José Ezequiel Santibañez-Aguilar

Optimal planning for the sustainable utilization of municipal solid waste

The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.

Optimal design of residential cogeneration systems under uncertainty

Abstract This paper presents a multi-objective optimization method for designing cogeneration systems in residential complexes and accounting for the involved uncertainty. The model accounts for satisfying the hot water and electric energy demands in a residential complex, while minimizing the total annual cost and the associated greenhouse gas emissions. The proposed model incorporates uncertain data for the ambient temperature, energy demands and prices of the local energy market, which are predicted through forecasting methods for determining the financial and environmental risks. Furthermore, the model accounts for determining the type and size of the central cogeneration unit, thermal storage unit, the needed auxiliary units, as well as the operating conditions. A housing complex in central Mexico is presented as case study. The results show significant economic and environmental benefits for the implementation of the proposed scheme as well as the importance of accounting for the involved uncertainty.

Optimal design of domestic water-heating solar systems

This paper presents a multi-criteria optimization formulation for the optimal design of a water-heating system for homes. The proposed model accounts for the available solar radiation in the specific place where the solar collector is installed and the hot water demands. The goal is to target economic and environmental objectives by optimizing the design and operating conditions including the optimal hot water storage and distribution. The proposed model is applied to several scenarios for homes with different inhabitants and in various cities in Mexico. The results show that the location has significant effects on the optimal design and operation of the water-heating solar system.

A mixed-integer dynamic optimization approach for the optimal planning of distributed biorefineries

Abstract The implementation of supply chains based on biomass conversion requires the exploration of various aspects, including the selection of processing technologies, configuration of the supply chain, portfolio of products as well as the feedstock selection. One important feature of this system is that the composition of the available biomass changes drastically through the year because this depends significantly on the climatic conditions; this way, the dynamic behavior of this process is an important issue that must be considered. This study presents a dynamic optimization model for the optimal planning of a distributed biorefinery system taking into account the time dependence of the involved variables and parameters. In addition, this paper incorporates a model predictive control methodology to obtain the behavior of the storages and orders of the supply chain; where the objective function is the difference between the required and satisfied demands in the markets. Therefore, this study considers relevant issues, which include the multiple available biomass feedstocks at various harvesting sites, the availability and seasonality of biomass resources, potential geographical locations for processing plants that produce multiple products using diverse production technologies, economies of scale for the production technologies, demands and prices of multiple products in each consumer, locations of storage facilities and a number of transportation modes between the supply chain components. The model was applied to a case study for a distributed biorefinery system in Mexico. Results show that is possible to get the configuration and the behavior of the supply chain considering its dynamic behavior in a rigorous way; furthermore, the solutions obtained by the model illustrate that the supply chains based on biomass conversion are seriously affected by the availability of bioresources over the time.

Optimal Multi-Objective Planning of Distributed Biorefinery Systems Involving Economic, Environmental and Social Aspects

Abstract This work presents a multi-objective optimization model based on a mathematical programming formulation for the optimal planning of distributed biomass conversion systems. The model considers the optimal selection of feedstocks, processing technologies and products while considering a time horizon. The multi-objective optimization problem simultaneously considers the profit maximization, the environmental impact minimization, as well as the maximization of the social impact benefit through the generation of jobs in rural areas. The economic objective function takes into account the availability of bioresources, processing limits and demand of products, as well as the cost of feedstocks, products and processing routes. The environmental impact is measured through the eco-indicator-99 based on the life cycle analysis methodology. The social impact is measured through the number of jobs generated. This formulation considers the variation of parameters over time. For instance, time-based profiles for raw-material availability and product demand are considered. Although the economic and environmental objectives may contradict each other with an influence on the social impact, by means of the proposed methodology is possible to obtain a set of Pareto curves that identify the set of optimal solutions for each objective. Each Pareto curve shows the compromise between the objectives and enables a better decision about the processing of biomass. The proposed methodology is applied to a case study for planning the production of a biorefinery system in Mexico, where several scenarios that compensate the economic, social and environmental objectives are identified.

Financial Risk Assessment and Optimal Planning of Biofuels Supply Chains under Uncertainty

Biofuels provide an attractive alternative for satisfying energy demands in a more sustainable way than fossil fuels. To establish a biorefinery, an optimal plan must be implemented for the entire associated supply chain, covering such aspects as selection of feedstocks, location, and capacity of biorefineries, selection of processing technologies, production amounts and transportation flows. In this context, there are several parameters, including the availability of biomass, product demand, and product prices, which are difficult to predict because they might change drastically over the different seasons of the year as well as across years. To address this challenge, this work presents a mathematical programming model for the optimal planning of a distributed system of biorefineries that considers explicitly the uncertainty associated with the supply chain operation as well as the associated risk. The potential of the proposed approach is demonstrated through its application to the production of biofuels in Mexico, considering multiple raw materials and products.

