Carbon Policies in the Optimal Design of Power Plants Involving Chemical Looping Combustion and Algae Systems

In search of power generation systems with minor environmental impact, the use of chemical looping combustion (CLC) in the generation of electricity has been proposed. This novel technology is classified as a variety of post-combustion, oxy-combustion and pre-combustion. It enables to capture the carbon dioxide with small penalties in thermal efficiency (Anheden and Svedberg, 1998). The basic principles of CLC systems and their potential application in power generation cycles har e been widely reported (Isliida and Jin, 1996a: Ishida and Jin, 1997b; Isliida and Jin, 2001c). Previous simulation studies have addressed the technical and economic feasibility as well as the sensitivity analysis of several parameters involved in this type of systems (fuels, oxygen carriers, CLC configurations, and power cycles) (Petriz-Prieto et al„ 2016; Zliu et al., 2015). After the CO, is captured, its utilization is desirable. An alternative that has recently gamed attention is sending the gas to an algae cultivation system. A microalgae system consists of different stages (cultivation, harvesting, extraction and production) to process the algal biomass and produce biofuels along with other valuable byproducts such as glycerol, ethanol and proteins (Dickinson et al., 2017). Some optimization approaches have addressed the integration of power plants with algae systems. For instance, Gutierrez-Arriaga et al. (2014) reported an analysis including energy integration, a conventional power plant (without modifying combustion systems) and a single-process evaluation for each stage of the algae cultivation system. The model involves economic and environmental objectives to obtain tradeoff solutions.

Model formulation

In this context, a mathematical model for the optimal integration of power plants involving chemical looping combustion with algae systems has been proposed (Munguia-Lopez et al., 2018). The model accounts for the optimal selection of the processes for each stage of the algae cultivation system as well as the optimum operation conditions, combustion systems and power cycles for the power generation plant. Economic and environmental objectives are taken into account including the maximization of the profit and the minimization of the emissions. The sales of electricity, biodiesel, glycerol, ethanol and proteins as well as the costs associated with the global system are considered. The generated carbon dioxide in the power plant and the amount sent to the algae-to-biodiesel process are considered as well. Besides, the impact of carbon taxes and tax credits on the objective functions and on the optimal configuration is evaluated. The problem was formulated as a MILP model that represents the global system at a macroscopic level. The proposed superstructure to represent the potential configurations is shown in Figure 2.

The mathematical model formulation includes several relationships to compute the flow rates, requirements, costs, revenues and the selection of the optimum technologies. The profit is computed considering the total sales {IN), capital costs (CAP) and operating costs (COPER). When the carbon tax (ССТЛХ) is evaluated, the profit (PTAX) is estimated by equation (1). Equation (2) is required in order to compute the profit (pC0MP) when the carbon tax credit (CCOMP) is analyzed. The corresponding penalization and compensation are given depending on the total emissions and on the avoided emissions, respectively. To obtain the total emissions, the CO, mitigated by the algae system is subtracted from the CO, generated in the power plant, as indicated in equation (3). The avoided emissions are defined by the difference between the emissions generated in a conventional system and the total emissions in the integrated system.

Superstructure to represent the possibilities for the integrated system

Figure 2. Superstructure to represent the possibilities for the integrated system


Although the objectives are opposite, the constraint method (Diwekar, 2008) is employed as solution procedure to generate the set of optimal solutions or Pareto front. The optimization results were obtained by solving the model using parameters reported in the literature. When the carbon taxes were evaluated, the Pareto curves presented in Figure 3 were obtained. The tradeoffs between the economic and environmental objectives can be identified through the Pareto front. As expected, with solutions involving higher profits the emissions increase as well. However, there are solutions where the generated emissions are low, and the system is still profitable. Each optimal solution of the Pareto set refers to

Pareto curves considering distinct penalties for the generation of CO, emissions

Figure 3. Pareto curves considering distinct penalties for the generation of CO, emissions.

Pareto curves considering distinct compensations for the avoided CO, emissions

Figure 4. Pareto curves considering distinct compensations for the avoided CO, emissions.

