The Power of Automation

abb
Credit: ABB

Greater optimization of electric power generation is now paramount, with ever more advanced automation and I&C technologies playing a pivotal role in achieving it. Paul Breeze discusses the rapidly evolving power plant automation sector and explores the factors that are driving its development forward.

abb
Automation and control of a 800 MW combined cycle power plant
Credit: ABB

Automation systems for power plants have become increasingly sophisticated over the past 20 years on the back of major advances in computer hardware and software. Where once a power plant was controlled by an operator facing a bank of gauges and controls, today most plants are controlled largely by computer, while the operator performs an executive role. In addition to providing a greater degree of plant automation, these advances have also provided the ability to more closely control all the processes of a power plant. This, in turn, has meant that plant operations can be optimized against a variety of parameters to provide higher efficiency or greater flexibility depending upon the demands of the operator.

Computer power and sophisticated software suites are at the core of this new breed of automation system. Without the advances in both computer hardware and communications, such systems could not be built. However, other factors are also important. Advances in sensor and measurement technology have enabled many more power plant operating parameters to be measured and monitored than was possible in the past, providing a much more detailed picture of the state of a plant in real time. Meanwhile modern distributed control systems (DCS) provide the ability to regulate the operations of the plant more precisely that before. It is the integration of all these elements that has allowed modern power plant optimization technology to evolve to the level it has today.

Model behaviour

The availability of more plant data and the widespread introduction of DCS have created a foundation upon which an automation and optimization system can be constructed. However, it is the layer above these that provides the actual plant optimization. And at the heart of this supervisory layer in most advanced systems is a sophisticated model of the power plant.

Models of this type will aim to include all the key elements of the power plant. For a coal-fired plant this will embrace the coal mills and fuel feed systems, the combustion chamber and boiler, the steam turbine and all the emission control systems. The model will establish how the plant should operate for optimum performance against a particular set of parameters and to achieve a particular target such as fuel efficiency. The monitoring systems will then show whether the plant is operating at this point, while the control system will allow changes to be made based on deviations from the required behaviour.

New and retrofits

Advanced control systems are available for all types of power plant, but it is in steam-turbine-based combustion plants that they offer perhaps the greatest advantages. A good modern system will allow control of the combustion process in the boiler to maintain low nitrogen oxides (NOx) conditions and high carbon burnout, both of which are important for plant emission performance, as well as efficiency. It will control the steam temperatures and pressures throughout the steam cycle, allowing the best efficiency to be achieved while minimizing mechanical stresses, and it will monitor and control steam turbine operation. At the same time, real-time system parameters are collected and can be used for predictive maintenance.

Optimization can be used to control gas turbine and combined-cycle plants too. However, with modern gas turbines often operating at the limits of their materials capabilities and already closely controlled to ensure that they do not exceed these limits, there is often less scope here for innovative plant-wide changes to the mode of operation. “Not much can be done on combined cycle plants since the regulatory control is sufficient to keep the gas turbine at its optimum level,” says Samir Pandya, vice president for the power business at Invensys. “But with cogeneration plants, process optimization will help to improve the economic benefits. This is achieved by maintaining the plant at optimum efficiency for multiple fuel changes and for frequent power and steam demand changes,” he adds.

For renewable technologies, such as wind and solar, optimization strategies are being developed although the potential is more limited than for combustion plants. Innovation here is only just beginning. Meanwhile, automation providers and utilities are beginning to utilize fleet management tools that allow the optimization of power production not just in one plant but across all the plants operated by a company or across a region. This has advantages both for fossil fuel plants and for renewables, and is seen as an important growth area for the future.

While optimization technology is relatively new, the market for power plant optimization is not limited to new plants. Older plants can also benefit.

Power plants being built today are usually designed around the use of these sophisticated control systems. In contrast, many older plants still rely on much earlier generations of control and automation systems. Recent advances have been so significant that it is often cost effective to completely replace the original control system in a power plant more than 20 years old with a modern system. The cost can be recouped in more efficient operation, lower maintenance costs and greater ability to match grid operator demands.

The pressures within the global power market are making this an important market for automation providers. As Pascal Stijns, power and energy consultant at Honeywell Process Solutions, observes, roughly one third of global fossil capacity today is new, one third is around 20 years old and one third is in need of replacing. This means that one third of existing fossil fuel generating capacity is ripe for an automation system retrofit so that it can meet new standards for emissions and for efficiency. That offers enormous potential for suppliers and is one of the most fruitful areas of the market today.

