Georges Heyen

Optimal process design for the polygeneration of SNG, power and heat by hydrothermal gasification of waste biomass: Thermo-economic process modelling and integration

This paper presents a process model for the polygeneration of Synthetic Natural Gas (SNG), power and heat by catalytic hydrothermal gasification of biomass and biomass wastes in supercritical water. Following a systematic process design methodology, thermodynamic property models and thermo-economic process models for hydrolysis, salt separation, gasification and the separation of CH4, CO2, H2 and H2O at high pressure are developed and validated with experimental data. Different strategies for an integrated separation of the crude product, heat supply and energy recovery are elaborated and assembled in a general superstructure. The influence of the process design on the performance is discussed for some representative scenarios that highlight the key aspects of the design. Based on this work, a thermo-economic optimisation will allow for determining the most promising options for the polygeneration of fuel and power depending on the available technology, catalyst lifetime, substrate type and plant scale.

Mathematical modelling and design of an advanced once-through heat recovery steam generator

The once-through heat recovery steam generator (HRSG) design is ideally matched to very high temperature and pressure, well into the supercritical range. Moreover this type of boiler is structurally simpler than a conventional one, since no drum is required. In a conventional design, each tube plays a well-defined role: water preheating, vaporisation, superheating. Empirical equations are available to predict the average heat transfer coefficient for each region. For once-through applications, this is no more the case and mathematical models have to be adapted to account for the disappearance of the conventional economiser, boiler and superheater. General equations have to be used for each tube of the boiler, and the actual heat transfer condition in each tube has to be identified. The mathematical complexity as well as the number of equations is increased. A thermodynamic model has been selected and implemented to suit very high pressure (up to 240 bar), sub- and supercritical steam properties. Model use is illustrated by two case studies: a 180 bar once-through boiler (OTB) and a conventional boiler superheater and reheater.

Sensitivity calculations and variance analysis in plant measurement reconciliation

Analysis of the results of a data reconciliation program is made easier by extracting more information from the Jacobian matrix of the constraint equations. Standard deviation for all state variables (measured or not measured) is related to the standard deviation of measurements. Distinction between variables that are actually corrected by the validation process, and those that are merely derived from a single measurement is straightforward. Based on this information, decisions can be taken: deletion of unnecessary measurements, addition of new measurement points and their optimal selection, or identification of key measurements for which any enhancement of accuracy would result in significant improvement in the quality of the process validation.

Plant monitoring and fault detection: Synergy between data reconciliation and principal component analysis

Data reconciliation and principal component analysis are two recognised statistical methods used for plant monitoring and fault detection. We propose to combine them for increased efficiency. Data reconciliation is used in the first step of the determination of the projection matrix for principal component analysis (eigenvectors). Principal component analysis can then be applied to raw process data for monitoring purpose. The combined use of these techniques aims at a better efficiency in fault detection. It relies mainly in a lower number of components to monitor. The method is applied to a modelled ammonia synthesis loop.

Optimal process design for the polygeneration of SNG, power and heat by hydrothermal gasification of waste biomass: Process optimisation for selected substrates

Based on a previously developed thermo-economic process model, this paper presents a detailed design study for the polygeneration of Synthetic Natural Gas (SNG), power and heat by catalytic hydrothermal gasification of biomass and biomass wastes in supercritical water. Using multi-objective optimisation techniques, the thermodynamic and thermo-economic performances of all candidate configurations from a general process superstructure are optimised with respect to SNG and electricity cogeneration and its associated investment cost, production cost and plant profitability. The paper demonstrates how both the optimal system configuration, its operating conditions and performances depend on the available technology, catalyst lifetime, process scale and the characteristics of the processed substrate.

Computer-Aided Design of Redundant Sensor Networks

Abstract A systematic method to design sensor networks able to identify key process parameters with a required precision at a minimal cost is presented. The procedure is based on a linearised model, derived automatically from a rigorous non-linear data reconciliation model. A genetic algorithm is used to select the sensor types and locations.

A comparison of advanced thermal cycles suitable for upgrading existing power plant

Abstract In view of the constant growth of electricity usage and public pressure to reduce the dependence on nuclear power plants in the energy supply, solutions are sought to increase the capacity of power plants using fossil fuels. Highly efficient cycles are available : gas turbines combined with waste heat boilers and steam cycles are able to achieve efficiencies above 50–55%. However building new plants requires a large amount of capital. Alternative proposals are based on upgrades of existing plants : capital savings are expected by reusing part of the facilities. In the present study, three parallel proposals are compared on the basis of exergy efficiency; cost of investment and flexibility of operation are also discussed. They are compared with classical Rankine cycle and state of the art combined cycles.

Energy savings in methanol synthesis: Use of heat Integration Techniques and Simulation Tools

Starting with a classical process for producing methanol using the reforming and synthesis steps, a combined approach applying simulation models and a new synthesis strategy, named Effect Modelling and Optimisation (EMO), has been used to optimise the energy efficiency of the process. The method allows to identify different ways of improving the energy efficiency of the process. The modifications concern the synthesis reactor and the reforming reactor designs, the exploitation of the purge stream as fuel gas to satisfy the process requirement and its integration to a gas turbine system. The EMO approach allows to target the impact of a process modification at the global level of the energy cost of the process, including the combined production of heat and mechanical power in a gas turbine and the steam network. Starting with a classical methane conversion of 60% for the classical system, we identify solutions with up to 93% of the overall methane conversion when we transform the net mechanical power produced into methane savings at the country level. The interest of the approach is the possibility of computing the impact of the process modifications suggested by the analysis of the shape of the heat cascade on the overall energy balance of the plant without having to simulate in many details the steam and the heat exchanger network.

Dynamic modelling and control of a pilot plant for post-combustion CO2 capture

A dynamic model of a post-combustion capture pilot plant is developed using Aspen Plus Dynamics. An innovative process control strategy is studied for regulating the water balance of the process. A washing section where the flue gas from the absorber is washed with cold water is included to the process in order to reduce the emissions of amine to the air. Control of the water balance in the solvent loop is successfully achieved by changing the washing water temperature. In previous publications regarding CO2 capture pilot plants, the regulation of the water balance always required a water make-up flow which appears here as unnecessary. Rejection of disturbances and different load reduction scenarios are tested to confirm the efficiency of this strategy. Potential operational problems of this control strategy are identified and solved.

Use of parallel computers in rational design of redundant sensor networks

A general method to design optimal redundant sensor network even in the case of one sensor failure and able to estimate process key parameters within a required accuracy is proposed. This method is based on a linear model, which derived from a non-linear data validation model and the sensor network is optimised thanks to a genetic algorithm. To reduce the solution time, two parallelisation techniques, both using the Message Passing Interface (MPI) library, are compared: the global parallelisation and the distributed genetic algorithms. Both methods allow reducing the solution time, but the second one is more efficient. Results are presented for an ammonia synthesis loop.