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Charlle L. Sy
Center for Engineering and Sustainable Development Research, De La Salle University, Manila 0922, Philippines

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Journal article
Published: 01 June 2021 in Journal of Sustainable Development of Energy, Water and Environment Systems
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ACS Style

Jayne San Juan; Charlle Charlle Sy. Multi-Objective Target-Oriented Robust Optimization of Biomass Co-Firing Networks Under Quality Uncertainty. Journal of Sustainable Development of Energy, Water and Environment Systems 2021, 9, 1 -26.

AMA Style

Jayne San Juan, Charlle Charlle Sy. Multi-Objective Target-Oriented Robust Optimization of Biomass Co-Firing Networks Under Quality Uncertainty. Journal of Sustainable Development of Energy, Water and Environment Systems. 2021; 9 (2):1-26.

Chicago/Turabian Style

Jayne San Juan; Charlle Charlle Sy. 2021. "Multi-Objective Target-Oriented Robust Optimization of Biomass Co-Firing Networks Under Quality Uncertainty." Journal of Sustainable Development of Energy, Water and Environment Systems 9, no. 2: 1-26.

Journal article
Published: 04 March 2021 in Energies
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Biofuel production from microalgae biomass has been considered a viable alternative to harmful fossil fuels; however, challenges are faced regarding its economic sustainability. Process integration to yield various high-value bioproducts is implemented to raise profitability and sustainability. By incorporating a circular economy outlook, recirculation of resource flows is maximized to yield economic and environmental benefits through waste minimization. However, previous modeling studies have not looked into the opportunity of integrating productivity reduction related to the continuous recirculation and reuse of resources until it reaches its end of life. In this work, a novel multi-objective optimization model is developed centered on an algal biorefinery that simultaneously optimizes cost and environmental impact, adopts the principle of resource recovery and recirculation, and incorporates the life cycle assessment methodology to properly account for the environmental impacts of the system. An algal biorefinery involving end-products such as biodiesel, glycerol, biochar, and fertilizer was used for a case study to validate the optimization model. The generated optimal results are assessed and further analyzed through scenario analysis. It was seen that demand fluctuations and process unit efficiencies have significant effect on the optimal results.

ACS Style

Celine Solis; Jayne San Juan; Andres Mayol; Charlle Sy; Aristotle Ubando; Alvin Culaba. A Multi-Objective Life Cycle Optimization Model of an Integrated Algal Biorefinery toward a Sustainable Circular Bioeconomy Considering Resource Recirculation. Energies 2021, 14, 1416 .

AMA Style

Celine Solis, Jayne San Juan, Andres Mayol, Charlle Sy, Aristotle Ubando, Alvin Culaba. A Multi-Objective Life Cycle Optimization Model of an Integrated Algal Biorefinery toward a Sustainable Circular Bioeconomy Considering Resource Recirculation. Energies. 2021; 14 (5):1416.

Chicago/Turabian Style

Celine Solis; Jayne San Juan; Andres Mayol; Charlle Sy; Aristotle Ubando; Alvin Culaba. 2021. "A Multi-Objective Life Cycle Optimization Model of an Integrated Algal Biorefinery toward a Sustainable Circular Bioeconomy Considering Resource Recirculation." Energies 14, no. 5: 1416.

Original research paper
Published: 28 January 2021 in Process Integration and Optimization for Sustainability
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The novel coronavirus disease 2019 (COVID-19) is a truly wicked problem which has remained a stubborn issue plaguing multiple countries worldwide. The continuously increasing number of infections and deaths has driven several countries to implement control and response strategies including community lockdowns, physical distancing, and travel bans with different levels of success. However, a disease outbreak and the corresponding policies can cause disastrous economic consequences due to business closures and risk minimization behaviors. This paper develops a system dynamics framework of a disease outbreak system covering various policies to evaluate their effectiveness in mitigating transmission and the resulting economic burden. The system dynamics modeling approach captures the relationships, feedbacks, and delays in such a system, revealing meaningful insights on the dynamics of several response strategies.

ACS Style

Charlle Sy; Phoebe Mae Ching; Jayne Lois San Juan; Ezekiel Bernardo; Angelimarie Miguel; Andres Philip Mayol; Alvin Culaba; Aristotle Ubando; Jose Edgar Mutuc. Systems Dynamics Modeling of Pandemic Influenza for Strategic Policy Development: a Simulation-Based Analysis of the COVID-19 Case. Process Integration and Optimization for Sustainability 2021, 1 -14.

