Medardo Serna-González

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.

Optimization model for re-circulating cooling water systems

Abstract This paper presents an optimization model for the simultaneous synthesis and detailed design of re-circulating cooling water systems. A cooler network superstructure that embeds all network configurations of practical interest is used as part of the integrated model. Pressure drops in each cooler are treated as optimization variables, and design guidelines and constraints are included in order to provide practical and feasible units. The model is based on a generalized disjunctive programming formulation, which gives rise to a mixed-integer nonlinear programming problem. The objective is to find cooling water systems that minimize the total annual cost. Solution of this mathematical formulation provides the optimal system configuration as well as the optimal operating conditions and design parameters required for each cooler unit in the network and in the cooling tower. Three example problems are presented to show the application of the proposed approach.

A global optimal formulation for the water integration in eco-industrial parks considering multiple pollutants

Abstract A mathematical programming formulation for the water integration in eco-industrial parks considering streams with several pollutants is presented. The formulation is based on a superstructure that allows the wastewater reuse in the same plant, the water exchange with different plants, and a shared set of interceptors that must be selected to determine the network configuration that satisfies process equipments and environmental constraints. The model formulation considers wastewater with several pollutants, and optimizes the network according to the minimum total annual cost, which includes the costs of fresh water, piping and regeneration. A new discretization approach is also proposed to handle the large set of bilinear terms that appear in the model in order to yield a near global optimal solution. The results obtained in several examples show considerable savings with respect to the solutions of the individual plant integration policy commonly employed for these types of problems.

Optimal reconfiguration of multi-plant water networks into an eco-industrial park

Abstract This paper presents an MINLP model to design an eco-industrial plant by retrofitting existing water networks from different industrial plants in the same industrial zone. The proposed model is based on a superstructure and takes into account both in-plant and inter-plant structural modifications, such as the placement/reassignment of existing treatment units, the required increase of capacity and/or efficiency of existing treatment units, the placement of new treatment units either within the participating plants or in a new shared wastewater treatment facility, and the stream re-piping associated with installing new treatment units and retrofitting existing treatment units. The model allows the tracking of changes in the process performance as a result of the stream re-routing and retrofitting activities. Two examples were solved, and the results show the economic and environmental benefits of the retrofitted networks within an eco-industrial park compared to the stand-alone retrofitted networks.

Industrial waste heat recovery and cogeneration involving organic Rankine cycles

This paper proposes a systematic approach for energy integration involving waste heat recovery through an organic Rankine cycle (ORC). The proposed approach is based on a two-stage procedure. In the first stage, heating and cooling targets are determined through heat integration. This enables the identification of the excess process heat available for use in the ORC. The optimization of the operating conditions and design of the cogeneration system are carried out in the second stage using genetic algorithms. A modular sequential simulation approach is proposed including several correlations to determine the properties for the streams in the ORC. The proposed approach is applied to a case study which addresses the tradeoffs among the different forms of energy and associated costs. The results show that the optimal selection of the operating conditions and working fluid is very important to reduce the costs associated to the process.

Synthesis of water networks considering the sustainability of the surrounding watershed

Abstract This paper presents a new mathematical programming model for the optimal synthesis of recycle and reuse networks considering simultaneously the integration of the water network system and the surrounding watershed to satisfy process and environmental constraints. The model considers the optimal location of the new industrial facility to integrate its wastewater discharge to the environment with the surrounding watershed through a disjunctive formulation. The pollutants discharged for the new plant are tracked simultaneously with the other discharges to the watershed (i.e., residential, sanitary, industrial and extractions), and the natural phenomena that affect the composition of the watershed (i.e., evaporation, filtration, etc.), in addition to the chemical reactions that are carried out in the rivers. The objective function consists in minimizing the total annual cost that is constituted by the installation of the new plant cost (including the transportation for raw materials, products and services, as well as the land cost), the wastewater treatment costs (including the piping cost) and the fresh sources cost. Two example problems were used to show the applicability of the proposed methodology.

Multi-objective optimization of steam power plants for sustainable generation of electricity

A unified framework that combines process simulation and multi-objective optimization is presented to simultaneously maximize the annual profit, while minimizing environmental impact (i.e., greenhouse gas emissions) of steam power plants with fixed flowsheet structures. The proposed methodology includes the selection of suitable primary energy sources (i.e., fossil fuels, biomass, biofuels, and solar energy) for sustainable electricity generation. For solving the problem of optimal selection of energy sources, a linear model is developed and included within a highly nonlinear simulation model for the parameter optimization of steam power plants that is solved by using genetic algorithms. This approach is robust and avoids making discrete decisions. Life cycle assessment technique is used to quantify the greenhouse gas emissions resulting from different combinations of energy sources and operating conditions of the power plants. The thermodynamic properties for liquid water and steam are calculated rigorously using the IAPWS-IF 97 formulation. An example problem of an advanced regenerative-reheat steam power plant is presented to illustrate the proposed method, which provides the Pareto optimal solutions, the types and amounts of primary energy sources as well as the optimal values of the operating conditions of the plant that simultaneously maximize the profit while minimizing environmental impact.

Optimal design of distributed treatment systems for the effluents discharged to the rivers

This paper presents a methodology for the optimal synthesis of distributed treatment systems of effluents discharged into a main river to meet water discharge quality constraints. The methodology is based on a new superstructure that is formulated and solved as a multi-objective mixed-integer nonlinear programming model. A material flow analysis technique is used to track the pollutants through the watershed considering the combined effects of the inputs, outputs (i.e., agricultural, residential, industrial, and so on) and the chemical transformations. A disjunctive programming model is implemented for selecting the optimal location of the distributed treatment system. Prior to the optimization and based on the pollutants considered, a discretization approach is implemented to determine from simulation the removal efficiency and the unit cost of given configurations and operating conditions of the selected treatment units. Therefore, the optimization process determines the removal efficiency used to treat the effluents and the flow rate treated. Simultaneous minimization of the total annual cost of the distributed treatment system and the contaminant concentration of the discharge to the catchment of the watershed are considered as two objective functions. Three case studies (one in Mexico and two in Egypt) have been selected to illustrate the methodology. Results show that significant savings can be obtained when the distributed treatment system is implemented. Finally, the proposed methodology can be used for supporting governmental decisions (i.e., it provides the investment required for a specific water quality).

Synthesis of multipass heat exchanger networks using genetic algorithms

Abstract In this work, a methodology based on genetic algorithms (GAs) is developed for the optimal synthesis of multipass heat exchanger networks (HENs). The network model is based on a stagewise superstructure, and the problem of finding the optimum number of 1–2 shells in series of multipass heat exchangers is aided by an efficient optimization model that uses the standard F T design method. The proposed methodology allows for proper handling of the trade-offs involving energy consumption, number of units, number of 1–2 shells and network area to provide a network with the minimum total annual cost. The results of the examples show that the new approach is able to find more economical networks than those generated by other methods.

Simultaneous design of water reusing and rainwater harvesting systems in a residential complex

Abstract This paper introduces an optimization formulation to design residential water systems that satisfy the water demands in a housing complex involving rainwater harvesting, storage and distribution as well as the simultaneous design of water networks for recycling, reusing, regenerating and storing reclaimed water. The design task is considered as a multi-objective optimization problem where one objective is the minimization of the fresh water consumption and the other objective is the minimization of the total annual cost. The proposed model accounts for the variability in the water demands through the different hours of the day and for the different seasons of the year. The seasonal dependence of the rainwater has also been considered in the optimization model. A case study for the city of Morelia in Mexico is presented. The results show that significant reductions can be obtained in the total fresh water consumption and in the total cost.