Involving resilience in optimizing the water-energy-food nexus at macroscopic level

https://doi.org/10.1016/j.psep.2020.09.037Get rights and content

Abstract

This paper presents a multi-objective optimization model for the optimal design of a resilient macroscopic system that incorporates the water-energy-food nexus targeting economic and environmental objectives. The model aims to properly satisfy and distribute water and energy for agricultural, domestic, industrial, and livestock sectors, also it takes into account the treatment of wastewater from agriculture, domestic and industrial sectors, as well as the use of agricultural wastes to be used as fuel in power and desalinization plants. The model was coded and solved in the software GAMS. A case study from the northwest part of Mexico was considered to show the applicability of the proposed approach. Results show that it is possible to obtain resilient solutions in satisfying water, energy and food needs with an appropriated distribution of resources, even when the climatic conditions are extreme.

Introduction

Nowadays, the proper use of water is a very important need in all sectors of modern society, especially in agriculture (Núñez-López et al., 2018a), livestock (Martínez-Guido et al., 2018), industry (Baklouti et al., 2018; El-Halwagi, 2006), and domestic sectors (Omwene and Kobya, 2018; Núñez-López et al., 2018b). Usually, 70 percent of the available water in a certain region is destined for agricultural use; however, 90 percent of the main agriculture districts uses up to 90 percent of the availability of this resource. Therefore, it is needed to improve the use of water in agriculture. Cervantes-Gaxiola et al. (2020) proposed a multi-period mixed integer nonlinear programming model for determining the optimal crop allocation for several planting cycles based on future crop prices and freshwater availability. In the same way, the proper use of water in the energy sector is especially important since these resources are closely related. Energy is used for treatment, consumption, and distribution of water, while water is used for energy generation (Larsen and Drews, 2019; Sharif et al., 2019). There are some approaches about the optimization of power plants, Hernández-Luna et al. (2019) presented an energy model to optimize the grid of power plants in the electricity sector, Rezaie et al. (2019) designed a heat recovery steam generation in a combined-cycle power plant using genetic algorithms. Also, the generation of electricity by a desalinization power plant has been studied for an industrial plant (Mansouri et al., 2019), and for the analysis of irrigation fields (Ricart et al., 2020).

Recently, the term of food has been introduced to the water-energy nexus to create the concept water-energy-food nexus, because food production requires water, and energy for transporting water and food, while generated wastes in food production can be used as fuel in energy generation. Biggs et al. (2015) proposed a critical review of nexus approaches and identified potential linkages with sustainable livelihoods, to deepen our understanding of the interrelated dynamics between human populations and the environment. Cansino-Loeza and Ponce-Ortega (2018) presented a general mathematical programming model for satisfying water, energy, and food needs in isolated and low-income communities involving different process integration approaches. Tan et al. (2020) presented an optimization-based systematic framework to design an integrated palm oil-based complex with food-energy-water nexus integrations.

On the other hand, the design and operation of integrated systems can face different disturbances (Luthra and Mangla, 2018; Wang et al., 2015), whether due to personnel operation errors, random failures, or caused by some natural disasters. Thus, in this work the concept of resilience has been incorporated in the design of integrated water-energy-food systems. The origin of resilience comes from the word “resilio”, which is defined as the ability of an object to return to its original state (Ravadanegh et al., 2019). In this sense, Ayyub (2014) proposed a resilience definition that meets a set of requirements with clear relationships to the metrics of the relevant abstract notions of reliability and risk. Resilience has represented an important challenge in process engineering; however, in recent years, the need to improve the recovery of systems, especially energy systems (Hao et al., 2018), has motivated the development of research in this area. For example, Ng and Sy (2014) considered a dynamic workforce-inventory control problem, wherein inventory planning, production releases, and workforce hiring decisions need to be made, they proposed a resilience optimization model for the problem. Gong and You (2018) proposed a general framework to incorporate an improved quantitative measure of resilience and a comprehensive set of resilience enhancement strategies for process design and operations.

