A Structured Approach to Steam System Improvement through Utility System Design and Optimisation

Optimal operation of site utility systems is becoming an increasingly important part of any successful business strategy as environmental, legislative and commercial pressures grow. A reliable steam model allows a clear understanding of the system and of any operational constraints. It can also be used to determine the true cost of improvement projects, relating any changes in steam demand back to purchased utilities (fuel, power, and make-up water) at the site boundary. Example projects could include improved insulation, better condensate return, increased process integration, new steam turbines or even the installation of gas-turbine based cogeneration. This approach allows sites to develop a staged implementation plan for both operational and capital investment projects in the utility system. Steam system models can be taken one step further and linked to the site DCS data to provide real-time balances and improve the operation of the system, providing an inexpensive but very effective optimizer. Such a model ensures that the steam system is set in the optimum manner to react to current utility demands, emissions regulations, equipment availability, fuel and power costs, etc. This optimization approach typically reduces day-to-day utility system operating costs by between 1% and 5% at no capital cost. Why Build a Steam System Model? On many operating sites, maybe even the majority of sites, production is king and the steam system is regarded merely as a service that is far less important than the manufacturing processes themselves. Consequently, even companies that invest heavily in process modeling and simulation pay far less attention to the modeling of the steam system and, consequently, do not have the same understanding of the key players, the sensitivities and the inter-dependencies in this area. Often, steam is assigned a unit value ($/000lbs) that serves to cover the perceived costs of operating the utility system when this value is apportioned across the various manufacturing cost centers. This value will, at best, represent an average cost of steam over a period of time and will often be inappropriate or downright misleading if used for evaluating potential projects. A simple example would be a site that has a very close balance between suppliers and users at the lowpressure steam level. Site management is perhaps considering a new project to reduce the low-pressure steam demand. If the project is evaluated at the accountant’s transfer figure of, say, $5 per thousand pounds it may appear that the project will pay back handsomely. In reality, however, the “saved” steam may simply be vented as it has nowhere else to go. The project will therefore save nothing at all and will even lead to the additional cost of lost water and heat in the vent. A reliable model that reflects what actually happens within the steam system would identify the real cost of the project and avoid this inappropriate capital spend. The above example is rather simplistic but no less valid for all its simplicity. In real life, the actual cost of low-pressure steam is likely to be variable. It may take on a finite value initially as the first amounts of steam are saved and then, at some point, the above situation applies and the value of low-pressure steam reverts to zero or even a negative value, as described. There may therefore be a specific limit to the amount of steam that can be saved and further investment would be fruitless. It is obviously good to know what this limit is! If a proper understanding of the real marginal steam and power costs is obtained, then the present inefficiencies in the system can be clearly identified and the correct investment decisions taken with confidence. The true marginal cost of steam at any time and place in the system will depend on the actual path through which the steam passes on its way from generator to consumer. Mediumor low-pressure steam that is simply produced via letdown from the high-pressure boilers will have the same cost as the highpressure steam. On the other hand, if the mediumor low-pressure steam is exhausted from a steam turbine, than the unit cost of that steam will be less than that of high-pressure steam because of the credit associated with the generation of shaftwork in the turbine. Also, live steam for process use will have a higher value than the same steam used indirectly in heat exchangers because the latter can obtain credit for the condensate returned to the boilers. Finally, the time of day is increasingly affecting the cost of steam as power tariffs become more and more sophisticated following deregulation of the electrical power industry. Initial reasons for building a model of the steam system could, therefore, be: • To calculate the real cost of steam under various operational scenarios • To identify current energy losses • To accurately evaluate project savings • To forecast future steam demand versus production • To identify the critical areas, sensitivities and bottlenecks within the system • To identify no-cost operational improvements • To evaluate tariffs and energy contract management • To target and report emissions • To form the basis of a consistent investment plan for the site This paper will go on to show that many other benefits, including the optimization of steam system operation, can be obtained from such a model. What Type of Model is Available? Many companies have made a good attempt at spreadsheet-based steam system modeling. Although these in-house models are invariably restricted to mass flow balances and flowrate-based power generation formulae, they represent a significant advance on nothing at all. They have the advantages of spreadsheet operation (flexibility, transparency) but are often limited by the spreadsheet skills of the utility engineer. Also, they cannot simultaneously reconcile mass and heat balances such as those required around deaerators. Perhaps their biggest drawback is that they are often only understood by the engineer who built them in the first place. At the other end of the range is the full-blown process simulator, which is perfectly capable of modeling the utility system. The drawbacks in this case are the cost (large annual license fee) and the lack of transparency of the model. This is particularly important when changes and upgrades are required to be made to the model. The structure of the model may also be too rigid to allow rapid evaluation of a number of possible future scenarios. A third type of model is that which looks and feels like a spreadsheet but, at the same time, has direct access to the whole range of steam and water properties through an add-in physical properties database. As well as taking advantage of all the benefits of spreadsheet operation, it yields a true simultaneous balance of mass, heat and power in the system. It also offers consistency between different users, company-wide, and can be linked easily to the site’s data historian for real-time calculations. Good software packages in this category should also include drag and drop options for creating the utility flow diagram initially and pre-programmed equipment models to ensure that appropriate and consistent data are inputted and outputted around each equipment item and each header. Figure 1 illustrates a simplified model of a large site steam system including boilers, gas and steam turbines and three pressure levels of steam. Figure 1 Typical Site Steam Model How Can I Use the Model? There are, essentially, two distinct types of model or model applications that are relevant to this paper. These are the planning model described earlier and an optimizer, which is constructed and used somewhat differently to the planning model. These are described below: 1. The planning model allows the engineer to evaluate potential projects, what-if scenarios and future production trends. Typically, this involves building the model with the conventional spreadsheet logic functions (e.g. “IF” statements) to replicate the way in which the plant control system operates. In this way, the model will simulate the present behavior of the system. This type of model can also be linked to the site data historian to produce real-time models and to flag up deviations from an optimum template. Such a model will generally contain two worksheets. The first is a top-down balance based upon plant readings (which are usually more reliable at the high-pressure level) and the second is a bottom-up balance based upon the actual process demands. This allows the actual steam balance at any time (the top-down model) to be compared to an ideal template (bottom-up model) for that mode of process operation/steam demand. Differences can be highlighted and the appropriate action taken by the operator. 2 % 8 % e ff. 9 2 % O 2 O 2 F u e l G a s 1 4 3 t/h B F W In je c tio n 2 8 M W 2 0 4 t/h S te a m S T IG 3 9 .0 % 1 0 4 M W