Multi-criteria optimization in a methanol process

Opportunities for additional profit in retrofits depend very much on the existing plant structure, its parameters and energy system. Combined production of heat flow rate, power and chemical products can improve process efficiency. This paper presents an application of the nonlinear programming (NLP) optimization techniques, including increased chemical product output, heat integration and electricity cogeneration by changing amount flow ratios of raw material, and modifying the separation and reaction systems. The existing NLP model has been extended with basic chemical kinetics, including the effects of changing raw material flow rate ratios on product yield.A case studied methanol plant was optimized using the NLP model developed earlier by including an additional flow rate of hydrogen (H₂), decreasing flow rate of high-pressure steam in crude methanol recycling, and increasing methanol production by 2.5%. The potential additional profit from the cogeneration and additional methanol production was estimated to be 2.51 MEUR/a.     

Multi-criteria optimization of a district cogeneration plant integrating a solid oxide fuel cell–gas turbine combined cycle,heat pumps and chillers

A simultaneous optimization of the design and operation of a district heating, cooling and power generation plant supplying a small stock of residential buildings has been undertaken with regards to cost and CO₂ emissions. The simulation of the plant considers a superstructure including a solid oxide fuel cell–gas turbine combined cycle, a compression heat pump, a compression chiller and/or an absorption chiller and an additional gas boiler. The Pareto-frontier obtained as the global solution of the optimization problem delivers the minimal CO₂ emission rates, achievable with the technology considered for a given accepted investment, or respectively the minimal cost associated with a given emission abatement commitment.     

Analysis of MTH-System (Methylcyclohexane-Toluene-Hydrogen-System) for hydrogen production as fuel for power plants

The utilization of hydrogen (H₂) gas as green energy fuel in power plants is a great challenge due to its storage, deployment and transportation. Herein, we propose a simulation based study of H₂ fueled power plant by using Methylcyclohexane-Toluene-Hydrogen-System (MTH-System). A 266 MW gas turbine was selected and the performance of MTH-System for power plant was investigated. The process for methylcyclohexane (MCH) production was not discussed here. However, the conversion of MCH into gaseous H₂ for power generation was discussed in detail. A sustainable process flow diagram (PFD) was developed. The heat integration b/w power plant and dehydrogenation reactor reveal that, minimum 70% MCH conversion is required to accomplish the heat demand of whole system. The effect of addition of H₂ recycle stream to dehydrogenation reactor and combined cycle power plants was investigated. The sensitivity and economic analysis reveal 2291.4 $/kW capital cost based on dehydrogenation of MCH for power production and 0.186 $/kWh output electricity cost based on complete MTH-System.     

Optimization of ejector-expansion transcritical CO2 heat pump cycle

Optimization studies along with optimum parameter correlations, using constant area mixing model are presented in this article for ejector-expansion transcritical CO₂ heat pump cycle with both conventional and modified layouts. Both the energetic and exergetic comparisons between valve, turbine and ejector-expansions-based transcritical CO₂ heat pump cycles are also studied for simultaneous cooling and heating applications. Performances for conventional layouts are presented by maximum COP, optimum discharge pressure and corresponding entrainment ratio and pressure lift ratio of ejector, whereas for modified layout by maximum COP, optimum discharge pressure and corresponding pressure lift ratio. The optimization for modified layout can be realized for certain entrainment ratio, evaporator and gas cooler exit temperature combinations. Considering the trade-off between the system energetic and exergetic performances, and cost associated with expansion devices, the ejector may be the promising alternative expansion device for transcritical CO₂ heat pump cycle.     

