Thermodynamic and technoeconomic optimization of Organic Rankine Cycle systems

Abstract The optimization of an organic Rankine cycle is a challenging task that cannot be tackled without the aid of numerical tools for plant simulation and optimization. The large availability of various working fluids, the possibility of adopting several plant layouts, and the need to consider many thermodynamic, technological, and economical aspects lead to a challenging design optimization problem. This chapter describes the most important steps in optimizing the design of organic Rankine cycles. First, general criteria for selecting the best working fluid and the best cycle configuration for a set of the most relevant applications are thoroughly discussed. Moreover, useful guidelines are provided for the definition of the design optimization problem, its objective function, the decision variables, and the constraints. Then, the available simulation and optimization approaches and algorithms are critically reviewed with respect to their suitability for the optimization of power cycles. Finally, three test cases are presented to highlight the importance of optimization in the development of efficient and profitable organic Rankine cycles for geothermal heat sources, biomass-fired boilers, and waste heat recovery.

[1]  François Maréchal,et al.  Multi-objective Optimization of a Rectisol® Process , 2014 .

[2]  S. Quoilin,et al.  Performance and design optimization of a low-cost solar organic Rankine cycle for remote power generation , 2011 .

[3]  Yujia Wang,et al.  Particle swarm optimization with preference order ranking for multi-objective optimization , 2009, Inf. Sci..

[4]  A. Yokozeki,et al.  Heat Transfer of Refrigerant Mixtures , 1992 .

[5]  Guo Tao,et al.  Performance comparison and parametric optimization of subcritical Organic Rankine Cycle (ORC) and transcritical power cycle system for low-temperature geothermal power generation , 2011 .

[6]  Yiping Dai,et al.  Multi-objective optimization of an organic Rankine cycle (ORC) for low grade waste heat recovery using evolutionary algorithm , 2013 .

[7]  J. Crawford Chapter 17 – Heat exchangers , 1988 .

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  W. Price Global optimization by controlled random search , 1983 .

[10]  Glynn J. Sundararaj,et al.  Ability of Objective Functions to Generate Points on Nonconvex Pareto Frontiers , 2000 .

[11]  Tamara G. Kolda,et al.  Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods , 2003, SIAM Rev..

[12]  Fredrik Haglind,et al.  Design methodology for flexible energy conversion systems accounting for dynamic performance , 2014 .

[13]  Costante Mario Invernizzi,et al.  Thermodynamic performance of selected HCFS for geothermal applications , 1997 .

[14]  Stefan Roth,et al.  Covariance Matrix Adaptation for Multi-objective Optimization , 2007, Evolutionary Computation.

[15]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[16]  Fredrik Haglind,et al.  Optimization of Organic Rankine Cycles for Off-Shore Applications , 2013 .

[17]  J. Gu,et al.  Decrement estimation of the heat transfer coefficient in mixture boiling , 1999 .

[18]  Richard Turton,et al.  Analysis, Synthesis and Design of Chemical Processes , 2002 .

[19]  Petros Koumoutsakos,et al.  Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.

[20]  Stefano Consonni,et al.  Numerical Optimization of Combined Heat and Power Organic Rankine Cycles - Part A: Design Optimization , 2015 .

[21]  Olav Bolland,et al.  Weight and power optimization of steam bottoming cycle for offshore oil and gas installations , 2014 .

[22]  Tetsuyuki Takahama,et al.  Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[23]  Sébastien Le Digabel,et al.  A Taxonomy of Constraints in Simulation-Based Optimization , 2015, 1505.07881.

[24]  Robert L. Smith,et al.  Simulated annealing for constrained global optimization , 1994, J. Glob. Optim..

[25]  François Maréchal,et al.  Environomic optimal configurations of geothermal energy conversion systems: Application to the future construction of Enhanced Geothermal Systems in Switzerland , 2012 .

[26]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .

[27]  William D'haeseleer,et al.  Comparison of Thermodynamic Cycles for Power Production from Low-Temperature Geothermal Heat Sources , 2013 .

[28]  Tao Wang,et al.  Constrained simulated annealing with applications in nonlinear continuous constrained global optimization , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[29]  J. K. Maund Process plant estimating evaluation and control: by Kenneth M. Guthrie, published by the Craftsman Book Co. (U.S.A.), 1974, price $ 25 , 1976 .

[30]  Charles Audet,et al.  Mesh Adaptive Direct Search Algorithms for Constrained Optimization , 2006, SIAM J. Optim..

[31]  C. D. Perttunen,et al.  Lipschitzian optimization without the Lipschitz constant , 1993 .

[32]  M. J. Box A New Method of Constrained Optimization and a Comparison With Other Methods , 1965, Comput. J..

[33]  Tamara G. Kolda,et al.  Stationarity Results for Generating Set Search for Linearly Constrained Optimization , 2006, SIAM J. Optim..

[34]  Ahmed Kovacevic,et al.  An Improved System for Power Recovery from Higher Enthalpy Liquid-Dominated Fields , 2005 .

[35]  Costante Mario Invernizzi,et al.  Experimental investigation on the thermal stability of some new zero ODP refrigerants , 2003 .

[36]  Ignacio E. Grossmann,et al.  Systematic Methods of Chemical Process Design , 1997 .

[37]  Paolo Iora,et al.  Bottoming micro-Rankine cycles for micro-gas turbines , 2007 .

[38]  Katya Scheinberg,et al.  Introduction to derivative-free optimization , 2010, Math. Comput..

[39]  Andreas Schuster,et al.  Efficiency optimization potential in supercritical Organic Rankine Cycles , 2010 .

[40]  Nikolaos V. Sahinidis,et al.  Derivative-free optimization: a review of algorithms and comparison of software implementations , 2013, J. Glob. Optim..

