A systematic approach to the synthesis and design of flexible site utility systems

Abstract

The paper presents a systematic approach for the synthesis of flexible utility systems satisfying varying energy demands. The approach combines benefits of total site analysis, thermodynamic analysis and mathematical optimisation. A thermodynamic efficiency curve (TEC) is developed, which gives an overview of the maximum thermodynamic efficiencies of all possible design alternatives. TEC and hardware composites guide the selection of candidate structures in the superstructure, excluding uneconomic options from the synthesis model. The integration of thermodynamics yields significant reduction in the synthesis model, addresses the impact of variable loads on the unit efficiencies, and enables a compact formulation of the design problem over long horizons of operation. The optimisation is formulated as a multi-period MILP problem that relies on new target models to describe the performance of steam turbines, condensing turbines, gas turbines and boilers. Target models account for the variation of efficiency with unit size, load and operating conditions in a simple, yet accurate way. As a result, these models are capable of accounting for the efficiency trends of realistic units.

Introduction

Industrial utility systems operate as part of a site complex servicing a pre-specified number of production processes each demanding heat and power at different levels throughout the year. The utility system is configured according to the needs of the entire system and it is desired that its operation remains efficient but robust to the different variations in demand. At times, such variations could be considerable, following changes in the markets, changes in the supplies of raw materials, product variability and seasonal changes. The variability has an apparent impact on the efficiency, as large units would be under-used in low periods whereas small units, being less efficient at full load, would make unfortunate choices in periods of high demand. The variability of demands requires a methodology that builds flexible utility systems which operate efficiently (thermodynamic target), are capable to adjust to different conditions (combinatorial challenge), and able to operate at minimum cost (economic target in optimisation). Critical design decisions include the selection of steam levels and the layout of the site utility system. The system consists of available steam turbines, gas turbines, boilers and other auxiliary units.

The optimal selection of steam levels has been discussed in Shang and Kokossis (2004). Once the steam levels are determined, the design can proceed with the development of the best structure to produce utilities. This task comprises a large combinatorial problem. Candidate systems involve layouts of the following units: (i) simple and/or complex back-pressure (BP) turbines, (ii) simple and/or complex condensing turbines, (iii) reheat cycles, (iv) simple and/or regenerative gas turbine cycles, and (v) boiler networks. Each alternative configuration results in a different overall efficiency and a different capital cost. As the utility demands vary with time, it is important that the utility system maintain high efficiency over the entire variation range. On the other hand, the optimum trade-off between flexibility and capital cost needs to be identified. In order to evaluate the alternative design options and distinguish amongst the associated efficiencies, the effects of the unit size, as well as load and operating conditions on the unit efficiencies, need to be taken into account. These effects generally involve non-linear relations that give rise to complex models and formulations.

In the last two decades, a number of approaches have been reported for the synthesis and design of utility systems. Papoulias and Grossmann (1983) proposed an MILP approach for the synthesis of flexible utility systems accounting for anticipated variations in process demands in the shape of a multiperiod utility demand pattern. Hui and Natori (1996) presented a mixed-integer formulation for multiperiod synthesis and operation planning for utility systems and discussed the industrial relevance. A simulated annealing algorithm was used by Maia and Qassim (1997) for the synthesis of utility systems with variable utility demands. Iyer and Grossmann (1998) proposed a multi-period MILP approach for the synthesis and planning of utility systems under multiple periods. Oliveira Francisco and Matos (2003) extended the model by Iyer and Grossmann to include global emissions of atmospheric pollutants from fuels combustion.

It is well documented that the appropriate selection of the different superstructure units/components reflects on the actual value of the synthesis work. Unless containing appropriate candidates, the superstructure approach delivers inferior results. At the same time, exhaustive or blind integration of potential units is pointless and ineffective. Multiple operational scenarios simply increase the size of the synthesis model, whereas efficiencies are complicated enough to be treated as parameters by the majority of researchers. None of the previous approaches have addressed the challenge to select superstructure units as a result of operational variations. This is particularly important as unit sizes directly relate—and have a major impact—on the network efficiency. At the same time, size and efficiency count as complicating variables since, if introduced to the formulation, they both lead to significant complexities. Mavromatis and Kokossis, 1998a, Mavromatis and Kokossis, 1998b have presented an approach to decouple the non-linear components of unit efficiencies with the use of thermodynamic models. They accordingly managed to formulate an MILP model for the design of steam turbine networks that takes into account the impact of operational variations on the efficiencies. Tested on real-life problems, and although limited to BP turbines, the approach reports improvements of 11% against cases that neglect variations or consider unit efficiencies as constant.

This paper presents a methodology inspired by these last developments. The approach is not limited to particular units though but includes boilers, gas turbines and all types of steam turbines. Thermodynamic models are used to develop synthesis formulations in the form of multi-period MILP problems. These include boiler hardware models, steam turbine hardware models and gas turbine hardware model. They account for the variability of equipment efficiency with size, load and operating conditions. Thermodynamics are employed to reduce the size of the superstructure and integrate only units required to achieve maximum performance. The approach is illustrated in several design problems most of which represent real-life applications.