Thermo‐economic‐environmental multiobjective optimization of a gas turbine power plant with preheater using evolutionary algorithm

In this study, the gas turbine power plant with preheater is modeled and the simulation results are compared with one of the gas turbine power plants in Iran namely Yazd Gas Turbine. Moreover, multiobjective optimization has been performed to find the best design variables. The design parameters of the present study are selected as: air compressor pressure ratio (r_AC), compressor isentropic efficiency (η_AC), gas turbine isentropic efficiency (η_GT), combustion chamber inlet temperature (T₃) and gas turbine inlet temperature. In the optimization approach, the exergetic, economic and environmental aspects have been considered. In multiobjective optimization, the three objective functions, including the gas turbine exergy efficiency, total cost rate of the system production including cost rate of environmental impact and CO₂ emission, have been considered. The thermoenvironomic objective function is minimized while power plant exergy efficiency is maximized using a genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost has been performed. In addition, the results showed that at the lower exergetic efficiency in which the weight of thermoenvironomic objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of Pareto Frontier with the lower weight of thermoenvironomic objective. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulation of the operation of a gas turbine installation of a thermal power plant with a hydrogen fuel production system

The growth in demand for the production of heat and electricity requires an increase in fuel consumption by power equipment. At the moment, the most demanded thermal equipment for construction and modernization is gas turbine units. Gas turbines can burn a variety of fuels (natural gas, synthesis gas, methane), but the main fuel is natural gas of various compositions. The use of alternative fuels makes it possible to reduce CO₂ and NO_x emissions during the operation of a gas turbine. Under conditions of operation of thermal power plants at the wholesale power market, it becomes probable that combined cycle power units, designed to carry base load, will start to operate in variable modes. Variable operation modes lead to a decrease in the efficiency of power equipment. One way to minimize or eliminate equipment unloading is to install an electrolysis unit to produce hydrogen.In this article the technology of “Power to gas” production with the necessary pressure at the outlet of 30 kgf/cm² (this pressure is necessary for stable operation of the fuel preparation system of the gas turbine) is considered. High cost of hydrogen fuel during production affects the final cost of heat and electric energy, therefore it is necessary to burn hydrogen in mixture with natural gas. Burning a mixture of 5% hydrogen fuel and 95% natural gas requires minimal changes in the design of the gas turbine, it is necessary to supplement the fuel preparation system (install a cleaning system, compression for hydrogen fuel). In addition, the produced hydrogen can be stored, transported to the consumer. For the possibility of combustion of a mixture of natural gas and hydrogen fuel in a gas turbine the methodology of calculation of thermodynamic properties of working bodies developed by a team of authors under the guidance of Academician RAS (the Russian Academy of Sciences) V.E. Alemasov has been adapted, resulting in a program that allows to obtain an adequate mathematical model of the gas turbine. The permissible range of the working body temperature is limited to 3000 K. This paper presents the developed all-mode mathematical model of a gas turbine.On the basis of mathematical modeling of a gas turbine, a change in the main energy and environmental characteristics is shown depending on the composition of the fuel gas. Adding 5% hydrogen to natural gas has little effect on the gas turbine air treatment system, the flow rate remains virtually unchanged. CO₂ emissions decrease, but there is an increase in the amount of H₂O in the turbine exhaust gases.     

Typical off-design analytical performances of internal combustion engine cogeneration

Based on experimental data, typical off-design characteristic curves with corresponding formulas of internal combustion engine (ICE) are summarized and investigated. In combination with analytical solution of single-pressure heat recovery steam generator (HRSG) and influence of ambient pressure on combined heat and power (CHP) system, off-design operation regularities of ICE cogeneration are analyzed. The approach temperature difference ΔT _a, relative steam production and superheated steam temperature decrease with the decrease in engine load. The total energy efficiency, equivalent exergy efficiency and economic exergy efficiency first increase and then decrease. Therefore, there exists an optimum value, corresponding to ICE best efficiency operating condition. It is worth emphasizing that ΔT _a is likely to be negative in low load condition with high design steam parameter and low ICE design exhaust gas temperature. Compared with single shaft gas turbine cogeneration, ΔT _a in ICE cogeneration is more likely to be negative. The main reason for this is that the gas turbine has an increased exhaust gas flow with the decrease in load; while ICE is on the contrary. Moreover, ICE power output and efficiency decrease with the decrease in ambient pressure. Hence, approach temperature difference, relative steam production and superheated steam temperature decrease rapidly while the cogeneration efficiencies decrease slightly. It is necessary to consider the influence of ambient conditions, especially the optimization of ICE performances at different places, on cogeneration performances.     

