The investigation of treatment design parameters on carbon integration networks

Carbon Integration methods help identify the appropriate allocation of captured carbon dioxide (CO2) streams into CO2-using sinks, and are especially useful when a number of CO2 sink options are present simultaneously. The method helps identify CO2 allocation scenarios when subjected to an emission target on the CO2 overall network. Many carbon dioxide sink options are costly, and more often than not, require a high purity carbon dioxide source to satisfy the sink demand. Hence, it is imperative to effectively incorporate treatment units in such networks, to obtain high-purity CO2 streams. In fact, it has been previously reported in many studies that the most expensive step in Carbon Capture, Utilization and Sequestration (CCUS) is the treatment system. As a result, this paper focuses on reassessing the performance of carbon integration networks using a more rigorous cost model for the treatment design stage. The effect of utilizing different treatment operating conditions on the overall cost of the treatment stage of CO2 (before allocation) is first captured using a detailed cost model. Subsequently, this information is then fed into a network design problem that involves a CO2 source-sink allocation network problem, and different CO2 net capture targets within the network. For this, an enhanced treatment model that captures all necessary treatment design parameters has been utilized alongside the original model. The original carbon integration formulation has been adopted from previous work. Many of the cost items have been lumped into single parameters in the original formulation, and lack the necessary depth required to carry out the necessary investigations for this work. Hence, the treatment model introduced in this paper is more rigorous, as it accounts for important technical performance constraints on the system to be assessed. Utilizing a more detailed cost model was found to be very helpful in understanding several effects of varying parameters on the overall source-sink allocations, when subjected to different CO2 net emission reduction targets. The cost of the carbon network increases when the solvent temperatures are increased. However, there was a noticeable linear trend at lower temperatures compared to higher temperatures, where the increase became non-linear. Furthermore, it was discovered that for net capture targets of 20% and 25%, no revenue from carbon storage could be generated beyond a solvent temperature of 25 °C. Additionally, the optimal diameter of the treatment column was more responsive to changes in solvent temperature for cases with low net capture targets (below 10%), while its sensitivity decreased for higher capture targets (above 10%). Graphical Abstract: [Figure not available: see fulltext.

Pipe size sensitivity in pressure relief networks using genetic algorithms

This paper utilizes a stochastic optimization approach using genetic algorithms, for conducting rigorous pipe size sensitivity assessments onto the design of pressure relief networks. By sampling high performance candidates, only the finest options can survive. The pressure relief network system that was investigated in this work was previously reported in literature. The problem is constrained and involves minimizing a cost objective function that evaluates the overall network performance, in which the best pipe size combination should be selected for each segment within the network. The overall goal of this paper was to seek cost-effective designs for the pressure relief piping system by exploring different ranges of pipe diameters that are available for each segment in the network and comparing how the overall design of the system is affected, when the number of pipe size options to select from is varied

Design and thermo-economic evaluation of an integrated concentrated solar power-Desalination tri-generation system

In this work, a concentrated solar power (CSP) tri-generation system that is capable of the simultaneous production of steam, power and freshwater is introduced. The abundantly available direct normal irradiance can potentially allow concentrated solar power systems to become major energy contributors in the desalination market. Since CSPs can generate both thermal and electrical energy, they have been found to be excellent candidates for sustainable operation of large scale desalination systems, in the long term. This paper presents a mathematical model in the form of a Mixed-Integer Nonlinear program (MINLP), which involves a tri-generation system for combined steam and power production, primarily using solar energy to operate steam turbines. Moreover, the option of freshwater production using various desalination technology choices, such as reverse osmosis (RO) and multi-stage flashing (MSF), is also accounted for within the model. Hence, the proposed model offers a very convenient and eco-friendly tri-generation route for steam, power and water production. The proposed systematic method was tested using different feedwater salinities, as well as using different product water flowrates, and electricity prices. According to the results obtained, the water production cost (WPC) associated with a water salinity of 25 g/L resulted in a value of 1.83 USD/m3, which is significantly lower than the WPCs obtained at 35 g/L (2.09 USD/m3) and 45 g/L (2.24 USD/m3). Moreover, a large scale tri-generation system with an overall production capacity of 100,000 m3/d of freshwater resulted in a 60% reduction of the attained WPC value, when compared against a small scale system with a production capacity of 10,000 m3/d of freshwater. The option of exporting electrical energy to the grid using the proposed tri-generation system was also investigated, and a sensitivity analysis was conducted by varying the price of electrical energy. The attained breakeven energy prices were 0.74, 0.79 and 0.82 cent/kWh at 25, 35 and 45 g/L of feedwater salinity, respectively