[41]  Stephen J. Wright,et al.  Numerical Optimization (Springer Series in Operations Research and Financial Engineering) , 2000 .

[42]  Paola Angela Bombarda,et al.  Estimating cost of the geothermal power technologies: main aspects and review , 2011 .

[43]  Brian Elmegaard,et al.  Multi-objective optimization of organic Rankine cycles for waste heat recovery: Application in an offshore platform , 2013 .

[44]  Marco Astolfi,et al.  Techno-economic Optimization of Low Temperature CSP Systems Based on ORC with Screw Expanders , 2015 .

[45]  Jiangfeng Wang,et al.  Parametric optimization and comparative study of organic Rankine cycle (ORC) for low grade waste heat recovery , 2009 .

[46]  M. Ali,et al.  Some Variants of the Controlled Random Search Algorithm for Global Optimization , 2006 .

[47]  François Maréchal,et al.  Framework for the Multiperiod Sequential Synthesis of Heat Exchanger Networks with Selection, Design, and Scheduling of Multiple Utilities , 2016 .

[48]  Lisa Branchini,et al.  Thermo-Economic Evaluation of ORC System in Off-Shore Applications , 2014 .

[49]  Gael D. Ulrich,et al.  A Guide to Chemical Engineering Process Design and Economics , 1984 .

[50]  Olav Bolland,et al.  Working fluids for low-temperature heat source , 2010 .

[51]  Jennifer Lyons,et al.  Process Equipment Cost Estimation, Final Report , 2002 .

[52]  Masao Fukushima,et al.  Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization , 2006, J. Glob. Optim..

[53]  A. Messac,et al.  The normalized normal constraint method for generating the Pareto frontier , 2003 .

[54]  Dan Simon,et al.  Evolutionary Optimization Algorithms , 2013 .

[55]  Arnold Neumaier,et al.  Global Optimization by Multilevel Coordinate Search , 1999, J. Glob. Optim..

[56]  Hussein A. Abbass,et al.  Differential Evolution for Solving multiobjective Optimization Problems , 2004, Asia Pac. J. Oper. Res..

[57]  D. Walraven,et al.  Optimum configuration of shell-and-tube heat exchangers for the use in low-temperature organic Rankine cycles , 2014 .

[58]  John E. Dennis,et al.  Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems , 1998, SIAM J. Optim..

[59]  Carlos A. Coello Coello,et al.  Solving Multiobjective Optimization Problems Using an Artificial Immune System , 2005, Genetic Programming and Evolvable Machines.

[60]  Luís N. Vicente,et al.  PSwarm: a hybrid solver for linearly constrained global derivative-free optimization , 2009, Optim. Methods Softw..

[61]  Emanuele Martelli,et al.  Numerical optimization of combined heat and power Organic Rankine Cycles – Part B: Simultaneous design & part-load optimization , 2015 .

[62]  Ian K. Smith,et al.  Development of the Trilateral Flash Cycle System: Part 1: Fundamental Considerations , 1993 .

[63]  W. Worek,et al.  Optimum design criteria for an Organic Rankine cycle using low-temperature geothermal heat sources , 2007 .

[64]  Kuppan Thulukkanam Heat Exchanger Design Handbook , 2013 .

[65]  George Papadakis,et al.  Low­grade heat conversion into power using organic Rankine cycles - A review of various applications , 2011 .

[66]  Leonardo Pierobon,et al.  Novel design methods and control strategies for oil and gas offshore power systems , 2015 .

[67]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[68]  T. Kolda,et al.  A generating set direct search augmented Lagrangian algorithm for optimization with a combination of general and linear constraints , 2006 .

[69]  Don W. Green,et al.  Perry's Chemical Engineers' Handbook , 2007 .

[70]  Qingfu Zhang,et al.  Multiobjective evolutionary algorithms: A survey of the state of the art , 2011, Swarm Evol. Comput..

[71]  Piero Colonna,et al.  Thermal energy storage for solar-powered organic Rankine cycle engines , 2013 .

[72]  Russell C. Eberhart,et al.  Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization , 2002 .

[73]  Vincent Lemort,et al.  Thermo-economic optimization of waste heat recovery Organic Rankine Cycles , 2011 .

[74]  Lorenz T. Biegler,et al.  Improved infeasible path optimization for sequential modular simulators—II: the optimization algorithm , 1985 .

[75]  Engelbert Ziegler Computer in der Chemie , 1984 .

[76]  I. Smith,et al.  Development of the Trilateral Flash Cycle System Part 2: Increasing Power Output with Working Fluid Mixtures , 1994 .

[77]  C. T. Kelley,et al.  An Implicit Filtering Algorithm for Optimization of Functions with Many Local Minima , 1995, SIAM J. Optim..

[78]  Edoardo Amaldi,et al.  Numerical optimization of heat recovery steam cycles: Mathematical model, two-stage algorithm and applications , 2011, Comput. Chem. Eng..

[79]  Akshay Hattiangadi,et al.  Working Fluid Design for Organic Rankine Cycle (ORC) Systems , 2013 .

[80]  Charles Audet,et al.  Analysis of Generalized Pattern Searches , 2000, SIAM J. Optim..

[81]  Cheng-Liang Chen,et al.  Synthesis of transcritical ORC-integrated heat exchanger networks for waste heat recovery , 2015 .

[82]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .

[83]  Pei-Xue Jiang,et al.  Thermodynamic analysis of a binary power cycle for different EGS geofluid temperatures , 2012 .

[84]  Roman Ulbrich,et al.  Implementation of a biomass-fired co-generation plant supplied with an ORC (Organic Rankine Cycle) as a heat source for small scale heat distribution system – A comparative analysis under Polish and German conditions , 2013 .