Emanuele Martelli

Numerical optimization of heat recovery steam cycles: Mathematical model, two-stage algorithm and applications

Abstract Most of the advanced integrated energy systems need a heat recovery steam cycle (HRSC), either fired or unfired, that recovers the waste heat from gas turbines and process units in order to generate electric power and supply mechanical power to compressors, heat to endothermic processes, and steam to external users. The key feature of such HRSCs is the integration between the heat recovery steam generator (HRSG) and the external heat exchangers. This paper presents a rigorous mathematical programming model, a linear approximation, and a two-stage algorithm for optimizing the design of integrated HRSGs and HRSCs, simultaneously considering the HRSG together with the heat recovery steam network and the intensive steam cycle variables. A detailed application of the methodology is described for an integrated gasification combined cycle plant with CO2 capture and results for other interesting plants are reported. A significant efficiency gain is obtained with respect to usual practice designs.

PGS-COM: A hybrid method for constrained non-smooth black-box optimization problems: Brief review, novel algorithm and comparative evaluation

Abstract In the areas of chemical processes and energy systems, the relevance of black-box optimization problems is growing because they arise not only in the optimization of processes with modular/sequential simulation codes but also when decomposing complex optimization problems into bilevel programs. The objective function is typically discontinuous, non-differentiable, not defined in some points, noisy, and subject to linear and nonlinear relaxable and unrelaxable constraints. In this work, after briefly reviewing the main available direct-search methods applicable to this class of problems, we propose a new hybrid algorithm, referred to as PGS-COM, which combines the positive features of Constrained Particle Swarm, Generating Set Search, and Complex. The remarkable performance and reliability of PGS-COM are assessed and compared with those of eleven main alternative methods on twenty five test problems as well as two challenging process engineering applications related to the optimization of a heat recovery steam cycle and a styrene production process.

Using Hydrogen as Gas Turbine Fuel: Premixed Versus Diffusive Flame Combustors

This work aims at estimating the efficiency gain resulting from using lean premixed combustors in hydrogen-fired combined cycles with respect to diffusive flame combustors with significant inert dilution to limit NOx emissions. The analysis is carried out by considering a hydrogen-fired, specifically tailored gas turbine whose features are representative of a state-of-the-art natural gas–fired F-class gas turbine. The comparison between diffusion flame and lean premixed combustion is carried out considering nitrogen and steam as diluents, as well as different stoichiometric flame temperatures and pressure drops. Results show that the adoption of lean premixed combustors allows us to significantly reduce the efficiency decay resulting from inert dilution. Combined cycle efficiency slightly reduces from 58.5%–57.9% when combustor pressure drops vary in the range 3%–10%. Such efficiency values are comparatively higher than those achieved by diffusive flame combustor with inert dilution. Finally, the study investigated the effects of decreasing the maximum operating blade temperature so as to cope with possible degradation mechanisms induced by hydrogen combustion.

Weight and power optimization of steam bottoming cycle for offshore oil and gas installations

Offshore oil and gas installations are mostly powered by simple cycle gas turbines. To increase the efficiency, a steam bottoming cycle could be added to the gas turbine. One of the keys to the implementation of combined cycles on offshore oil and gas installations is for the steam cycle to have a low weight-to-power ratio. In this work, a detailed combined cycle model and numerical optimization tools were used to develop designs with minimum weight-to-power ratio. Within the work, single-objective optimization was first used to determine the solution with minimum weight-to-power ratio, then multi-objective optimization was applied to identify the Pareto frontier of solutions with maximum power and minimum weight. The optimized solution had process variables leading to a lower weight of the heat recovery steam generator while allowing for a larger steam turbine and condenser to achieve a higher steam cycle power output than the reference cycle. For the multi-objective optimization, the designs on the Pareto front with a weight-to-power ratio lower than in the reference cycle showed a high heat recovery steam generator gas-side pressure drop and a low condenser pressure.