Investigation of seasonal variations and multiple fuel options in a novel tri-generation CSP integrated hybrid energy process

This work presents a novel Mixed-Integer Non-linear Program (MINLP) that accounts for the presence of multiple fuels in tri-generation systems. The key novelty of this work pertains to the use of hybrid energy systems in tri-generation processes, which are associated with multiple energy sources. In this work, different fuel sources such as natural gas, biomass and municipal solid waste (MSW) have been considered in the model, together with concentrated solar power (CSP), as a renewable energy option. The use of the aforementioned energy sources in tri-generation systems for heat, power and water production, were assessed simultaneously by the proposed model. CSP was utilized as the sole renewable energy option, due to the ease of obtaining both heat and power from such systems. The design of optimal tri-generation systems has been studied using the proposed model, under different conditions for carbon reduction. The model has been formulated using multi-period considerations, so as to account for seasonal variations. Moreover, the effect of several different operating parameters on the land use requirements of such systems were also investigated. The results indicate that despite the high cost of CSP, it was still found to be a highly desirable choice in the presence of carbon taxation. The water production cost of a hybrid natural gas-CSP tri-generation system was estimated at 1.277 USD/m3. This value could be 16% higher in the presence of carbon taxation. Additionally, biomass and solid waste options were found to be very promising energy outlets for desalination, especially in winter and fall seasons which have the lowest DNI values. The selection of these energy streams is also highly affected by the presence of carbon taxation policy. On the other hand, the incorporation of these two energy streams along with CSP could result in a fully local energy independent system with a water production cost of 1.44 and 1.537 USD/m3, respectively

Optimization of multiple fuel utilization options in Tri-generation systems

This work investigates the design of optimal tri-generation systems for heat, power and water production via multiple fuel selections, thus aiming to reduce the reliance on fossil fuel consumption. Generally speaking, tri-generation systems are associated with high levels of carbon dioxide emissions to meet energy and water production requirements. Hence, a shift towards more renewable energy sources can assist in partially reducing the environmental damage associated with standard tri-generation operations. Since the switch from fossil fuels to renewable energy is very costly, hybrid energy systems were found an appealing solution that could allow a gradual reduction of carbon emissions. Hence, the novelty aspect of this work is the ability to generate cost-effective tri-generation systems that incorporate optimal hybrid energy selections and utility generation routes, subject to specific net carbon reduction targets (NCRT). As such, four different energy sources (natural gas, biomass, municipal solid waste (MSW) and Concentrated Solar Power (CSP) were investigated, together with five different routes for steam expansion and electricity production using a Mixed Integer Nonlinear Program (MINLP), including technical, economic and environmental constraints. In order to study the effect of different fuel selections, energy production operations, and water production routes on the performance of tri-generation systems, data from three different desalination plants (located in USA, Cyprus and Qatar) were used. The results obtained show that energy requirements for desalination greatly affects the order of selection of energy sources. In general, biomass was identified as the best alternative to replace natural gas at NCRT values below 40%. On the other hand, MSW incineration using grate-fired and fluidized bed boilers became more desirable for steam production when higher NCRT values were utilized. The water production costs (WPC) of a standalone CSP system integrated with each of the studied plants, having a feedwater salinity of 33.5, 41.8 and 45 g/L, were estimated at 1.739, 2.233 and 2.67 USD/m3, respectively. In addition, an average incremental increase of 5.5% in the WPC has been observed during seasons that provide the lowest solar availability values

A universal transportation model for reverse osmosis systems

This paper presents a new transport model for reverse osmosis (RO) systems, which combines irreversible thermodynamics, together with solution-diffusion theory. The simplifications adopted by the classical theory for solution-diffusion mechanisms have been found to be quite lacking when it comes to predicting the separation of multicomponent mixtures. The presented model accounts for multicomponent computations through the application of thermodynamic property models, as a means to predict the various interactions amongst the species that are present in solution. The developed transport model is relatively easy to implement, and can be utilized alongside existing equipment and thermodynamic property models. The applicability of the model presented in this paper has been tested on three different case studies, including a case that investigates single component behavior and a case that investigates multicomponent behavior The proposed model shows very good agreement with experimental results