Scope of power plant optimization

Russia's Surgut-2 power plant
An automation upgrade was completed at Russia’s Surgut-2 power plant this year
Credit: EPM

It has always been the ambition of power plant operators to manage their plants in the optimum way to provide the highest heat rate or a high level of flexibility in order to generate the highest economic returns. In the past, however, this ambition was limited by the ability to integrate the operations of all the different parts of a power plant. In a fossil fuel combustion plant, for example, the combustion process, the steam cycle, the steam turbine and the emission control systems would be optimized, but often independently of one another. Any integration of this optimization across the whole plant would rely on the expertise of the plant operator and his or her understanding of how these components interacted with one another. Thus, the whole plant model, if there was one, resided in the operator’s head.

What modern automation systems have brought is the ability not just to optimize the elements of the power plant, piece by piece, but the ability to optimize the whole plant as a single unit. So today, when plant operators talk about power plant optimization, they are talking about this holistic view of plant control.

In practice this whole-plant optimization has clear aims, and two are emerging as the most important, namely efficiency and flexibility. So, for example, Invensys’ Pandya cites two key objectives when applying a modern control system to a combustion plant such as a supercritical or subcritical coal-fired power station.

The first aim, he says, is to optimize power plant efficiency. This allows the plant operator to meet power demand with less fuel. The second objective, he believes, is better and tighter steam temperature control because this will then allow for higher unit dispatch rate.

For Alexander Frick, head of power plant optimization for ABB, optimization similarly means maximizing plant output or its availability. Again this boils down to maximizing efficiency (or heat rate) or maximizing the ability to respond quickly to grid operator demands. Both of these aims are determined by the prevailing conditions in the electricity markets, so they will vary in different parts of the world, but both are fundamentally driven by economic considerations.

Optimizing efficiency

Efficiency is at the core of all power plant operations and drives the advance of technologies across the whole of the power generation spectrum, from coal-fired plants to solar photovoltaics and wind power. For fossil fuel plants such as coal-fired power plants, this has led to the development of supercritical and ultra-supercritical boiler technologies based on ever higher steam temperatures and pressures, and relying on ever more sophisticated materials and technologies. A similar drive to higher operating conditions can be found in other generation technologies.

In a coal-fired plant, these advances come with the need for greater control of the steam cycle to ensure that the plant always operates within its capabilities. Further, optimum plant efficiency will often depend on maintaining the plant within a narrow range of steam cycle operating conditions. The more tightly the control can be maintained, the easier it becomes to maintain efficient generation. As Frick points out, the secret of a high heat rate and hence of high efficiency is to maintain operation at set points with as little variation as possible. Any variation leads to a lowering of the heat rate. This means a loss of efficiency and, at the bottom line, a loss of revenue.

High steam-cycle efficiency is crucial and, when talking about power plant efficiency, it is the headline efficiency figure that is mentioned most. But the potential for optimizing efficiency stretches well beyond this. Power plants are large users of electricity, which is consumed to drive a whole range of auxiliary systems, such as pumps and fuel preparation lines.

If the operation of all of these energy consuming power plant components can be controlled as part of the overall optimisation scheme, there are enormous savings to be made. It is by taking control of these auxiliary systems and operating them so that they do no more work than they need to, and only when they are needed, that modern automation systems score highly compared to their predecessors. This underscores one of the strongest business cases for optimization that companies can make. By operating each component of a plant as efficiently as possible, a new or improved automation system may be able to pay for itself in two years.

There is yet another important role that optimization can play in ensuring high efficiency, and that is by enabling a power plant to operate with fuels of varying quality. Most modern fossil fuel plants have to be able to burn fuels that have come from a variety of different sources, often with varying compositions and combustion properties. Managing fuel provision is particularly important for coal-fired power plants where substantial variations in fuel quality can be found. However, this can equally be applied to plants fired by natural gas, which are increasingly also seeing variations in fuel quality. Optimization for different fuels improves both generation efficiency and plant emissions, and each has an impact on the overall economics of power plant operation.

Drive towards greater flexibility

The other key driver of power plant optimization technology today is flexibility. Again the main focus for most automation system providers today is fossil fuel-fired stations, old and new. Traditionally, fossil fuel-based plants, both coal- and gas-fired, were designed for baseload operation. A plant was expected to operate with little variation in output, which was generally maintained at or close to the maximum. But changing system demands in some parts of the world mean that this is no longer the case. Instead plants are being asked to start up and shut down regularly. They must be able to operate at a range of part loads, and they must be able to change output, either up or down, rapidly.