AMA Style

Charlle Sy, Phoebe Mae Ching, Jayne Lois San Juan, Ezekiel Bernardo, Angelimarie Miguel, Andres Philip Mayol, Alvin Culaba, Aristotle Ubando, Jose Edgar Mutuc. Systems Dynamics Modeling of Pandemic Influenza for Strategic Policy Development: a Simulation-Based Analysis of the COVID-19 Case. Process Integration and Optimization for Sustainability. 2021; ():1-14.

Chicago/Turabian Style

Charlle Sy; Phoebe Mae Ching; Jayne Lois San Juan; Ezekiel Bernardo; Angelimarie Miguel; Andres Philip Mayol; Alvin Culaba; Aristotle Ubando; Jose Edgar Mutuc. 2021. "Systems Dynamics Modeling of Pandemic Influenza for Strategic Policy Development: a Simulation-Based Analysis of the COVID-19 Case." Process Integration and Optimization for Sustainability , no. : 1-14.

Journal article
Published: 21 September 2020 in Sustainability
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Given increasing energy demand and global warming potential, the advancements in bioenergy production have become a key factor in combating these issues. Biorefineries have been effective in converting biomass into energy and valuable products with the added benefits of treating wastewater used as a cultivation medium. Recent developments enable relationships between sewage sludge and microalgae that could lead to higher biomass and energy yields. This study proposes a multi-objective optimization model that would assist stakeholders in designing an integrated system consisting of wastewater treatment systems, an algal-based bioenergy park, and a sludge-based bioenergy park that would decide which processes to use in treating wastewater and sludge while minimizing cost and carbon emissions. The baseline run of the model showed that the three plants were utilized in treating both sludge and water for the optimal answer. Running the model with no storage prioritizes water disposal, while having storage can help produce more energy. Sensitivity analysis was performed on storage costs and demand. Results show that decreasing the demand is directly proportional to the total costs while increasing it can help reduce expected costs through storage and utilizing process capacities. Costs of storage do not cause a huge overall difference in costs and directly follow the change.

ACS Style

Jayne Juan; Carlo Caligan; Maria Garcia; Jericho Mitra; Andres Mayol; Charlle Sy; Aristotle Ubando; Alvin Culaba. Multi-Objective Optimization of an Integrated Algal and Sludge-Based Bioenergy Park and Wastewater Treatment System. Sustainability 2020, 12, 7793 .

AMA Style

Jayne Juan, Carlo Caligan, Maria Garcia, Jericho Mitra, Andres Mayol, Charlle Sy, Aristotle Ubando, Alvin Culaba. Multi-Objective Optimization of an Integrated Algal and Sludge-Based Bioenergy Park and Wastewater Treatment System. Sustainability. 2020; 12 (18):7793.

Chicago/Turabian Style

Jayne Juan; Carlo Caligan; Maria Garcia; Jericho Mitra; Andres Mayol; Charlle Sy; Aristotle Ubando; Alvin Culaba. 2020. "Multi-Objective Optimization of an Integrated Algal and Sludge-Based Bioenergy Park and Wastewater Treatment System." Sustainability 12, no. 18: 7793.

Original research paper
Published: 02 September 2020 in Process Integration and Optimization for Sustainability
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Micro hydroelectric power is a clean and efficient source of energy that has been used for the electrification of rural off-grid communities. However, numerous micro hydro installations have failed as caused by factors such as poor site selection and uneconomical design of materials, among others. A multi-period mixed integer linear programming model for the design of an off-grid micro hydro power plant is then developed. The proposed model is able to provide technical specifications such as the penstock dimensions, turbine choice, weir height, and site choice in order to fulfill a community’s demand while simultaneously maximizing the net present value of the investment. The model may choose among different productive end uses, with each being subject to a respective investment cost as well as a set-up time and degradation rate. Computational experiments demonstrate the different capabilities of the model to address real-life scenarios such as population growth and streamflow variability. An increase in energy consumption due to population growth leads to the requirement of a more powerful turbine. Capacity limitations likewise prevent the community to invest in productive end usage. Meanwhile, streamflow variability potentially reduces the capability of the power plant to produce electricity. In these instances, batteries had to simultaneously be used in order to augment the increase in energy requirement.

ACS Style

Juan Carlo Hernandez; Carlos Jan Peñas; Adrianne Ressa Tiu; Charlle Sy. A Multi-period Optimization Model for the Design of an Off-Grid Micro Hydro Power Plant with Profitability and Degradation Considerations. Process Integration and Optimization for Sustainability 2020, 5, 193 -205.

