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Energy Systems Design Accounting for Dynamic Performance dynamic requirements, even if aggressive control strategies are pursued. This chapter is aimed at the development of an automated preliminary design methodology in which system transient performance can be seamlessly evaluated together with other typical design requirements. In order to test the automated design tool, a relevant test case has been selected, namely the power plant of an off-shore oil and gas platform in the North Sea, operating off-grid. The problem consists in evaluating if it is possible to increase the efficiency of the three gas turbines (GTs) by installing an organic Rankine cycle (ORC) turbo-generator powered by the exhaust gases of one of the GTs, and still comply with stringent dynamic requirements. This chapter is structured as follows: the novel design methodology is outlined in §5.2, while §5.3 deals with the description of the case study. A detailed description of the models is presented in §5.4. The results are thus reported and discussed in §5.5. Concluding remarks are given in §5.6. 5.2 Methodology The objective of this study is to develop and demonstrate a methodology for the preliminary de- sign of power generation systems that integrates the fulfilling of dynamic requirements into the automated procedure. This goal is attained by performing two main steps. In the first step, N performance metrics are selected (e.g., the thermal efficiency, the overall system volume, the net present value), and a multi-objective optimization problem is solved in order to find a set of preliminary system designs which lead to optimal performance of the system at the rated operating point. The outcome is an N-dimensional Pareto front of system designs, which are optimal with respect to different objectives. In the second step, the dynamic performance of the system is assessed by simulating critical transients for each design on the Pareto front, and by verifying whether requirements and constraints involving dynamic variables are met or not. System designs which do not meet the dynamic requirements are discarded. The end-result of the procedure is a reduced set of optimal system designs complying with the trade-offs between different objectives, while ensuring proper system operation during critical transients. Based on this result, properly informed decisions about the final system design can be taken, thus avoiding the risk of discovering criticalities of transient operation at later project stages, i.e., during detailed design, or even commissioning, when corrective action might be very expensive or impossible. 5.2.1 Multi-Objective Design Optimization The design methodology utilized in the present chapter is described in detail in Ref. [10], where it is applied to the exemplary case of an ORC power system. The design algorithm is implemented using the Matlab language; several new features were added in the present thesis to the previous version of the program. The design procedure is briefly summarized here for the sake of completeness. First of all, boundary conditions, which hold for all designs, are defined. For example, in the case of an ORC heat recovery system, these are the mass flow rate, temperature and composition of the flue gas source, the selection of the working fluid, and the choice of the components, such as once-through boiler, shell and tube recuperator, and condenser. The thermodynamic states at the in- let and outlet of each component can thus be identified by applying basic energy and mass balances. Subsequently, the design of the plant equipment, e.g., the number, length, and diameter of tubes in the heat exchangers, or the turbine flow coefficient, is carried out automatically, ultimately leading to the evaluation of the chosen performance metrics. An iterative procedure then explores the de- 123PDF Image | New Concepts FOR Organic Rankine Cycle Power Systems
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