Thermodynamic analysis of a new process for hydrogen and electric power production by using carbonaceous fuels and high-temperature process heat

A new process for the simultaneous production of hydrogen and electrical power by using carbonaceous fuels and high-temperature process heat is presented in this paper. In an electrolytic cell, sulfur dioxide dissolved in an aqueous solution of sulfuric acid is electrochemically oxidized to sulfuric acid at the anode, while hydrogen gas is evolved at the cathode. The sulfuric acid produced in the cell provides the oxygen for the fuel combustion which subsequently takes place at high pressure. The combustion gas consisting mainly of CO₂, SO₂ and H₂O expands in a turbine in order to produce electrical power. After the expansion, the components sulfur dioxide and water are separated from the combustion gas and fed together with added water into the electrolysis cell.The process shows some advantages compared with already existing or proposed processes for the production of hydrogen or electric power. The influence of the sulfuric acid concentration and some other important process parameters on the energetic and exergetic efficiency of the total process is shown. The results shown in this paper have been obtained by using carbon (as a substitute for coal which is the preferred fuel) and a nuclear heat production plant (as an example of providing the required high-temperature process heat).     

Heat integration modeling of hydrogen production from date seeds via steam gasification

The purpose of the current study is to identify the potential of energy-efficient hydrogen (H₂) production from date seeds as biomass via steam gasification process along with heat integration in Gulf countries. A reaction kinetics model has been established for steam gasification with in-situ carbon dioxide (CO₂) capture of date seeds using MATLAB software. The kinetics of reactions involved in the gasification process was calculated using the optimization parameters fitting approach. The heat integration model has been developed via mixed integer nonlinear programming (MINLP) in MATLAB. In the parametric study, temperature and steam/biomass ratio considered their impact on syngas composition and energy recovery. Results showed that both variables have a strong positive effect on H₂ production and depicted maximum production of 68 mol% at a temperature of 750 °C with steam/biomass ratio of 1.2. Methane (CH₄) and CO₂ production were low in the product gas, which showed the activity of water gas shift reaction, methanation reaction, and carbonation reaction. Utilization of waste heat via process heat integration within the system reduced system's external heat load. More than 70% of energy recovered, which could be utilized for gasification and steam production. Energy analysis and process heat integration proved a prospective approach for energy-efficient and sustainable hydrogen production from date seeds.     

Multi-objective,multi-period optimization of biomass conversion technologies using evolutionary algorithms and mixed integer linear programming (MILP)

The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity.Several options for integrating biomass in the energy system, namely back pressure steam turbines, biomass rankine cycles (BRC), biomass integrated gasification gas engines (BIGGE), biomass integrated gasification gas turbines, production of synthetic natural gas (SNG) and biomass integrated gasification combined cycles (BIGCC), are considered in this paper. The goal is to simultaneously minimize costs and CO₂ emission using multi-objective evolutionary algorithms (EMOO) and Mixed Integer Linear Programming (MILP).Finally the proposed model is demonstrated by means of a case study. The results show that the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. Furthermore, higher primary energy savings and CO₂ emission reduction, 40%, are obtained through the gradual increase of renewable energy sources as opposed to natural gas usage. However, higher economic profitability, 52%, is achieved with natural gas-based technologies.     

