Alberto Mian

Multi-objective optimization of SNG production from microalgae through hydrothermal gasification

The conversion of microalgae biomass into biofuels is a quite well explored field of research. Due to high photosynthetic efficiency, microalgae are considered as a potential feedstock for next-generations biofuel conversion processes. This paper addresses the thermochemical conversion of highly diluted microalgae feedstock into synthetic natural gas (SNG) through supercritical hydrothermal gasification. The complete conversion chain is modeled including the cultivation phase, settling ponds, centrifuges, catalytic hydrothermal gasification with salt separation unit and SNG purification system. Thermodynamic, economic and environmental models are considered for each process step, in order to solve a Mixed Integer Non Linear Programming (MINLP) optimization problem. The problem is solved by applying a two steps decomposition approach, using Multi Objective Evolutionary Algorithm with Mixed Integer Linear Programming (MILP). It is finally demonstrated that coupling microalgae cultivation systems with hydrothermal gasification (HTG) and waste energy recovery utilities leads to high energy/exergy efficiencies, emissions reduction and globally better sustainable processes.

Dynamic Modeling of the Microalgae Cultivation Phase for Energy Production in Open Raceway Ponds and Flat Panel Photobioreactors

A dynamic model of microalgae cultivation phase is presented in this work. Two cultivation technologies are taken into account: the open raceway pond and the flat panel photobioreactor. For each technology, the model is able to evaluate the microalgae areal and volumetric productivity and the energy production and consumption. Differently from the most common existing models in literature, which deal with a specific part of the overall cultivation process, the model presented here includes all physical and chemical quantities that mostly affect microalgae growth: the equation of the specific growth rate for the microalgae is influenced by CO2 and nutrients concentration in the water, light intensity, temperature of the water in the reactor and by the microalgae species being considered. All these input parameters can be tuned to obtain reliable predictions. A comparison with experimental data taken from the literature shows that the predictions are consistent, slightly overestimating the productivity in case of closed photobioreactor. The results obtained by the simulation runs are consistent with those found in literature, being the areal productivity for the open raceway pond between 50 and 70 t/(ha*year) in Southern Spain (Sevilla) and Brazil (Petrolina) and between 250 and 350 t/(ha*year) for the flat panel photobioreactor in the same locations.

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.

Optimal Design of Solar Assisted Hydrothermal Gasification for Microalgae to Synthetic Natural Gas Conversion

Catalytic hydrothermal gasification is a promising technology which allows the conversion of wet biomass into methane rich syngas. It consists of three major steps, in which thermal energy has to be supplied at different temperature levels, leading to multiple products, such as clean water, nutrients/salts and methane rich syngas. Microalgae have an important potential as a new source of biomass, principally due to the fact that they can grow much faster than others biomass feedstock available in nature. Considering the energy balance of the algae cultivation step, the gasification process and thecrude product upgrading step, part of the converted syngas has to be used to close the energy balance. In this context, solar heat can be considered as an alternative to replace the heat that has to be generated from product or crude product burning. This would lead to higher fuel production, higher carbon conversion efficiency and in general a better sustainable use of energy sources. In this paper, the goal is to show the integration potential of solar thermal energy use in the catalytic hydrothermal gasification of microalgae. In order to maximize the fuel production, thermal energy requirements of the gasification and SNG upgrading process can be generated in concentrating solar systems, coupled with thermal energy storage. This allows to continuously provide heat for the process at different temperature levels. A superstructure of design models will permit the estimation of the optimal size and integration of the solar utility for different process configurations. The optimal design configurations are evaluated by solving a multi objective optimization problem which aims at the maximization of conversion efficiency and the minimization of operating and total production costs. Copyright

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).

Energy Integration in the cement industry

Cement production is an energy intensive industrial process that requires heat to be supplied at high temperature levels under the constraints of gas-solid heat exchange phenomena and the kinetics of chemical reactions. In this paper, the use of Pinch Analysis and Process Integration techniques to optimize the energy efficiency of the cement production will be explored. The aim is to use process modeling to characterize cooling and heating requirements of the process, focusing on the gas-solid heat exchanges while including waste fuel utilization. The heat cascade model is adapted to account for gas-solid and gas-gas heat recovery used to calculate the heat recovery in the process. A mixed integer linear programming problem is solved to calculate the integration of the available heat; this model optimizes the heat recovery and the energy conversion efficiency considering different fuels, heat recovery options and process operating conditions.