AMA Style

Juan Carlo Hernandez, Carlos Jan Peñas, Adrianne Ressa Tiu, Charlle Sy. A Multi-period Optimization Model for the Design of an Off-Grid Micro Hydro Power Plant with Profitability and Degradation Considerations. Process Integration and Optimization for Sustainability. 2020; 5 (2):193-205.

Chicago/Turabian Style

Juan Carlo Hernandez; Carlos Jan Peñas; Adrianne Ressa Tiu; Charlle Sy. 2020. "A Multi-period Optimization Model for the Design of an Off-Grid Micro Hydro Power Plant with Profitability and Degradation Considerations." Process Integration and Optimization for Sustainability 5, no. 2: 193-205.

Short communication
Published: 29 July 2020 in Process Integration and Optimization for Sustainability
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The coronavirus disease 2019 (COVID-19) outbreak has burdened several countries. Its high transmissibility and mortality rate have caused devastating impacts on human lives. This has led countries to implement control strategies, such as social distancing, travel bans, and community lockdowns, with varying levels of success. However, a disease outbreak can cause significant economic disruption from business closures and risk avoidance behaviors. This paper raises policy recommendations through a system dynamics modeling approach. The developed model captures relationships, feedbacks, and delays present in a disease transmission system. The dynamics of several policies are analyzed and assessed based on effectiveness in mitigating infection and the resulting economic strain.

ACS Style

Charlle Sy; Ezekiel Bernardo; Angelimarie Miguel; Jayne Lois San Juan; Andres Philip Mayol; Phoebe Mae Ching; Alvin Culaba; Aristotle Ubando; Jose Edgar Mutuc. Policy Development for Pandemic Response Using System Dynamics: a Case Study on COVID-19. Process Integration and Optimization for Sustainability 2020, 4, 497 -501.

AMA Style

Charlle Sy, Ezekiel Bernardo, Angelimarie Miguel, Jayne Lois San Juan, Andres Philip Mayol, Phoebe Mae Ching, Alvin Culaba, Aristotle Ubando, Jose Edgar Mutuc. Policy Development for Pandemic Response Using System Dynamics: a Case Study on COVID-19. Process Integration and Optimization for Sustainability. 2020; 4 (4):497-501.

Chicago/Turabian Style

Charlle Sy; Ezekiel Bernardo; Angelimarie Miguel; Jayne Lois San Juan; Andres Philip Mayol; Phoebe Mae Ching; Alvin Culaba; Aristotle Ubando; Jose Edgar Mutuc. 2020. "Policy Development for Pandemic Response Using System Dynamics: a Case Study on COVID-19." Process Integration and Optimization for Sustainability 4, no. 4: 497-501.

Journal article
Published: 12 June 2019 in Energies
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The growth in energy demand, coupled with declining fossil fuel resources and the onset of climate change, has resulted in increased interest in renewable energy, particularly from biomass. Co-firing, which is the joint use of coal and biomass to generate electricity, is seen to be a practical immediate solution for reducing coal use and the associated emissions. However, biomass is difficult to manage because of its seasonal availability and variable quality. This study proposes a biomass co-firing supply chain optimization model that simultaneously minimizes costs and environmental emissions through goal programming. The economic costs considered include retrofitting investment costs, together with fuel, transport, and processing costs, while environmental emissions may come from transport, treatment, and combustion activities. This model incorporates the consideration of feedstock quality and its impact on storage, transportation, and pre-treatment requirements, as well as conversion yield and equipment efficiency. These considerations are shown to be important drivers of network decisions, emphasizing the importance of managing biomass and coal blend ratios to ensure that acceptable fuel properties are obtained.

ACS Style

Jayne Lois G. San Juan; Kathleen B. Aviso; Raymond R. Tan; Charlle L. Sy; Juan; Tan; Sy. A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations. Energies 2019, 12, 2252 .

AMA Style

Jayne Lois G. San Juan, Kathleen B. Aviso, Raymond R. Tan, Charlle L. Sy, Juan, Tan, Sy. A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations. Energies. 2019; 12 (12):2252.

Chicago/Turabian Style

Jayne Lois G. San Juan; Kathleen B. Aviso; Raymond R. Tan; Charlle L. Sy; Juan; Tan; Sy. 2019. "A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations." Energies 12, no. 12: 2252.