Synthesis and thermo-economic design optimization of wood-gasifier-SOFC systems for small scale applications

The conceptual design of a biomass integrated gasification fuel cell system for small scale applications (40 kg h⁻¹ woody biomass input with 50% mass fraction water content) is discussed in this work. Two different biomass gasifiers (circulating fluidized bed and downdraft), two different reformers, a solid oxide fuel cell, a gas turbine and a heat recovery steam cycle were investigated. A two-step optimization procedure was used to perform thermo-economic design optimizations of nine system configurations generated by combining different technologies. At the master level an evolutionary algorithm is used to optimize the system intensive parameters following the minimization of the system costs and the maximization of the net power production simultaneously (two-objective). At the inner level, system mass flow rates are optimized by linear programming subject to the thermal balance and to the heat transfer feasibility constraints which were formulated by means of Pinch Analysis techniques. The degree of system internal heat recovery was studied by including the minimum temperature difference between hot and cold streams as a decision variable at the master optimization level. Optimization results are shown by means of an optimal Pareto front for each configuration. The degree of system internal heat recovery of some specific solutions is discussed by means of Pinch Analysis composite curves. The study shows that very high system efficiencies can be obtained but only at the expense of really high system costs mainly because of the high costs of the fuel cell and of the gasifier especially at the small scale level considered here. Minimum specific plant costs of the most cost-effective configuration, based on a hybrid cycle, greater than 7000 $ kW⁻¹ (2010 dollars) are found. The indirect circulating fluidized bed gasifier appears the most promising choice both in terms of cost and of system performance since it allows for better thermal integration at high temperatures and greater hydrogen yields. Auto-thermal reforming is a cheaper solution compared to steam reforming but does not benefit of the system internal heat recovery thus leading to comparably lower system efficiency. Steam reforming is particularly convenient when the system is pressurized and extra power can be recovered by gas expansion since a great amount of steam can be injected prior the reformer and vaporized by recovering the heat from exhaust gases.     

Optimization of heat recovery steam generator through exergy analysis for combined cycle gas turbine power plants

This paper proposes a new approach to finding the optimum design parameters of the heat recovery steam generator (HRSG) system to maximize the efficiency of the steam turbine (bottom) cycle of the combined cycle power plant (CCPP), but without performing the bottom cycle analysis. This could be achieved by minimizing the unavailable exergy (the sum of the destroyed and the lost exergies) resulted from the heat transfer process of the HRSG system. The present approach is relatively simple and straightforward because the process of the trial-and-error method, typical in performing the bottom cycle analysis for the system optimization, could be avoided. To demonstrate the usefulness of the present method, a single-stage HRSG system was chosen, and the optimum evaporation temperature was obtained corresponding to maximum useful work for given conditions of water and gas temperatures at the inlets of the HRSG system. Results show that the optimum evaporation temperature obtained based on the present exergy analysis appears similar to that based on the bottom cycle analysis. Also shown is the dependency of number of transfer unit (NTU) on the evaporation temperature, which is another important factor in determining the optimum condition when the construction cost is taken into account in addition to the operating cost. The present approach turned out to be a powerful tool for optimization of the single-stage HRSG systems and can easily be extended to multi-stage systems. Copyright © 2008 John Wiley & Sons, Ltd.     

Design and optimization of a non-TEMA type tubular recuperative heat exchanger used in a regenerative gas turbine cycle

A special non-TEMA type tubular recuperative heat exchanger used as a regenerator of a gas turbine cycle is considered for multi-criteria optimization. It is assumed that the recuperator is designed for an existing gas turbine cycle to be retrofitted. Three scenarios for optimization of the proposed system have been considered. In one scenario, the objective is minimizing the cost of recuperator; while in another scenario maximizing the cycle exergetic efficiency is considered. In third scenario, both objectives are optimized simultaneously in a multi-objective optimization approach. Geometric specification of the recuperator including tubes length, tubes outside/inside diameters, tube pitch in the tube bundle, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles are considered as decision variables. Combination of these objectives and decision variables with suitable engineering and physical constraints (including NO_x and CO emission limitations) makes a set of MINLP optimization problem. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms namely NSGA-II. This approach which is based on the Genetic Algorithm is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained and a final optimal solution is selected in a decision-making process. It is shown that the multi-objective optimization scenario can be considered as a generalized optimization approach in which balances between economical viewpoints of both heat exchanger manufacturer and end user of recuperator.     