Multi-objective optimization of SNG production through hydrothermal gasification from microalgae

Abstract Microalgae cultivation for biofuel conversion is widely treated in literature as it could allow reducing fossil fuel consumptions. One of the challenges of this technology is related to the high power and cost requirements for the harvesting and dewatering steps. The influence of dewatering process can be substantially reduced when considering hydrothermal gasification (HTG). This technology, which have already been demonstrated and tested, allows treating feedstock with more than 80% moisture content and can lead to high SNG conversion efficiencies. The object of this paper is to show the combination of microalgae growing and processing coupled with the HTG and syngas purification for SNG grid quality production. The productivity potential for this given technology is evaluated considering global solar radiation data available and the cultivation technology, which can be characterized by photosynthesis conversion efficiency. Systematic system design methodology followed by multi-objective optimization technique using evolutionary algorithms are carried out to provide a set of candidate solutions considering different configurations and conflictive objectives such as efficiency, cost and environmental impact.

MINLP Model and two-level Algorithm for the Simultaneous Synthesis of Heat Exchanger Networks and Utility Systems

This work proposes a novel approach for the simultaneous synthesis of Heat Exchanger Networks (HEN) and Utility Systems. Given a set of hot and cold process streams and a set of available utility systems (e.g., gas turbine, steam cycle, boiler, etc), the method determines the optimal selection of utility systems, their arrangement and design (including steam generator), and the heat exchanger network (between process-process as well as process-utility and utility-utility streams) rigorously considering the trade-off between efficiency and capital costs. The mathematical model is formulated as a Mixed Integer NonLinear Program (MINLP) and it combines the SYNHEAT superstructure for HENs with ad hoc models/superstructures for utility systems. The challenging MINLP is solved with a two-level algorithm using at the upper level the Variable Neighbourhood Search (VNS) algorithm to optimize the integer variables, and at the lower level the SQP algorithm to optimize the real variables. The algorithm is tested on problems with up to 15 streams (corresponding to 465 binary variables).

Integrated System Design of a Small-scale Power-to-Methane Demonstrator

Integrated System Design of a Small-scale Power-to-Methane Demonstrator Ligang Wang*, Alberto Mian, Luiz C.R. de Sousa, Stefan Diethelm, Jan Van herle, François Maréchal a Industrial Process and Energy Systems Engineering, École Polytechnique Fédérale de Lausanne, 1951 Sion, Switzerland b Group of Energy Materials, École Polytechnique Fédérale de Lausanne, 1951 Sion, Switzerland c Institut für Energietechnik, HSR Hochschule für Technik Rapperswil, 8640 Rapperswil-Jona, Switzerland ligang.wang@epfl.ch

A Heat Load Distribution Method for Retrofitting Heat Exchanger Networks

Abstract Fluctuating energy prices, increasing environmental concerns, and regulations push industries toward more energy efficient plants. Process integration (PI) techniques, proven to be effective in providing solutions with improved energy and material efficiencies often neglect modifications to the heat exchanger network (HEN). HEN design methods have been studied extensively to overcome this drawback of process integration but often still focus on grassroots design to suggest retrofits. This work proposes a method to solve heat load distribution (HLD), a sub problem of HEN design, in the context of retrofit problems. The problem is solved using a mixed integer linear programming (MILP) model with integer cuts (IC) to obtain many retrofit options with high computational speed. The model is built on previously developed methods for PI (Marechal and Kalitventzeff, 2003) and HEN design (Ciric and Floudas, 1989; Mian et al., 2016), such as mathematical programming (MP) and pinch analysis (PA). The objective function of the proposed method is minimisation of the estimated cost of the modifications required in an existing HEN, by considering the costs of repiping, additional heat exchanger area and additional heat exchangers. The estimated area of the potential stream matches is calculated using graphical techniques on the process integration results and taking into account correction factor. The additional heat exchanger area is constrained to practical limits available in the literature. The cost of heat exchanger area is calculated using piece-wise linearization of nonlinear cost functions. Solving the model yields information on stream matches and their heat loads as well as identifying which streams should be repiped and which heat exchangers should be modified or replaced. An industrial case study is solved to show the effectiveness of the proposed method resulting in annualized cost reductions of 9% considering the HEN design alone and 29% with modifications to the utility system to include heat pumping.