These new demands have a profound effect on plant operations. During startup and shutdown a plant will often operate at lower efficiency that when at its steady-state operating position. The changing conditions will increase fuel consumption and also make the combustion process much more difficult to control, increasing emissions. This has an impact on both efficiency and the plant’s ability to meet its environmental standards. A similar situation arises during fast ramping. Meanwhile all of these modes of operation place much greater stress on plant components than would be experienced under steady-state operating conditions.

Plant optimization provides the tools to enable a coal-fired combustion plant or a gas-fired combined-cycle plant to operate flexibly to meet grid demands, while still ensuring that the best efficiency and the lowest emission performance is maintained. This is particularly important for coal-fired power plants. Many of the oldest coal-based plants in operation are incapable of adapting to these new demands, but more recent plants can be modified to enable this type of operation. Plant optimization can mean the difference between shutting a plant and being able to continue to operate it.

Predictive maintenance

As noted above, a power plant that was designed for baseload operation but finds itself having to operate in a flexible manner will be subject to much greater levels of stress than anticipated when it was built. Power plant optimization systems can help alleviate this by ensuring that the plant always operates within certain parameters that keep stress to a minimum. During startup, for example, if temperature gradients within the parts of the furnace boiler can be limited, then thermal stresses can be reduced.

By maintaining tight control of conditions during startup and shutdown, and when a plant is ramping, an automation system can help extend the lifetime of plant components.

In addition to this, the recording of the conditions experienced by each plant component during each cycle can be used to build up a historical picture of its evolving state of health, and this can be used for predictive maintenance, anticipating the health of a component before it fails.

The underlying model used as the basis for the automation of a plant is of vital importance here too. The normal operating conditions of all plant components are hardwired into the model so that any deviation from normal behaviour can quickly be pinpointed, be it a pump or a bearing running at a higher temperature than expected, or a broader change in combustion or emission conditions.

“We can follow the whole plant or just one of the processes to see if there is a change of behaviour that might lead to a fault,” elaborates Dieter Fluck, vice president for product management of instrumentation and electrical at Siemens Energy. Stress reduction and predictive maintenance allow a power plant to operate more efficiently by reducing downtime for outages and by reducing overall maintenance costs, which all feed into the bottom line and therefore achieve economic efficiency.

Technology and market demands

Metso
Power plant optimization techniques are likely to become more central to generation and to grid operators
Credit: Metso

While automation systems’ ability to control power plant operation has advanced, it has not done so simply in response to the technological advances which have made it possible. Behind it at every step have been market forces. Massimo Danieli, global business unit manager for power generation at ABB , identifies three such forces, which he considers of primary importance in driving optimisation technology today: the advance of renewable generation, global fuel costs and the effect of environmental concerns and legislation.

According to ABB’s Danieli, renewable generating capacity is growing rapidly, particularly in Europe and the US, and with high renewable energy penetration come greater challenges to grid management. In order to manage this, traditional baseload plants such as coal-fired and gas turbine units must act in a grid support role. They must be able to change output quickly, a demand also highlighted by Juha-Pakka Jalkanen, director of plant performance solutions at Metso Automation. Only with advanced power plant optimization is it possible to economically operate such plants in this way.

Global fuel prices are the second factor. All power plant operators want their plants to burn the lowest amount of fuel for the highest amount of energy output, maximizing their returns.

However, the changes being experienced in some global power markets are making this a critical issue. In the US, cheap gas is making it more and more difficult for coal plant operators to generate for a profit, while in Europe high gas prices are challenging gas-fired plant operators. In both cases the ability of an optimization regime to maintain tight control of the combustion system while minimizing stresses and holding maintenance costs down can be the difference between economic and non-economic operation.

Finally, environmental concerns that have stimulated the rise in renewable generation are also having a direct impact on fossil fuel-based plant operations as a consequence of environmental legislation.

Much tighter emission control restrictions in the US are starting to drive older coal-fired plants out of business. Newer plants have a greater chance of meeting the new restrictions, but the cost of compliance may well depend on the ability of an automation system to regulate the station’s operation. Similar considerations are affecting coal plants in Europe too.

Taken together, all these trends are creating a great deal more complexity in power systems. Take the number of units attached to a grid. In 1990 in Germany, Fluck said, there were 1000 generating units on the German grid. By 2011 there were 1 million, many of them wind and solar. Grid interventions to maintain stability on the German grid numbered two in 2003. In 2011 there were 1024 examples of action being taken.

This additional complexity, and the economic issues it raises, means that power plant optimization techniques are likely to become more and more central to generation and to grid operations too. “Everybody expects a reliable supply based on an ever-increasing share of volatile resources,” observed Fluck. Achieving that will not be possible without sophisticated control systems.

Paul Breeze is a UK-based freelance writer who specializes in energy-related matters.

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