Aristotle T. Ubando

Fuzzy mixed-integer linear programming model for optimizing a multi-functional bioenergy system with biochar production for negative carbon emissions

A multi-functional bioenergy system is an efficient way for producing multiple energy products from biomass, which results in near-zero carbon emissions. To achieve net negative carbon emissions, biochar production as carbon sequestration can be integrated in the system. A fuzzy mixed-integer linear programming model is developed to simultaneously design and optimize a multi-functional bioenergy system given multiple product demands, carbon footprint, and economic performance constraints. Case studies are presented involving multi-functional bioenergy systems with biochar production for carbon sequestration. The results show that net negative carbon footprint can be achieved in such systems.

Simultaneous carbon footprint allocation and design of trigeneration plants using fuzzy fractional programming

Trigeneration systems offer an inherently efficient, low-carbon approach to producing useful energy streams. Due to multiple products from a trigeneration system, the challenge of allocating carbon footprint to each energy stream arises, particularly if the streams are sold to different customers. A fuzzy fractional programming model is proposed to design a trigeneration system, taking such allocation into account. The model allows for solving for a configuration that gives the minimum carbon footprint for each energy stream, given a range of values for demand for each product in a trigeneration system. The final design must meet a specified energy output requirement, while satisfying fuzzy carbon footprint limits for all products. The methodology is illustrated using hypothetical but realistic case studies. Sensitivity analysis was carried out to show the effects of changing the system carbon footprint limits.

Analyzing the disruption resilience of bioenergy parks using dynamic inoperability input–output modeling

Bioenergy parks are low-carbon industrial symbiosis networks that are comprised of biomass processing plants. However, such highly integrated energy systems are inherently vulnerable to capacity disruptions. The strong interdependencies among component plants in a bioenergy park decrease system resilience due to cascading failure effect. The consequences of such disruptions are even greater if the critical components are damaged. Resilience is defined as the ability of an energy system to withstand a disruption and subsequently recover to its normal state. In this work, a disruption resilience framework is developed to analyze the resilience of bioenergy parks against an array of capacity disruption scenarios. This framework is derived from dynamic inoperability input–output modeling previously used in economic and critical infrastructure systems. A microalgal multi-functional bioenergy system case study is presented to demonstrate the applicability of the resilience framework. The example shows that the resilience of a bioenergy park is influenced by both the recovery time of component plants and their degree of connectivity within the network; such insights can be used for planning more disruption-resilient bioenergy parks.

A Systematic Approach for Optimization of an Algal Biorefinery Using Fuzzy Linear Programming

Abstract In order to efficiently convert microalgae into value added products, a sustainable integrated algal biorefinery is needed. Generally, conversion of microalgae into biofuel involves several processing steps: cultivation, harvesting, dewatering, drying, oil extraction, and biofuel production. One of the main challenges in designing and optimizing an integrated algal biorefinery is determining the configuration which meets the requirements for key outputs as well as environmental and resource limits. In this work, a systematic fuzzy linear programming (FLP) approach for design and optimization of an integrated algal biorefinery which considers water footprint, land footprint, and carbon footprint is presented. A hypothetical case study is presented to illustrate the proposed approach.

Application of stochastic analytic hierarchy process for evaluating algal cultivation systems for sustainable biofuel production

Algal biomass is considered as a promising source of alternative fuel energy given its high yield per land area and other potential benefits. Categorized as an advanced generation biofuel feedstock, microalgae are grown in non-conventional ways through different cultivation systems. A preference of a cultivation system may vary depending on a given scenario and its inherent configuration (strength and weakness). Hence, the usage of a specific cultivation system to sustainably produce algal biofuels depends on various factors. Thus, a multi-criteria approach based on analytic hierarchy process (AHP) is proposed for evaluating alternative cultivation systems for sustainable production of algal biofuels. The main criteria considered to evaluate the alternatives based on consultation with a panel of expert and from literature are environmental impact, energy consumption, economic viability, social acceptability, and system robustness. Sub-criteria were identified under each main criterion to further qualify the analysis into relevant sub-factors in the sustainable production of algal biofuels. Three cultivations systems were used as an example to demonstrate the developed decision model using qualitative data and quantitative data. Probabilistic scenarios were analyzed using stochastic approach via Monte Carlo simulation. The results of the stochastic-based AHP showed which cultivation system is preferred for conservative (risk-averse) and optimistic (risk-inclined) scenarios.

Fuzzy Multi-Objective Approach for Designing of Biomass Supply Chain for Polygeneration With Triple Footprint Constraints

Polygeneration systems produce multiple energy products (i.e. electricity, heat, cooling), and other biochemical products (biofuels and syngas). Such systems offer a sustainable approach in meeting the ever-growing demand of energy, while reducing its environmental impact. The optimal design of such systems should consider the design of the supply-chain in producing the targeted energy products to reduce the resource consumption and waste generation and to maximize its economic potential. One of the important considerations in designing such a system is whether to out-source its raw materials or to produce them in-house. The criteria for such decision strategies are assessed through economics, product demand, and environmental impact. One holistic way to measure the environmental impact of such system is to consider the triple footprint: carbon, water, and land. The objective of this work is to maximize the economic potential while maintaining the footprints at acceptable levels and simultaneously meeting product demands. In this study, an adoption of fuzzy multi-objective approach is presented wherein the economic potential is introduced as a constraint. Moreover, predefined fuzzy trapezoidal-shaped limits for the product demand constraints are used which mimics the probabilistic demand scenario for each of the product streams. Lastly, the triple footprint constrains is utilized to assess the environmental impact of the polygeneration. The technique is demonstrated using a modified industrial case study of a polygeneration system.Copyright

