Optimal design methods applied to solar-assisted hydrothermal gasification plants

The gasification of highly watered waste residues may help to reduce fossil fuels consumption, as well as emissions, all the while improving efficiency. The integration of supercritical gasification with solar energy may improve the performances of both new and existing plants. The design and optimization of such kinds of energy conversion plants requires to take into account the following aspects: renewable sources are intermittent, prices of fuels and materials are continuously fluctuating and are uncertain, the energy efficiency should be maximized and the capital and opeating costs should be minimized. The main goal of this thesis is to develop mathematical programming frameworks in order to solve the design, the scheduling and the Heat Exchanger Network Synthesis (HENS) of any industrial plant. In particular, the final goal is to apply the proposed methods to the design of a solar-assisted supercritical gasification plant. The methods are developed in order to propose strategies to account for uncertainty, sizing constraints, scheduling options and multi-period HENS. In order to apply the frameworks elaborated in this dissertation, a set of mathematical models is suggested. The goal is to describe the thermodynamics of the considered process units: supercritical water gasification, gas separation, solar energy conversion technologies and storage utilities are studied. The pre-design problem is first tackled by coupling an energy targeting model with a Global Sensitivity Analysis (GSA) method and a Monte Carlo (MC) simulation. Given a set of energy conversion options, the most promising energy conversion paths with respect to a set of uncertain parameters are identified while applying energy integration principles. The design problem is then tackled and the design, the scheduling, as well as HENS for multi-period operations are investigated. The result is a sequential mathematical programming algorithm for solving the problem. A decomposition approach is applied using a bi-level optimization strategy, where derivative-free optimization algorithms are coupled with derivative based, mixed integer linear and non linear models. The framework is tested on a literature example and on a large scale example in order to prove its effectiveness. The integration of thermal storage options is included in order to highlight the improvements that can be achieved with process heat recovery. The computation time problem is addressed and an alternative strategy to solve the same problem is put forward. Finally, the developed methods are coupled with a Multi-Objective Optimization algorithm and the multi-period design problem for designing a solar-assisted super-critical gasification plant is solved. It is thus demonstrated how the proposed methods can be successfully applied to industrial-scale problems. It remains that computational issues are problem-dependent and sensitive to the problem definition.

Thermo-economic and environmental model of microalgae-to-SNG conversion process through hydrothermal gasification

Kevin Arrandel, François Maréchal, Alberto Mian, Adriano Viana Ensinas

Due to its high photosynthesis conversion efficiency, microalgae are currently considered as a serious feedstock for next-generation biofuels production. One possible conversion process is the production of synthetic natural gas (SNG) through catalytic hydrothermal gasification which uses a supercritical water-processing for the gasification and has the advantage to avoid drying of the biomass. The whole system includes four steps of production: microalgae cultivation, dewatering, gasification and product separation. In this paper the SNG production from microalgae is analyzed considering algal biomass cultivation system with open-ponds technology. To do so, a mathematical model based on mass and energy balances has been developed in order to represent microalgae growth process, and regarding culture temperature, solar-radiation incidence, CO2 and nutrients supply. The complete physical model of the biomass conversion system is developed including the dewatering system with settling ponds and centrifuges, catalytic hydrothermal gasification with salt separation unit and the SNG separation and purification system. An economic model is carried out for investment and operation cost of the process, from the biomass cultivation to the final product, including possibilities of nutrients, CO2 and water recovery. Finally, the environmental impact regarding the CO2 emission of this process and the avoided emission from the replacement of fossil natural gas is estimated in a complete life cycle analysis. A multi-objective optimization methodology is used to find the trade-off between the total cost of the system and the environmental impact that can be linked with the equipment size and the energy conversion efficiency.