PGS-COM: A hybrid method for constrained non-smooth black-box optimization problems

Abstract In the areas of chemical processes and energy systems, the relevance of black-box optimization problems is growing because they arise not only in the optimization of processes with modular/sequential simulation codes but also when decomposing complex optimization problems into bilevel programs. The objective function is typically discontinuous, non-differentiable, not defined in some points, noisy, and subject to linear and nonlinear relaxable and unrelaxable constraints. In this work, after briefly reviewing the main available direct-search methods applicable to this class of problems, we propose a new hybrid algorithm, referred to as PGS-COM, which combines the positive features of Constrained Particle Swarm, Generating Set Search, and Complex. The remarkable performance and reliability of PGS-COM are assessed and compared with those of eleven main alternative methods on twenty five test problems as well as two challenging process engineering applications related to the optimization of a heat recovery steam cycle and a styrene production process.

MINLP model and two-stage algorithm for the simultaneous synthesis of heat exchanger networks, utility systems and heat recovery cycles

Abstract This work proposes a novel approach for the simultaneous synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. Given a set of hot and cold process streams and a set of available utility systems, the method determines the optimal selection, arrangement and design of utility systems and the heat exchanger network aiming to rigorously consider the trade-off between efficiency and capital costs. The mathematical formulation uses the SYNHEAT superstructure for the HEN, and ad hoc superstructures and nonlinear models to represent the utility systems. The challenging nonconvex MINLP is solved with a two-stage algorithm. A sequential synthesis algorithm is specifically developed to generate a good starting solution. The algorithm is tested on a literature test problem and two industrial problems, the optimization of the Heat Recovery Steam Cycle of a Natural Gas Combined Cycle and the heat recovery system of an Integrated Gasification Combined Cycle.

Short-Term Planning of Cogeneration Power Plants: a Comparison Between MINLP and Piecewise-Linear MILP Formulations

Abstract In this work we compare two optimization approaches to tackle the short-term operational planning of energy systems including power plants, boilers, heat storage, as well as cogeneration units. We first describe a mixed-integer nonlinear programming formulation for the problem and then a mixed-integer linear one, obtained using piecewise-linear approximations of the nonlinear performance functions. We report and discuss numerical results on a set of realistic test cases, comparing the quality of the solutions and the computing time of the two approaches.

Multi-objective Optimization of a Rectisol® Process

This work focuses on the design, simulation and optimization of a Rectisol®-based process tailored for the selective removal of H2S and CO2 from gasification derived synthesis gas. Such task is quite challenging due to the need of addressing simultaneously the process design, energy integration and utility design. The paper, starting from a Rectisol® configuration recently proposed by the authors, describes the models and the solution strategy used to carry out the multi-objective optimization with respect to exergy consumption, CO2 capture level and capital cost.

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.

Multi-period Sequential Synthesis of Heat Exchanger Networks and Utility Systems including storages

This work proposes a sequential approach for the multi-period synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems, including thermal, electric and material storage. The optimization approach is sequential and it consists in three steps: (1) the multi-period Mixed Integer Linear Programming (MILP) energy integration model of Marechal and Kalitventzeff (2003) determines the optimal utility selection, size and operation scheduling (on/off) as well as the size of the storage system which minimize the linearized utility total costs for given Heat Recovery Approach Temperature (HRAT), (2) a modified version of the multi-period MILP minimum number of units problem Floudas and Grossmann (1986) determines the number of matches (heat exchanger units) between hot and cold streams such that the sum of the associated penalty levels are minimized, (3) the Non Linear Programming (NLP) multi-period HEN synthesis model proposed by Floudas and Grossmann (1987) finds the HEN with minimum area. In order to partially overcome limitations of the sequential approach, HRATs for each stream and for each time period, as well as penalty levels associated to each possible exchange and the sizes of available utilities are optimized using the derivative-free hybrid algorithm PGS-COM Martelli and Amaldi (2014).