An Optimal Planning for the Reuse of Municipal Solid Waste Considering Economic, Environmental and Safety Objectives

Abstract Nowadays, the waste generation is a serious problem mainly in the countries with inefficient waste management systems. However, some waste can be reused as raw material for several products using a set of available technologies. In this context, several options to attack this problem have been implemented, but just a few alternatives consider the waste management as an integral part in the supply chain. This way, several technical, environmental and economic aspects have been taken into account for the assessment of the entire supply chain; although, the incorporation of safety criteria into the assessment of the supply chain focused in municipal solid waste have not been implemented in previous papers. Therefore, in this paper is proposed a mathematical programming model for the optimal planning of the reuse of municipal waste to maximize the economic benefits considering sustainability and safety criteria simultaneously. This methodology considers several phases: the separation of waste, distribution of waste to processing facilities, processing of waste to obtain useful products and distribution of products to consumers. Additionally, the safety criteria are based on the fatalities associated with the supply chain for the waste management. The problem is formulated as a multi-objective problem that considers three different objectives: the net annual profit, the amount of reused waste and the total fatalities generated with the considered risks. Results show that it is possible to implement a distributed processing system to reuse municipal waste in an economically attractive way. In addition, results can be used for governments to take decisions about the waste disposal and define the amount of waste that must be reused to obtain several products. It should be noted that results include the supply chain configuration. In addition, in future works this methodology can be extended to problems focused in supply chain design and retrofit simultaneously.

Chapter 19 – Supply Chains and Optimization for Biorefineries

Abstract This chapter presents an analysis of three main concepts involved in planning the supply chains for future biorefineries. First, the supply chain must include distributed systems that account for the economies of scale while simultaneously addressing the site selection for the installation of preprocessing hubs and central processing facilities. Second, the seasonal variation in the availability of the biomass resources must be considered in these supply chains. Finally, the optimal planning must take into account the multiobjective nature of the problem involving the optimization of the three aspects of a sustainable design: economic, environmental, and social issues. This chapter presents three mathematical programming models considering different key issues for the optimal planning of a biorefinery system and proposes procedures to solve these multiobjective problems. The proposed models were applied to several case studies for the optimal planning in Mexico where the importance of the key issues is highlighted.

Optimal Planning of Distributed Systems of Refineries and Biorefineries Considering Pollution Trading with Forest Plantations

The production of fossil fuels to satisfy the energy demand has caused a drastic increment in the greenhouse gas emissions, which are associated directly with the global warming problem. Installing biorefineries is an interesting alternative to address this problem because biomass can capture CO2 emissions during its growth. On the other hand, a new interesting approach to promote economic growth in low-income regions is through new eco-industries dedicated to cultivate trees and taking care of the forest. These forest plantations help to capture CO2 emissions produced by petroleum refineries and biorefineries. Therefore, a system able to integrate production of fuels through refineries and biorefineries with the use of forest plantations to decrease the greenhouse gas emissions can be an attractive solution to significantly improve the environmental sustainability. However, the implementation of this project has to consider several factors, including the life time of the project, the availability of resources, the amount and type of products that should be produced, the allocation and capacity of the involved refineries, biorefineries and forest plantations, among others. For this reason, this paper presents an optimization model for the optimal planning of an integrated system for the production of fossil fuels and biofuels considering the interaction with eco-industries, which are able to capture emissions from biorefineries and refineries and receive an economic benefit. The proposed mathematical model takes into account the availability of biomass, the production of oil, a set of existing biorefineries and refineries as well as the possibility to install new facilities. The mathematical approach was applied to a nationwide case study from Mexico, considering the creation of new jobs, overall emissions and net profit as objectives. The results are shown through a Pareto curve, which is useful to make decisions about the planning of the interactions between these types of industries as well as determining the supply chain configuration in order to satisfy overall demand of products.

Multi-objective optimization of absorption refrigeration systems involving renewable energy

Abstract This work presents a new methodology for the synthesis of absorption refrigeration systems integrated with different types of fossil energies (i.e., coal, oil, natural gas, etc) and renewable energies (i.e., waste-heat recovery, biomass, solar energy) to operate the stripper required by these heat-powered systems to release the vapor at the higher pressure. Since in a given location, the available biomass and solar energy depend on the season of the year, this work proposes an appropriate multi-period approach to satisfy the energy requirements by the process year-round. To properly solve the addressed problem, this work presents a two stage methodology considering social and environment aspects besides the economic performance. The first stage identifies the energy targets while the second stage uses a new multi-objective mathematical programming model to determine the minimum cost, minimum greenhouse gas emissions and the maximum social benefit that satisfies the energy target identified in the first stage. It is noteworthy that the main novelty of this work is the incorporation of social criteria, and particularly the consideration of the potential jobs generated to satisfy the energy target identified in the first stage. The proposed model considers the optimal selection of different types of solar collectors. The application of this methodology to a case study in Mexico shows that it is possible to reduce the greenhouse gas emissions at attractive costs obtaining additional social benefits through the generation of jobs in rural areas when a combination of different biofuels, fossil fuels and a solar collector is used to run the absorption refrigeration system.