Journal article
Published: 25 May 2019 in Journal of Cleaner Production
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Rapid global industrial development has led to a significant increase in waste generation, including wastewater. Improper disposal of wastewater leads to the degradation of water bodies, endangering marine life and posing health hazards to the nearby communities. This study addresses the current lack of integration in the design of wastewater treatment plants and the challenge presented by the conflicting criteria of economic impact and environmental cost. A multi-period and multi-criterion non-linear programming model for a wastewater treatment plant that simultaneously considers economic and environmental tradeoffs, alternative plant configurations, disposal and reuse options is then developed. The study considers the variability of inputs in the form of water quality and quantity in order to demonstrate the natural variations presented by wastewater sources across a planning horizon. The proposed model is applied to a case study of an actual water utility company in the Philippines. It was seen that the integration of disposal and reuse options had facilitated the realization of improved economic and environmental benefits as it was able to match the effluent water quality to the best suited option. The model enabled the improvement of the treatment process of wastewater inputs by considering alternative methods of entry such as series and parallel configurations instead of just having a mixed input configuration. This significantly improved relevant metrics such as processing time and operational costs.

ACS Style

Michael S. Ang; Jensen Duyag; Kimberly C. Tee; Charlle L. Sy. A multi-period and multi-criterion optimization model integrating multiple input configurations, reuse, and disposal options for a wastewater treatment facility. Journal of Cleaner Production 2019, 231, 1437 -1449.

AMA Style

Michael S. Ang, Jensen Duyag, Kimberly C. Tee, Charlle L. Sy. A multi-period and multi-criterion optimization model integrating multiple input configurations, reuse, and disposal options for a wastewater treatment facility. Journal of Cleaner Production. 2019; 231 ():1437-1449.

Chicago/Turabian Style

Michael S. Ang; Jensen Duyag; Kimberly C. Tee; Charlle L. Sy. 2019. "A multi-period and multi-criterion optimization model integrating multiple input configurations, reuse, and disposal options for a wastewater treatment facility." Journal of Cleaner Production 231, no. : 1437-1449.

Research article
Published: 08 June 2018 in Frontiers in Energy
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An emerging alternative solution to address energy shortage is the construction of a microgrid system. This paper develops a mixed-integer linear programming microgrid investment model considering multi-period and multi-objective investment setups. It further investigates the effects of uncertain demand by using a target-oriented robust optimization (TORO) approach. The model was validated and analyzed by subjecting it in different scenarios. As a result, it is seen that there are four factors that affect the decision of the model: cost, budget, carbon emissions, and useful life. Since the objective of the model is to maximize the net present value (NPV) of the system, the model would choose to prioritize the least cost among the different distribution energy resources (DER). The effects of load uncertainty was observed through the use of Monte Carlo simulation. As a result, the deterministic model shows a solution that might be too optimistic and might not be achievable in real life situations. Through the application of TORO, a profile of solutions is generated to serve as a guide to the investors in their decisions considering uncertain demand. The results show that pessimistic investors would have lower NPV targets since they would invest more in storage facilities, incurring more electricity stock out costs. On the contrary, an optimistic investor would tend to be aggressive in buying electricity generating equipment to meet most of the demand, however risking more storage stock out costs.

ACS Style

Lanz Uy; Patric Uy; Jhoenson Siy; Anthony Shun Fung Chiu; Charlle Sy. Target-oriented robust optimization of a microgrid system investment model. Frontiers in Energy 2018, 12, 440 -455.

AMA Style

Lanz Uy, Patric Uy, Jhoenson Siy, Anthony Shun Fung Chiu, Charlle Sy. Target-oriented robust optimization of a microgrid system investment model. Frontiers in Energy. 2018; 12 (3):440-455.

Chicago/Turabian Style

Lanz Uy; Patric Uy; Jhoenson Siy; Anthony Shun Fung Chiu; Charlle Sy. 2018. "Target-oriented robust optimization of a microgrid system investment model." Frontiers in Energy 12, no. 3: 440-455.

Chapter
Published: 22 December 2017 in Smart and Sustainable Planning for Cities and Regions
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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.

ACS Style

Charlle L. Sy; Kathleen B. Aviso; Aristotle T. Ubando; Raymond R. Tan. Synthesis of Cogeneration, Trigeneration, and Polygeneration Systems Using Target-Oriented Robust Optimization. Smart and Sustainable Planning for Cities and Regions 2017, 155 -171.

AMA Style

Charlle L. Sy, Kathleen B. Aviso, Aristotle T. Ubando, Raymond R. Tan. Synthesis of Cogeneration, Trigeneration, and Polygeneration Systems Using Target-Oriented Robust Optimization. Smart and Sustainable Planning for Cities and Regions. 2017; ():155-171.

