Every power producer engaged in power trading today is faced with the following crucial questions: How much can I produce? What are my production costs? How much do I have to deliver? How big is my risk? What price can I buy in at? What price can I sell at? He needs the answers within minutes, with high accuracy and with high reliability. And he needs this information not only for the current time, but also for the next few days, to be able to make advance arrangements for his ongoing operations.

Just a few years ago, answering such questions would have been inconceivable and, in times of regulated markets and guaranteed prices, pointless. Even today, finding the answers is still a difficult task that challenges all the capabilities and competence of both information technology and power plant engineering.

Clear-cut answers can only be given if the current and forecast technical condition of the plant is precisely known and if the contractual obligations can be called up immediately. In particular, it is necessary to accurately quantify and reliably predict all the cost components of power generation: fuel, consumables and chemicals consumption, possibly aggravated service life exhaustion, perhaps extra expenditures on maintenance, spare parts and personnel, etc.

In today’s power plants, different information systems are used for operations management, process instrumentation and control, and business management. It is very difficult to produce forecasts for the precise production cost and load capability (ie the maximum possible power plant production) for electric power, heat and process steam based on information from all these areas.

Information such as deficiency reports, job orders, circuit diagrams, design drawings, lists of spare parts, ordering procedures, documentation, and operating conditions is most often stored in different software systems on different computers at different locations. The computer-specific log-in procedures and operating commands alone complicate even the simplest query.

There is little support for the exchange of stored, actual and forecast data among the various computers systems, and in most cases it is not possible to generate forecasts automatically.

A tool for all tasks

The PROFIT Cockpit aims to address these issues. The system is now commercially available and the first projects are in progress.

Essentially, the PROFIT Cockpit performs three basic functions:

• The access function gives the operator direct access to all underlying systems from a single user interface. The automatic context-dependent navigation feature is particularly user-friendly. This ensures simple and, above all, standardised user control.

• The integrator function collects the data from all underlying systems, processes them into meaningful information, and displays them on a user interface in the form in which they are required for the selected task.

• The time navigation feature makes it possible to access past, present and future data. It is this function, in particular, that distinguishes the PROFIT Cockpit from other navigation tools. As-if analyses can be performed for the near future on the basis of calculated trends or forecasts.

Together with the underlying subsystems, the Cockpit computes costs by accessing all relevant data from process management, business management and production, financially evaluating these data, and linking them to generate information and forecasts that serve as a decision-making basis. For this reason, the comprehensive information provided by the Cockpit can also be used for medium-term decisions and as a cost-cutting database for routine activities.

The PROFIT Cockpit gives access to the entire “data world” of the plant and thus constitutes a big step towards what has been called the “transparent power plant”, in which process, operations and enterprise management data are accessed, interlinked and evaluated.

All relevant information in relation to process conditions, maintenance and repair procedures, as well as economic variables such as fuel costs, operating costs and anticipated earnings from the sale of electric power are taken into account in the assessment.

PROFIT Cockpit supports not only cost tracking but also the monitoring and planning of various activities within the power plant. For these tasks, several forecasting modules provide reliable information on anticipated load, production costs and spare parts management.

Other areas included in this process are the logistics for fuel, various consumables and chemicals, documentation management, and power distribution. This makes it possible to generate precise cost forecasts for profit-oriented participation in the power market.

Requirements for power trading

The process of selling electricity, heat and steam involves a diversity of complex functions with a large number of players and systems.

The preparation-negotiation-execution-review cycle has to be run through afresh for each individual transaction, and a large number of information sources have to be tapped in the process.

The plant’s generating capability is derived from the load capability forecast, which predicts the maximum and minimum generation possible from a power plant on the basis of the component availability.

The production cost is computed in real time in an on-line cost model and is projected into the future, with allowance for the expected ambient conditions, the contracts in force, and optimum operations planning. The available generating capacity can be calculated from the forecast demand versus the supply contracts and purchase agreements already concluded, taking into account the forecast load capability.

Supplementary functions for power trading are risk management and incorporation of the relevant market information.

Load capability forecast

The precise prediction of future load capability (maximum and minimum possible generation) is an essential component in the implementation of the PROFIT Cockpit’s functionality. This information gains in importance if extra power is to be sold, for example, on the spot market.

The purpose of the load capability forecast function within the Cockpit is to predict the load capability for each production unit within the defined time horizon (eg, two days, one week, etc).

In principle, two types of load capability can be distinguished:

• the control-defined load capability, which takes into account the limitations imposed by the instrumentation and control systems; and

• the physical load capability, which takes into account the real, instantaneous physical boundaries of the equipment determining the load capability.

The load capability forecast is normally governed by the control-defined load capability, ie, the instantaneous load capability as derived from the control functions for the respective generating equipment. However, it may be necessary to take the physical load capability into account, for example if the mills of a coal plant are being operated at the limits of their capacity due to poor coal quality, or if the maximum turbine output cannot be achieved due to inadequate condenser vacuum under limited main steam flow conditions.