Improving inter-plant integration of syngas production technologies by the recycling of CO2 and by-product of the Fischer-Tropsch process

This paper deals with the emission reduction in synthesis-gas production by better integration and increasing the energy efficiency of a high-temperature co-electrolysis unit combined with the Fischer-Tropsch process. The investigated process utilises the by-product of Fischer-Tropsch, as an energy source and carbon dioxide as a feedstock for synthesis gas production. The proposed approach is based on adjusting process streams temperatures with the further synthesis of a new heat exchangers network and optimisation of the utility system. The potential of secondary energy resources was determined using plus/minus principles and simulation of a high-temperature co-electrolysis unit. The proposed technique maximises the economic and environmental benefits of inter-unit integration. Two scenarios were considered for sharing the high-temperature co-electrolysis and the Fischer-Tropsch process. In the first scenario, by-products from the Fischer-Tropsch process were used as fuel for a high-temperature co-electrolysis. Optimisation of secondary energy sources and the synthesis of a new heat exchanger network reduce fuel consumption by 47% and electricity by 11%. An additional environmental benefit is reflected in emission reduction by 25,145 tCO₂/y. The second scenario uses fossil fuel as a primary energy source. The new exchanger network for the high-temperature co-electrolysis was built for different energy sources. The use of natural gas resulted in total annual costs of the heat exchanger network to 1,388,034 USD/y, which is 1%, 14%, 116% less than for coal, fuel oil and LPG, respectively. The use of natural gas as a fuel has the lowest carbon footprint of 7288 tCO₂/y. On the other hand, coal as an energy source has commensurable economic indicators that produce 2 times more CO₂, which can be used as a feedstock for a high-temperature co-electrolysis. This work shows how in-depth preliminary analysis can optimise the use of primary and secondary energy resources during inter-plant integration.     

Parametric optimization design for supercritical CO2 power cycle using genetic algorithm and artificial neural network

Supercritical CO₂ power cycle shows a high potential to recover low-grade waste heat due to its better temperature glide matching between heat source and working fluid in the heat recovery vapor generator (HRVG). Parametric analysis and exergy analysis are conducted to examine the effects of thermodynamic parameters on the cycle performance and exergy destruction in each component. The thermodynamic parameters of the supercritical CO₂ power cycle is optimized with exergy efficiency as an objective function by means of genetic algorithm (GA) under the given waste heat condition. An artificial neural network (ANN) with the multi-layer feed-forward network type and back-propagation training is used to achieve parametric optimization design rapidly. It is shown that the key thermodynamic parameters, such as turbine inlet pressure, turbine inlet temperature and environment temperature have significant effects on the performance of the supercritical CO₂ power cycle and exergy destruction in each component. It is also shown that the optimum thermodynamic parameters of supercritical CO₂ power cycle can be predicted with good accuracy using artificial neural network under variable waste heat conditions.     

Thermoeconomic optimization of combined cycle gas turbine power plants using genetic algorithms

This paper shows a possible way to achieve a thermoeconomic optimization of combined cycle gas turbine (CCGT) power plants. The optimization has been done using a genetic algorithm, which has been tuned applying it to a single pressure CCGT power plant. Once tuned, the optimization algorithm has been used to evaluate more complex plants, with two and three pressure levels in the heat recovery steam generator (HRSG).The variables considered for the optimization were the thermodynamic parameters that establish the configuration of the HRSG.Two different objective functions are proposed: one minimizes the cost of production per unit of output and the other maximizes the annual cash flow. The results obtained with both functions are compared in order to find the better optimization strategy.The results show that it is possible to find an optimum for every design parameter. This optimum depends on the selected optimization strategy.     