Specifically, the resilience of a system can be characterized by its performance when stressed by internal or external interruptions. The term resilience refers to the inability of the system to deliver its functional service(s) during and after the interruption (Moslehi and Reddy, 2018). Ouyang (2017) defined the hazards that can cause direct localized damage or interruption as Spatially Localized Attacks (SLA). The paper implemented a worst-case analysis and proposed a mathematical framework to support resilience optimization of interdependent critical infrastructure system under the worst SLA. Liao et al. (2018) aimed to measure and optimize transportation under disasters, they proposed an optimization model for resilience under constraints of budget and traversal time. Therefore, in this paper is presented a resilience analysis for a macroscopic system that involves the water-energy-food nexus, which considers the proper use and distribution of resources. Considering resilience in this type of system brings us the benefit of identifying possible failures that may occur during a process and thus addressing it to avoid functional losses in exchange for an economic cost.

Section snippets

Problem statement

Given the required needs of the water-energy-food nexus by the analyzed sector, the addressed problem (Fig. 1) consists in determining a resilient system for the optimal use and distribution for water, energy and food in a macroscopic level, where the agricultural, domestic, energy, industrial, and livestock sectors are considered. Power plants are used to satisfy energy demands in the sectors. Similarly, the potential installation of desalinization plants is proposed to fulfill energy and to

Proposed model formulation and solution Approach

For solving the addressed problem, a mathematical model formulation for the sustainable analysis of the water-energy-food nexus for a waste heat recovery scheme based on the superstructure shown in Fig. 2 is proposed. The mathematical model is a multi-objective formulation, where the objectives are the minimization of the total annual cost and the minimization of the emissions generated by the system. The used indexes in the model are defined as follows: q represents the aquifers as a natural

Case study

To demonstrate the applicability of the mathematical model, a case study from the northwest part of Mexico is proposed (Fig. 4). Specifically, the Hydrological Region 10 was considered, which covers approximately 85 % of the state of Sinaloa. In this region, 4 power plants are available for power generation, one located in the City of Mazatlán and the other three in the Topolobampo port. In addition, 8 aquifers, 11 dams, and 27 deep wells are used to satisfy the water demands of the

Results

The mathematical model for the water-energy-food nexus was coded and solved in the software GAMS (Brooke et al., 2020) using data from a case study of the most important agriculture area in Mexico, the model is a mixed-integer linear programming, which includes 24,413 equations, 29,815 continuous variables, and 1,331 binary variables.

The Pareto Curve (Fig. 5) was constructed using the Epsilon Constraint method (Laumanns et al., 2006), where, in first instance, the total annual cost was

Conclusions

A mathematical model was formulated to optimize the water-energy-food nexus at macroscopic level. A methodology to quantify the resilience of the processes was analyzed and implemented to improve the performance of the system and to satisfy the required needs.

A case study from the Norwest part of Mexico was presented. The results show that in case of the minimum annual cost (Scenario A) only the four existing power plants are used, in case that one or two units fail, the system could still

Declaration of Competing Interest

The authors report no declarations of interest.

Acknowlegment

We are grateful to Mexico’s National Council for Science and Technology (Conacyt-FORDECYT/12SE/2018/11/29-05) for financial support.

References (32)

  • G. Aguilar-Oropeza et al.

    Involving acceptability in the optimal synthesis of water networks in eco-industrial parks

    Ind. Eng. Chem. Res.

    (2019)
  • B.M. Ayyub

    Systems resilience for multihazard environments: definition, metrics, and valuation for decision making

    Risk Anal.

    (2014)
  • A. Brooke et al.

    GAMS, A User’s Guide

    (2020)
  • B. Cansino-Loeza et al.

    Involving the water–energy–food nexus in integrating low-income and isolated communities

    ACS Sustain. Chem. Eng.

    (2018)
  • M.E. Cervantes-Gaxiola et al.

    Optimal crop allocation including market trends and water availability

    Eur. J. Oper. Res.

    (2020)
  • M.M. El-Halwagi

    Process Integration

    (2006)
  • Cited by (24)

    View all citing articles on Scopus
    View full text