries, is the boiler. Therefore, it is important to optimize the boiler combustion process to provide maximum efficiency while respecting equipment and environmental constraints. Improved combustion control is one of the simplest ways to decrease plant operational costs and improve safety.

02/01/2009


Sidebars:
HMIs: Even the little costs add up
Don’t forget the HVAC
Detecting steam leaks with wireless

A primary source of power for many manufacturing operations, particularly in the process industries, is the boiler. Therefore, it is important to optimize the boiler combustion process to provide maximum efficiency while respecting equipment and environmental constraints. Improved combustion control is one of the simplest ways to decrease plant operational costs and improve safety.

“Effective combustion control provides multivariable, rate-optimal, and model-based predictive control for the boiler combustion process,” says Ming Ge, product marketing manager, power generation, Honeywell Process Solutions. “Combustion control should tightly coordinate the ratio of and fuel supply into the combustion chamber under varying fuel characteristics and disturbances. A tighter air to fuel (A/F) ratio in dynamic and steady conditions can reduce the variability in the emissions. This reduction in variability also allows the combustion process to operate more efficiently.”

However, there is a trade-off between boiler efficiency and flue-gas emission concentrations. “The boiler efficiency depends on the A/F ratio, therefore an optimal air to fuel ratio needs to be calculated guaranteeing that CO and NOx are within specified limits while maximizing the thermal efficiency of the combustion process,” Ming says. The A/F ratio is then calculated to keep the probability of emissions from exceeding set threshold limits.

With effective combustion control derived via A/F ratio monitoring, the following benefits are possible:

  • 2-5% reduction in fuel usage;

  • 2-4% reduction in greenhouse gas emission; and

  • 3-5% reduction in overall operation and maintenance costs.

Fuel feedstock planning and scheduling

Sometimes the key to reducing energy cost for a plant comes down to simply buying cheaper energy. And buying cheaper energy is all about planning and scheduling applications to optimize how the plant meets forecasted demand over an extended period. Planners need to consider the variety of fuels that can be used in their units and how they might be blended to keep the plant full and meet demand.

“Information about yield and quality data of different crude fractions provides input to the operational plan along with knowledge of process unit configuration, material availability, and price,” says Pat Kelly, senior marketing manager, refining, Honeywell Process Solutions. “A good planning tool should be able to incorporate product mix limits, energy costs, and even CO 2 emissions limits or costs to find the feedstock that optimizes profitability of the plant.”

Although these planning applications can help determine how much of a particular feedstock should be run, it does not provide the granularity necessary for detailed operating instructions. To execute the plan, it must first be converted into a sequence of feasible activities over a short time horizon of a few days or weeks.

“This can be a complex step and many planners will use spreadsheets to help them come up with a feasible operating schedule,” says Brendan Sheehan, senior marketing manager, chemicals and energy, Honeywell Process Solutions. “As a result, they will often adopt the first feasible solution that they find knowing that it may have to be updated on a regular basis. However, incorporating the use of a scheduling model enables the user to find the optimal schedule that maximizes profitability while honoring quantity, quality, and logic constraints. In addition, this model can be run as often as required to reflect any changes in conditions in the plant or in feedstock availability.”

Kelly says that optimization of the feedstock selection by improved planning and scheduling can typically improve energy efficiency up to 2% for a 100,000 BPSD (barrels per stream day) refinery. The corresponding CO 2 reduction is 12 to 24,000 metric tons per year.

Pinch analysis and energy reuse

A widely recognized plant energy efficiency process involves recovering heat from waste heat streams and using it to preheat process streams that are typically heated with fossil fuels in furnaces or boilers. The difficulty with this process often lies in deciding which streams should be preheated and by how much, which should be cooled and by how much, and from where the excess heating and cooling should be tapped.

The best way to approach this problem is to first get an accurate picture of the energy flows around a unit and be able to measure the energy and material flow associated with each stream, recommends Honeywell’s Sheehan. “Then you can extract the necessary thermal data from flow sheets,” he says. “Typically, streams requiring heat are designated as 'hot’ streams and streams that need cooling are designated as 'cold’ streams—each having a starting temperature, a heat capacity flow rate, and a target temperature that is to be achieved.”

Sheehan notes that there is usually a minimum approach temperature (DTmin)—the minimum distance between a “hot” curve and a “cold” curve—plotted on a temperature versus enthalpy chart. “This minimum distance between the two curves is known as the pinch point,” Sheehan says. Pinch analysis provides a target for the minimum energy consumption.