Variation of emissions according to different cases

Figure 5. Variation of emissions according to different cases.

a different configuration in terms of the selection of energy sources and technologies, including their required specific conditions. Note that there is no further reduction in emissions despite increasing the tax. This occurs because the evaluated penalizations are not enough to promote the use of processes that contribute to further reducing emissions.

On the other hand, the results involving the carbon tax credits are shown in Figure 4. When the highest compensation values are evaluated (120 and 130 S/ton CO,), important reductions in emissions throughout the Pareto front are obtained. Therefore, a maximum profit solution including low emissions can be attained. Notice that with the rest of the tax credits, only variations in the profit are observed. The impact of considering the penalizations and compensations in the integrated system can be observed by comparing the results with the generated emissions in a conventional system (without CLC or algae systems). This comparison is presented in Figure 5. The three solutions can be compared because their optimal configuration for the technologies in the power plant is equal and, thus, the net electricity is as well. Note that the highest compensation and the lowest penalization were considered in order to find the best economic and environmental solution (as described above, no further reduction of the emissions was found with greater taxes). The reduction in emissions for the considered tax and tax credit scenarios is similar: 70 and 71%, respectively. Regarding the economic objective, higher profits are attained with the carbon compensations. Therefore, it is concluded that involving tax credits for the avoided emissions gives better tradeoffs among the objective functions. Furthermore, the benefits of considering carbon policies as a strategy to reduce emissions and simultaneously attain a profitable system of power generation and biofuels production are identified. Through the different tradeoff solutions of the Pareto front, decision makers can select specific configurations depending on the power demand and on economic or environmental restrictions.

Carbon Policies in the Optimal Design of Water Distribution Networks Involving Power-Desalination Plants

The use of renewable resources, such as solar energy and biofuels, in energy systems has been proposed to reduce the environmental impact. Additionally, the simultaneous production of water and electricity in power-desalination plants (Gonzalez-Bravo et al., 2015) and polygeneration plants (Rubio-Maya et al., 2011) has been presented as an alternative for the increasing demands of water and electric energy. In this regard, it is important to identify the optimum configurations and renewable energies that lead to efficient systems involving savings in power consumption and costs. Also, other aspects to consider are energy availability and consumption as well as economic and environmental impacts (Al-Karaghouli and Kazmerski, 2013). Particularly for desert regions, solar energy facilities can be more easily implemented because of the high solar radiation and the availability of large areas. Gonzalez-Bravo et al. (2015) reported a case study for a problem related to water scarcity in the Sonoran Desert. This approach includes a system involving seawater desalination plants integrated with power plants using solar energy.

Model formulation

Recently, carbon taxes and tax credits have been evaluated in a macroscopic water distribution network integrated with power-desalination plants (Munguia-Lopez et al., 2019). Taxes and tax credits are applied to water management as well. The optimization approach accounts for economic, environmental and social aspects to find a design that represents an alternative to reduce emissions and water scarcity. Solar energy, biofuels, water storage tanks, and the possibility of sending water to recharge aquifers are considered. Hie proposed model involves the selection of the optimum energy resource and the optimum configuration of the integrated system to satisfy demands for domestic, agr icultural and industrial users. The objective function consists of maximizing the annual profit while, through the taxes and credits, a positive impact on the environmental (generated emissions, extracted water, and recharge of aquifers) and social (generation of jobs) functions is expected. Furthermore, the model formulation includes the electricity generation in existing and new dual-purpose power plants, availability restrictions for the renewable energy, existing and new water storage tanks, and variation in the demands. To represent the different alternatives for the design of the system under compensations and penalizations, the superstructures presented in Figure 6 are proposed and evaluated through an optimization model.

Several carbon taxes and carbon tax credits are evaluated in order to find tlierr impact on the objective function and on the reduction in CO, emissions as well as on the generation of jobs. A decrease in emissions is achieved by satisfying part of the energy requirements with biofuels and solar collectors.