Derivation of the control-defined load capability is part of the unit control functionality for power plants operating in unit mode. Its purpose is to calculate the minimum and maximum allowable unit output and the associated load change gradients in the load regime and if necessary to limit the setpoint for electric power output.

The load capability derivation function is highly plant-specific and thus has to be taken into consideration for each production unit separately.

For computation of the load capability forecast it is necessary to know only the availability of the equipment units defined in the instrumentation and control system as limiting the load capability. If servicing or preventive maintenance activities are scheduled for any such equipment, the start and end of this activity are read out of the operations management system, integrated into the load capability forecast with the aid of a special availability logic, and processed for graphic display (colour-coded).

Cost forecast

Precise calculation of costs is also crucial to the implementation of the Cockpit’s functionality. The aim of the cost tracking function within the Cockpit is to capture all variable production-related costs and to assign them to the individual production units with a defined accuracy. The production costs must be known as precisely as possible for: planning the operation of the generating equipment; drawing up power supply and purchase contracts; and purchase or sale of defined amounts of power on the spot market.

This requires, among other factors, calculation of the instantaneous generating cost.

The task can thus be formulated as follows:

• real-time calculation of the variable generating costs, especially the fuel cost;

• adequately precise estimation of the fixed generating costs (overheads).

Implementation of the Cockpit essentially requires data from the cost calculation software, ie, the existing data structures and all calculations and analyses already available are used as far as possible, and all additional computations necessary are performed within the Cockpit itself.

The most important item among the variable costs is fuel, not just because fuel costs are the biggest cost item, but also because they can be calculated and predicted by means of thermodynamic models. Besides, they are usually (more or less accurately) continuously measured. In this context, the calorific value of the fuel must be known for a statistical combustion computation. However, precise specification of the fuel composition (analysis) is better, because this permits the calorific value to be accurately calculated and allowance to be made for the excess air coefficient in a precise combustion computation.

Using PROFIT Cockpit: an example

To explain the functions of the Cockpit, consider the production manager of a power utility that operates a power plant park consisting of eight units: four coal-fired units; two waste-incinerating power plants; and two gas turbines which, owing to their higher fuel costs, are mainly kept on standby.

The production manager’s aim is to produce as reliably as possible, because he has contracts he has to fulfill. And he has to produce at the lowest possible cost, because competition is stiff.

He will normally use the Cockpit in the “production” function, which gives him an overview of the entire production process. For example, he can tell at a glance how much he can supply, how much he has to supply, and what it is costing him.

PROFIT Cockpit shows the present status of his plants. We can see he is heading for a problem in the near future. The load capability – that is to say the maximum possible production from the power plant complex – is predicted to drop off drastically over the following weekend.

In Figure 5 (figures currently not available) the time cursor has been moved forward into the future, showing the status of the power plants over the coming weekend. Because the Cockpit enables him to see into the future in this way, our production manager recognises that he will just about be able to satisfy the demand, but at a very high cost. The red areas indicate that he is running on his expensive standby capacity.

How is he to assess this situation? What is behind the slump in the load capability? With the time cursor moved to the future he can see in detail what is going to happen: Coal-Fired Unit 1 is shut down for maintenance, he can tell that from the red coloured rectangle. The gas turbines, previously on standby, are now on line. That is the reason for the high cost, which is indicated at almost 15 E/MWh. No hope of a profit at that rate!

To see why Unit 1 had to go off line for maintenance, he clicks on the symbol for that unit. This takes him one level lower, where all the data the Cockpit now shows him relate to this unit. The bright red symbol indicating a work order immediately catches his eye. This is where the bug must be. When he clicks on the work schedule for the boiler (not shown) he finds: “Leak in high-pressure section. Replace tube”. Serious damage. That much is clear, this repair cannot be postponed.

But if he uses the gas turbines to meet the demand, he will be running at a loss for as long as the boiler is down. What other options does he have for avoiding this? The repair work cannot be postponed. He could use his existing purchase contract to bridge this period. The Cockpit shows him a price of 18 E/MWh. That is even more expensive than the gas turbines, so no point. The only other thing is to buy in on the spot market.

Here, too, our production manager can consult the Cockpit. He switches from “Production” to “Market”, and then to “Buy”. A new display appears on screen. It shows him what prices he would have to pay when, and how much he would have to buy on the market to make it cheaper than in-house production.

He sends this diagram to the purchasing section. If he can get an offer of less than 12.3 E/MWh for the period in question on the spot market, he can take it up and rescue the situation.

But the production manager does not use the Cockpit only to buy in power.

The “Sell” function shows him at a glance how much surplus capacity he has available and what price he would have to get for it on the power exchange to cover his production cost.

This is an opportunity to make some extra profit, because electricity prices on the exchange fluctuate widely – between 10 and 70 E/MWh, sometimes even as much as 100 E.

If he sells only 2 per cent of his production of 500 MW at a mere 10 E/MWh above his normal contract rate, he can earn an extra 500 000 E per year, assuming the plant clocks up 5000 full-load hours.

At that rate, the PROFIT Cockpit will soon have paid for itself.