Chicago/Turabian Style

Charlle L. Sy; Kathleen B. Aviso; Aristotle T. Ubando; Raymond R. Tan. 2017. "Synthesis of Cogeneration, Trigeneration, and Polygeneration Systems Using Target-Oriented Robust Optimization." Smart and Sustainable Planning for Cities and Regions , no. : 155-171.

Book chapter
Published: 01 January 2017 in Computer Aided Chemical Engineering
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ACS Style

Kathleen B. Aviso; Charlle L. Sy; Raymond R. Tan. A Target Oriented Robust Optimization Model for Selection of Engineering Project Portfolio under Uncertainty. Computer Aided Chemical Engineering 2017, 949 -954.

AMA Style

Kathleen B. Aviso, Charlle L. Sy, Raymond R. Tan. A Target Oriented Robust Optimization Model for Selection of Engineering Project Portfolio under Uncertainty. Computer Aided Chemical Engineering. 2017; ():949-954.

Chicago/Turabian Style

Kathleen B. Aviso; Charlle L. Sy; Raymond R. Tan. 2017. "A Target Oriented Robust Optimization Model for Selection of Engineering Project Portfolio under Uncertainty." Computer Aided Chemical Engineering , no. : 949-954.

Journal article
Published: 01 December 2016 in Energy
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Production of clean, low-carbon energy and by-products is possible through the use of highly integrated, efficient systems such as polygeneration plants. Mathematical programming methods have proven to be valuable for the optimal synthesis of such systems. However, in practice, numerical parameters used in optimization models may be subject to uncertainties. Examples include cost coefficients in volatile markets, and thermodynamic coefficients in new process technologies. In such cases, it is necessary for the uncertainties to be incorporated into the optimization procedure. This paper presents a target-oriented robust optimization (TORO) approach for the synthesis of polygeneration systems. The use of this methodology leads to the development of a mathematical model that maximizes robustness against uncertainty, subject to the achievement of system targets. Its properties allow us to preserve computational tractability and obtain solutions to realistic-sized problems. The methodology is demonstrated for the synthesis of polygeneration systems using TORO with an illustrative case study.

ACS Style

Charlle L. Sy; Kathleen B. Aviso; Aristotle T. Ubando; Raymond R. Tan. Target-oriented robust optimization of polygeneration systems under uncertainty. Energy 2016, 116, 1334 -1347.

AMA Style

Charlle L. Sy, Kathleen B. Aviso, Aristotle T. Ubando, Raymond R. Tan. Target-oriented robust optimization of polygeneration systems under uncertainty. Energy. 2016; 116 ():1334-1347.

Chicago/Turabian Style

Charlle L. Sy; Kathleen B. Aviso; Aristotle T. Ubando; Raymond R. Tan. 2016. "Target-oriented robust optimization of polygeneration systems under uncertainty." Energy 116, no. : 1334-1347.

Journal article
Published: 03 February 2016 in Clean Technologies and Environmental Policy
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Electronic firms are being required to collect used products for environmental purposes. In order to meet requirements, these firms carry out collection activities and provide incentive offers to attract product returns. These product returns may then undergo recovery options such as refurbishing, remanufacturing, cannibalizing, and controlled disposal. A mixed integer nonlinear programming model for a closed-loop supply chain that includes decisions for collection activities, incentive offers, and recovery options is formulated and validated. Quantity is modeled as a function of incentive offers between the collection centers and consumers, while quality of product returns follows an arbitrary probability distribution based on the incentive level. Quality of product returns dictates the possible recovery options, which these products can undergo. The model is then subjected to scenario analysis, which identified conditions wherein rebate or discount incentives are preferred, and when low or high incentive levels are favored. High stockout costs to secondary consumers encouraged the model to perform more cash rebate activities to stimulate more product returns. Meanwhile, when both the costs of activities and stockouts are high, the model is induced to carry out discount activities as this would generate sales rather than the cash rebate which simply incentivizes the participation in the take-back program.

ACS Style

Antonio Yamzon; Veanney Ventura; Paolo Guico; Charlle Sy. Optimal planning of incentive-based quality in closed-loop supply chains. Clean Technologies and Environmental Policy 2016, 18, 1415 -1431.

AMA Style

Antonio Yamzon, Veanney Ventura, Paolo Guico, Charlle Sy. Optimal planning of incentive-based quality in closed-loop supply chains. Clean Technologies and Environmental Policy. 2016; 18 (5):1415-1431.

Chicago/Turabian Style

Antonio Yamzon; Veanney Ventura; Paolo Guico; Charlle Sy. 2016. "Optimal planning of incentive-based quality in closed-loop supply chains." Clean Technologies and Environmental Policy 18, no. 5: 1415-1431.