Exergy analysis and optimization of a hydrogen production process by a solar-liquefied natural gas hybrid driven transcritical CO2 power cycle

A solar transcritical CO₂ power cycle for hydrogen production is studied in this paper. Liquefied Natural Gas (LNG) is utilized to condense the CO₂. An exergy analysis of the whole process is performed to evaluate the effects of the key parameters, including the boiler inlet temperature, the turbine inlet temperature, the turbine inlet pressure and the condensation temperature, on the system power outputs and to guide the exergy efficiency improvement. In addition, parameter optimization is conducted via Particle Swarm Optimization to maximize the exergy efficiency of hydrogen production. The exergy analysis indicates that both the solar and LNG equally provide exergy to the CO₂ power system. The largest amount of exergy losses occurs in the solar collector and the condenser due to the great temperature differences during the heat transfer process. The exergy loss in condenser could be greatly reduced by increasing the LNG temperature at the inlet of the condenser. There exists an optimum turbine inlet pressure for achieving the maximum exergy efficiency. With the optimized turbine inlet pressure and other parameters, the system is able to provide 11.52 kW of cold exergy and 2.1 L/s of hydrogen. And the exergy efficiency of hydrogen production could reach 12.38%.     

Natural gas based hydrogen production with zero carbon dioxide emissions

A novel process flowsheet is presented that co-produces hydrogen and formic acid from natural gas, without emitting any carbon dioxide. The principal technologies employed in the process network include combustion, steam methane reforming (SMR), pressure swing adsorption, and formic acid production from CO₂ and H₂. Thermodynamic analysis provides operating limits for the proposed process, and the use of reaction clusters leads to the synthesis of a feasible process flowsheet. Heat and power integration studies show this flowsheet to be energetically self-sufficient through the use of heat engine and heat pump subnetworks. Operating cost/revenue studies, using current market prices for natural gas, hydrogen and formic acid, identify the proposed design’s operating revenue to cost ratio to be 9.29.     

Exergoenvironmental analysis and optimization of a cogeneration plant system using Multimodal Genetic Algorithm (MGA)

In the present work, a combined heat and power plant for cogeneration purposes that produces 50 MW of electricity and 33.3 kg/s of saturated steam at 13 bar is optimized using genetic algorithm. The design parameters of the plant considered are compressor pressure ratio (r_AC), compressor isentropic efficiency (η_comp), gas turbine isentropic efficiency (η_GT), combustion chamber inlet temperature (T₃), and turbine inlet temperature (TIT). In addition, to optimally find the optimum design parameters, an exergoeconomic approach is employed. A new objective function, representing total cost rate of the system product including cost rate of each equipment (sum of the operating cost, related to the fuel consumption) and cost rate of environmental impact (NO_x and CO) is considered. Finally, the optimal values of decision variables are obtained by minimizing the objective function using evolutionary genetic algorithm. Moreover, the influence of changes in the demanded power on various design parameters are parametrically studied for 50, 60, 70 MW of net power output. The results show that for a specific unit cost of fuel, the values of design parameters increase, as the required, with net power output increases. Also, the variations of the optimal decision variables versus unit cost of fuel reveal that by increasing the fuel cost, the pressure ratio, r_AC, compressor isentropic efficiency, η_AC, turbine isentropic efficiency, η_GT, and turbine inlet temperature (TIT) increase.     

Power-to-ammonia in future North European 100 % renewable power and heat system

Power-to-gas and other chemicals-based storages are often suggested for energy systems with high shares of variable renewable energy. Here we study the North European power and district heat system with alternative long-term storage, the power-to-ammonia (P2A) technology. Assuming fully renewable power and heat sectors and large-scale electrification of road transport, we perform simultaneous optimization of capacity investments and dispatch scheduling of wind, solar, hydro and thermal power, energy storages as well as transmission, focusing on year 2050. We find that P2A has three major roles: it provides renewable feedstock to fertilizer industry and it contributes significantly to system balancing over both time (energy storage) and space (energy transfer). The marginal cost of power-based ammonia production in the studied scenarios varied between 431 and 528 €/t, which is in the range of recent ammonia prices. Costs of P2A plants were dominated by electrolysis. In the power and heat sector, with our cost assumptions, P2A becomes competitive compared to fossil natural gas only if gas price or CO₂ emission price rises above 70 €/MWh or 200 €/tCO₂.