2013

Thermo-Economic Optimisation of Solar Tower Thermal Power Plants

James Spelling

Amidst a backdrop of rapidly increasing world-wide electricity demand, solar thermal power generation shows great potential for supplying the electricity needs of numerous countries in the Sun-belt regions of the world. In these regions, the absence of significant biomass, hydrological or geothermal reserves makes solar thermal power the most promising solution for meeting that most fundamental of demands: energy. Amidst the different options available for harnessing the Sun’s power, solar thermal technologies have been shown capable of producing electricity at the most economically viable rates [32]. However, all currently existing solar thermal power plants have been based around the use of Rankine, or steam turbine, cycles which are limited in the efficiencies they can achieve. In order to make better use of the Sun’s energy, higher efficiency cycles should be used. With their high concentration ratios, solar thermal power tower systems are amongst the best options for making use of the Sun’s potential. As the energy delivery temperature of central receiver systems is higher, they harness the solar radiation at a higher exergy level [4]. This higher temperature also opens the road to the use of more advanced thermodynamic cycles. Hybrid fossil-fuel – solar systems are also imaginable [13], as the energy delivery temperature is compatible with standard gas turbine cycles. Hybrid systems can help mitigate the requirements of thermal energy storage, as well as reducing the perceived risk when investing in new solar technology, which stimulates research and development, as well as providing employment. Recent developments in the field of high temperature volumetric receivers [10] along with rock- based packed-bed storage systems have opened up an interesting possibility. High temperature receivers allow the use of higher-efficiency combined-cycle setups, whereas packed-bed units offer the possibility of cheap storage. Larger storage volumes allow pure-solar systems to extend their power production into the night, making hybrid options less attractive. This is compounded by the common practice of guaranteeing a preferred tariff for electricity sales from pure-solar sources With this in mind, a complete dynamic model of a power plant based on the pure-solar concept has been elaborated. The performance of the setup is evaluated over a range of days, using solar insolation profiles obtained from satellite data. In order to examine different design options and their impact on the performance of the power plant, a multi-objective, thermo-economic optimisation of both the power plant superstructure and operating conditions was performed using the new, dynamic models. By means of an evolutionary algorithm [17], a family of Pareto-optimal points were obtained, representing the trade-off between increased power plant efficiency, and lower levelised energy costs. Through use of optimisation, it was shown that exergetic efficiencies in the region of 21-27% can be achieved, for relatively low power outputs of between 3 and 11 MWe. These configurations correspond with levelised electricity costs in the region of 14-21 UScts/kWhe. In most regions, the use of solar power is encouraged by the guarantee of a preferential tariff for electricity sales from renewable sources. Sale of electricity at a price of around 24 UScts/kWhe [32] should therefore be imaginable, ensuring the economic viability of solar thermal power tower systems. It can be concluded that, when properly designed, solar thermal power plants based on combined cycles are both economically and thermodynamically promising. By raising the efficiency of the plant, the size of the solar collector field is diminished, increasing the otherwise low energy densities of solar power systems. By reducing the levelised electricity costs, solar thermal power plants become more economically viable, accelerating their construction and thus, hopefully, reducing our dependence on fossil-fuels.

2009

Integration of Supercritical Water Gasification in Combined 1G/2G Ethanol Production

François Maréchal, Alberto Mian, Adriano Viana Ensinas

The present study investigates the potential conversion of sugarcane into ethanol and synthetic natural gas. The considered conversion path consists in combining ethanol first and second generation ethanol production plant with a catalytic supercritical water gasification system. The main steps of the ethanol conversion consider fermentation of sugars (1G) and enzymatic hydrolysis of bagasse (2G). Enzymatic hydrolysis is selected since it represents a promising alternative for 2nd generation biofuels due to its high conversion efficiency. Among streams that are leaving the ethanol production plant are some high watered streams, whose carbon/energy content is not negligible. These streams should be valorised in an efficient way in order to improve the energy conversion efficiency. In this context supercritical gasification process allows to valorise these flows leaving the ethanol plant. Using supercritical water gasification it is in fact possible to avoid the drying the ethanol production leftovers, thus performing a direct gasification. The conversion of ligno-cellulosic residues into synthetic natural gas is modelled considering a catalytic supercritical gasification plant. Since the goal is to achieve high energy and exergy conversion efficiencies, the potential use of an additional set of utilities, such as burners, steam injected gas turbines or steam networks, is added to the sizing problem. The mathematical nature of the optimal utility selection problem deals with mixed integer linear programming (MILP) model, in which the type and size of utilities represent the independent variables, having fixed the process size. The results of the integration are showed in terms of Composite and Grand Composite Curves, economic indicators and local CO2 balance. Finally, having identified the ratio of sugarcane that goes to second generation ethanol plant as key dependent variables, the results of a sensitivity analysis are presented. The sensitivity analysis results are shown accounting economics for the Brazilian market, energy conversion performance indicators and considering local carbon dioxide balance.