The overall greenhouse gas emissions (GHGE) are estimated considering the emissions for fuels and biofuels, as presented in equation (4). The emissions for the solar collector are assumed to be zero. The economic penalty is function of the generated emissions and is computed as shown in equation (5). The parameter C’m symbolizes the unitary carbon tax, which is a cost per ton of produced CO,. In contrast, the economic compensation for avoiding emissions is presented in equation (6). The parameter CrreA' refers to the unitary tax credit. Hie compensation depends on the variable amount of avoided emissions, which is given by the difference between the generated emissions in a conventional system (F"m) and the emissions in the proposed system, as indicated in equation (6).

The problem was solved considering the objective function of maximizing the annual profit. This economic function was estimated involving the sales of water and energy minus the total annual costs. When the carbon tax was evaluated, the corresponding penalization was included in the objective function as well as the compensation when the tax credits are analyzed. The variation on the reduction in emissions and on the generated jobs with the different taxation schemes was described as well.


The presented model is general and applicable to any case study. In this approach, the results were obtained based on a water and energy management problem in Hermosillo, Sonora, Mexico. Hemiosillo city is located in a desert region (Sonoran Desert) and it represents a potential place to implement the proposed system. It is an optimum location for solar collectors because of the high direct normal irradiation (around 3000 kWh/т2). In this case study, existing and new power-desalination plants are considered to satisfy the electricity demands. Also, the variation in the availability of biofuels depending on the seasons and the generation of agricultural wastes is involved. More details of the case study have been previously reported (Gonzalez-Bravo et al., 2015).

The optimization results related to the carbon tax are presented in Figure 7. Besides the penalizations reported in the literature (10,15,25,32.41 and, 52 S/ton CO,), a greater tax of 115 S/tonCO, was included in the analysis. This economic penalty represents the uecessaiy tax to find better values for environmental and social functions. That means the minimum amount of greenhouse gas emissions (GHGE) and the maximum number of jobs. The solution with the highest tax shows that with the appropriate penalization further environmental and social benefits can be achieved, although the economic objective can be compromised. As shown in Figure 7, the solution with this tax gives the best values for the emissions and jobs (14,484,014 ton CO,/year and 12,647 generated jobs) and the worst value of the Pareto front for the profit (-39 MMS/year). On the other hand, it was found that even with the lowest tax (10 $/'ton CO,), a reduction in the emissions with a positive value for the profit is obtained. However, this reduction is not maximum. Evaluating the rest of the taxes, lower values for the profit are achieved as the penalty increases. Therefore, tradeoffs among the economic, environmental and social functions can be identified through the Pareto front, as well as the cost of reducing emissions and generating jobs.

The sets of optimal solutions for the carbon tax credits analysis are presented in Figure 8. The Pareto sets show compromise solutions for the emissions, generated jobs and profit. Various economic compensations were evaluated (0.3, 1, 4, 7, 10, 80, 120 and. 130 S/ton CO, avoided) (Kossoy et al.,

2015). The decrease in emissions and the rise in the generation of jobs start at a tax credit equal to 7 $/ ton CO,. As expected, with higher tax credits better values for the environmental and social functions are achieved as well as for the economic objective (as opposed to the carbon taxes). Specifically, with the greatest compensation, the reduction in emissions and the generated jobs are maximum as well as with

Pareto curves considering different carbon taxes for the integrated system

Figure 7. Pareto curves considering different carbon taxes for the integrated system.

Pareto curves considering different carbon tax credits for the integrated system

Figure 8. Pareto curves considering different carbon tax credits for the integrated system.

the highest penalization. However, involving the tax credits higher profits can be attained. Despite the fact that the profit is contrary to the other functions, it is possible to find its highest value (1635 MMS/year) along with the minimum amount of emissions and the maximum number of jobs due to the considered tax credit. Therefore, in this analysis, the tradeoff between the environmental and economic functions is represented by the required tax credit. Regarding the energy resources, the case of the tax credit equal to 130 $/ton CO, results in the solution with fewer fossil fuels consumption. Biogas and biomass are used to fulfill the total energy requirement.

The proposed methodology presents optimal configurations for water distribution networks involving power-desalination plants. Furthermore, the potential application of the model was illustrated through a case study. Results show the benefits of applying taxes and tax credits to the generated and avoided emissions, while through the Pareto front, compromises between the environmental and social functions are identified while maximizing the profit.

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