“Where multiple streams are involved, they can be graphically combined so that two hot and cold 'composite curves’ can be constructed on temperature versus enthalpy charts,” Sheehan says. “The pinch point can be seen by pushing the two composite curves as close together as possible until the minimum temperature difference target is reached. You can also see the minimum hot and cold utilities required by the process for the target DTmin.”

Pinch analysis allows for quick identification of the scope of energy savings possible prior to heat exchanger network design. However, it does not directly provide realistic energy savings because composite curves provide overall utility levels but take no account of cases where there are multiple utilities providing heat and cooling at different levels.

“To overcome this problem, a 'Grand Composite Curve’ is constructed by shifting the cold composite curve up by 1/2 DTmin and shifting the hot composite curve down by 1/2 DTMin,” says Sheehan. “The 'Grand Composite Curve’ is therefore constructed from the enthalpy differences between the shifted composite curves.”

In this way the overall energy target is retained, but the utility loads are not altered. Future modifications to the shifted curves to allow the addition of multiple utility sources (such as high pressure and medium pressure steam or refrigeration and cooling water) ensure that DTMin is always maintained.

“Points where utilities touch the Grand Composite Curve are called utility pinches and the violation of one of these pinches results in heat load to be shifted from a cheaper utility level to a more expensive utility level,” Sheehan says. “This makes it possible to see how much preheat might be added to a feed that will be further heated by a furnace or how much cooling a product might get from a cooling water source before being further cooled by refrigerated chilled water.”

Sheehan notes that the best design for an energy efficient heat exchanger network often involves a trade-off between equipment and operating costs. “The lower the DTmin, the lower the energy costs but the higher the heat exchanger costs,” he says. “Other issues to consider include the total area of heat exchange, the location and type of utilities available, and the number of heat exchanger units.”


Author Information

David Greenfield is editorial director. Reach him at david.greenfield@reedbusiness.com .


HMIs: Even the little costs add up

You’ve probably seen the commercial by now where one teenager is informing another that even when her cell phone charger is plugged in and not charging her phone, it is still using electricity. A close correlation can be found in the backlighting of HMIs.

In most modern PCs and larger HMIs, the background lighting of TFT displays can be configured to switch off after a certain time, especially if the backlight is not LED based. This not only extends the life of the backlight light bulbs, but also can save between 2W to 8W depending on the display size.

To provide a case in point, Peter P. Fischbach, manager of component sales for Bosch Rexroth Corp., says that a medium size display with 5W backlight power—and considering the fact that most controls and HMIs are turned on 24/7/365—will use about 44 kWh/per year, or $4.40 at $0.1 per kWh.

This amount is small, but considering that many factories have hundreds or thousands of displays with powered backlights, it can add up to a measurable dollar savings. Considering that most HMIs consume 20 to 100 W of power due to the electronics (PC, HDD, Flash, etc.) this represents about a 10% to 15% energy savings.

Besides the cost of keeping the screen illuminated, those displays create heat that has to be removed via the air conditioning system.

Don’t forget the HVAC

You may not be a facilities engineer, but if you are located in a warm climate, the costs incurred by your facility’s air conditioning system should not escape the scrutiny of the plant’s engineers. To cool a large area, commercial and industrial centralized air-conditioning systems traditionally consist of multiple machines, commonly known as chillers that control air temperature by removing heat from a coolant liquid through vapor-compression or an absorption-refrigeration cycle.

CEMS Engineering (a South Carolina-based engineering firm serving industrial, commercial, institutional, and governmental clients) developed a technology to lower the energy usage of these chillers while still maintaining the same, cooled temperature of the building. To do this, CEMS Engineering uses the National Instruments’ Compact FieldPoint programmable automation controller to acquire real-time input data directly from sensors on the chillers and then uses this data to determine and send new operating instructions to the chillers. These operating instructions are determined through a series of variance calculations of the real-time input data, PID control loops, principles of thermodynamics, heat transfer, and advanced mathematical optimization and other proprietary equations in a NI LabView real-time application, resulting in reduced electricity bills and energy consumption up to 30%, according to CEMS Engineering.

Detecting steam leaks with wireless

It’s no secret that leaks can waste a considerable amount of steam, driving energy costs up and affecting process efficiency. The reason these leaks are not dealt with as completely as they should be is often due to the lack of manpower to monitor these leaks. In addition, test methods can be unreliable and the steam traps are sometimes impossible to access. In such cases, online, wireless monitoring of these valves is the answer, says Carl Hosier, marketing leader, power generation, Honeywell Process Solutions. “Wireless monitoring provides a constant acoustic record of steam trap performance, so leaks can be detected in real-time and energy losses minimized,” Hosier says.



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