Life cycle validation study of algal biofuels in Philippines via CML impact assessment

Biodiesel is seen as one of the promising alternatives for fossil-based fuels while reducing the carbon dioxide emissions. However, as first generation biodiesels are derived from food crops, the concern on food versus fuel heightens. As such, algal biodiesel is perceived as a solution to this problem, due to its lesser land requirement while having high oil yield compared to biofuels derived from conventional feedstocks. As the Philippines is considered as a thriving habitat for numerous microalgae species in the tropics, it offers a big potential for algae biofuel production. However, like any other bioenergy system, algal biofuels require natural resource consumption and entails environmental impact. Hence, a life cycle assessment approach is proposed in this study to assess the current microalgae cultivation setup in the Philippines. A validation study is conducted to compare the results of an aquaculture setup in the Philippines and a cultivation system by Khoo et al. (2011). The functional unit used is 1 ton algal biodiesel. The results of the study revealed that the cultivation system found in the Philippines has performed well as compared to Khoo et al. (2011), in terms of the impact assessment and energy consumption. However, the study also found that the energy return on energy invested (EROEI) of the two models were less than the benchmark value of one. Thus, the result of this study can be used to improve the EROEI of the algal biodiesel life cycle in the Philippines.

Synthesis of Cogeneration, Trigeneration, and Polygeneration Systems Using Target-Oriented Robust Optimization

Simultaneous generation of heat, cooling, and other secondary products along with electricity can be more efficient than stand-alone production of these individual streams, due to the opportunities for process integration that naturally arise in such systems. Various cogeneration, trigeneration, and polygeneration schemes can also be configured to achieve operational flexibility to cope with a variable supply of fuels and feedstocks, as well as fluctuating product demand. However, techno-economic risks resulting from long-term uncertainties in the prices of both inputs and outputs can be a barrier to investing in these efficient systems. Hence, this chapter presents a target-oriented robust optimization (TORO) approach for dealing with parametric uncertainties in the synthesis of cogeneration, trigeneration, and polygeneration systems. The model is formulated as a mixed-integer nonlinear program (MINLP), and candidate designs at different levels of robustness can be assessed using Monte Carlo simulation. The methodology is illustrated with a case study on the synthesis of a cogeneration plant.

Fuzzy mathematical programming approach in the optimal design of an algal bioenergy park

a Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue Manila, Philippines b Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue Manila Philippines 1004 c Chemical Engineering Department, De La Salle University, 2401 Taft Avenue Manila, Philippines d Agricultural and Biosystems Engineering Department, The University of Arizona, Tucson, Arizona, USA e Deaprtment fo Chemical and Environmental Engineering/ Centre of Excellence for Green Technologies, The University of Nottingham, Malaysia Campus, Semenyih, Malaysia f Center for Engineering and Sustainable Development Research, De La Salle University, Manila, Philippines aristotle.ubando@dlsu.edu.ph

Priority Evaluation of Life Cycle Impact Factors for Algal Biofuel Production in the Philippines Using Analytic Hierarchy Process

Algal biofuel is considered as an advanced generation bioenergy fuel which addresses the concerns of the preceding generations of biofuels on crop land competition and water consumption. Microalgae are considered as the only biomass feedstock capable of displacing fossil-fuel based on very high-oil yield per land area and other benefits. The production of biofuels in the Philippines is mandated by its Biofuel Act of 2006 which aims to introduce low-carbon fuels to mitigate greenhouse gas emissions and reduce the dependence on oil imports. The Philippines’ biodiesel production uses solely coconut as biomass feedstock to produce coconut methyl ester (CME). With the mandate to increase the biodiesel blend to 5% by 2015, this adds pressure to the production of CME while battling for the fluctuating price of coconut. Due to the archipelagic geography and tropical climate of the country, abundance of thriving endemic species of microalgae can be found in the country. Hence, algal biofuel presents a viable option to alternatively produce biodiesel in the Philippines. Thus, policies in sustainable production of algal biofuel based on its environmental impact and natural resource consumption must initially be developed and drafted. A life-cycle assessment (LCA) approach was recommended to evaluate the sustainability of algal biofuel production in the country leading to policy development. Prior finalizing the impact assessment of an LCA study, prioritization of impact factors must initially be established and evaluated based on the programs and goals of the government and other stakeholders. LCA studies on algal biofuels were previously conducted overseas. However, the impact assessment of such studies is not applicable for the Philippines. Furthermore, there has been limited LCA study on algal biofuel production in the Philippines. Hence, this study proposes to establish a multi-criteria decision structure of the life-cycle impact factors of algal biofuels specifically for the Philippines and quantifying its priority levels using Analytic Hierarchy Process (AHP). AHP is a multi-criteria decision analysis which quantifies the prioritization weights of the considered impact factors via pairwise comparison method. Survey shall be conducted to various government agencies, the industry, and other research institutions to establish an initial impact assessment of algal biofuels in the country. The initial results revealed priority are given to global warming potential, eco-toxicity, and photochemical ozone depletion, respectively. The results of this work shall aid the policy and decision makers of the country to develop and draft environmental policies and strategic plans for the proliferation of algal biofuels in the Philippines.