生态工业园区的设计外文文献

Design of sustainable and resilient eco industrial parks Planning the fl ows integration network through multi objective optimization Guillermo Valenzuela Venegas Gabriela Vera Hofmann Felipe A D az Alvarado Department of Chemical Engineering Biotechnology and Materials Faculty of Physical and Mathematical Sciences Universidad de Chile Av Beauchef 851 Piso 6 poniente Center for Sustainable Design and Process Systems Engineering 8370456 Santiago Chile a r t i c l e i n f o Article history Received 18 December 2018 Received in revised form 11 August 2019 Accepted 26 September 2019 Available online 30 September 2019 Handling editor Lei Shi Keywords Eco industrial parks Resilience Multi objective optimization Industrial networks Sustainability a b s t r a c t An Eco Industrial Park is a community of businesses located together exchanging material and energy with each other to achieve sustainability advantages for its participants The main benefi ts of this kind of parks are related to the three dimensions of sustainability economic environmental and social An important problem when designing and redesigning an Eco Industrial Park is the infrastructure planning to connect plants In this context the connectivity of this network plays a signifi cant role because of material and energy sharing and the new dependence and the problem thereof failures are also propagated within the network In this sense the goal of this work is to formulate and solve an optimization problem to design the material network of an EIP considering environmental economic and resilience aspects in this effort Specifi cally this problem is constructed based on two well known EIPs Kalundborg in Denmark and Ulsan in South Korea The novelty of the present model is to simultaneously consider both aspects confi guring an EIP which not only optimizes its usual economic benefi ts but also defi nes its topology to improve resilience Therefore the resulting confi guration would achieve economic and environmental benefi ts ensuring the operation of the park if any participant suffers a disruptive event In order to analyze and to compare the use of this optimization model when designing EIPs fi ve confi gurations are obtained for each case study three single objective solutions optimizing the eco nomic environmental and resilience aspects separately and two multi objective solutions considering the economic and environmental aspects and the economic environmental and resilience aspects simultaneously The resulting individual confi gurations present the best value for each assessed characteristic among all the cases considered even when comparing them with the reported situation of the park These solutions represent an orientation to project changes on the existing Eco Industrial Parks in Kalundborg and Ulsan Finally even though the proposed model presents several simplifi cations it allows to design more resilient and more sustainable EIPs In this sense this model can support decision makers in the in dustrial design generating new alternatives to implement eco industrial parks 2019 Elsevier Ltd All rights reserved 1 Introduction An Eco Industrial Park EIP is as a set of companies located together in a common property with the goal of sharing resources effi ciently and to improve the sustainability of the sector Boix et al 2015 Within its main benefi ts are fi rm profi tability envi ronmental impact reduction of the sector and concern for local community next to the park In other words benefi ts related to the sustainability dimensions economic environmental and social Valenzuela Venegas et al 2016 Since the magnitude of these benefi ts depends on the EIP confi guration concerning connections among participating fi rms and theirlocation in the park PCSD 1997 it is important to make a proper planning and design to obtain the maximum possible benefi ts Corresponding author E mailaddresses gvalenzu ing uchile cl G Valenzuela Venegas gverahofmann G Vera Hofmann felidiaz ing uchile cl F A D az Alvarado Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage https doi org 10 1016 j jclepro 2019 118610 0959 6526 2019 Elsevier Ltd All rights reserved Journal of Cleaner Production 243 2020 118610 Nomenclature General Model h Effi ciency of the pump gDeviation of each objective function in the goal programming method m Dynamic viscosity of the fl uid fFlow Adaptability Index Sub indicator measuring the operational characteristic of a network r Density of the fl uid relative effective roughness height of the pipe CNumber of connections in the park Di jDiameter of the connection pipe between participant i and j FOiObjective function for aspect i FOWorstCase i Worst expected value for the aspect i FOEcEconomic objective function FOEnEnvironmental objective function FOReResilience objective function gGravitational acceleration gapRelative changes for each assessed aspect in regard to its optimal and worst obtained value m Lowest fl ow accepted as distinct to 0 NCINetwork Connectivity Index Sub indicator measuring the topological characteristic of a network PpumpPressure drop kWh Preal pump Real pressure drop for a pump kWh Qin j Demand of material by participant j Qmax in j Maximum input capacity of participant j Qmax in j 1 25Qin j Qmax out i Maximum output capacity of participant i Qmax out i 1 25Qout i Qmin in j Minimum input capacity of participant j Qmin in j 0 25Qin j Qmin out i Minimum output capacity of participant i Qmin out i 0 25Qout i Qout i Supply of material by participant i ReReynolds number RIEIPResilience indicator composed by two sub indicators Network Connectivity Index and Flow Adaptability Index v Velocity of the fl uid wEcEconomic objective function weight wEnEnvironmental objective function weight wReResilience objective function weight xi jExistence of connection between participant i and participant j Kalundborg case study a1and a2 Construction and installation cost coeffi cients per unit of pipe length a1in V m2and a2in V m EcostPrice of the electricity in Kalundborg V kWh Fi h Shared fl ow between participant i2I and participant h2H Fi j Shared fl ow between participant i2I and participant j2J Fi t Shared fl ow between participant i2I and participant t2T Fk j Shared fl ow between participant k2K and participant j2J Ft h Shared fl ow betweenparticipant t2T and participant h2H FOBestCase i Expected value for the aspect i HSet of sinks J fH1g ISet of industrial plants I fI1 I2 I3g KSet sources I fK1 K2g Li hLength of the pipe between participant i2I and h2H Li jLength of the pipe between participant i2I and j2I Li tLength of the pipe between participant i2I and t2T Lk jLength of the pipe between participant k2K and j2I Lt hLength of the pipe between participant t2T and h2H TSet of treatment plants I fT1g xk jExistence of connection between participant k2K and participant j2J xi jExistence of connection between participant i2I and participant j2J xi tExistence of connection between participant i2I and participant t2T xi hExistence of connection between participant i2I and participant h2H xt hExistence of connection between participant t2T and participant h2H Ulsan case study L k Total lack of fl ows related to a disruption in participant k fkFlow sensitivity of the participant k a1and a2 Construction and installation cost coeffi cients per unit of pipe length a1in USD m2and a2in USD m EcostPrice of the electricity in Ulsan USD kWh Flayerr i j Shared fl ow between participant i2Ilayerrand participant j2Jlayerr IlayerrSet of participants in layer r supplying output material ISteam f1 3 7 10 13 16 22g ICO2 f3g IOil f18 20g JlayerrSet of participants in layer r demanding input material JSteam f2 8 14 17 23 28g JCO2 f2g JOil f19 25g LSet of layers or exchanged material considered in the problem L fSteam CO2 Oilg Li jLength of the pipe between participant i and j PriceOil Selling price of an oil fl owoutside the park estimated by the exports price of Ulsan USD t Sinklayerr i Flow to a sink from participant i2Ilayerrin layer r2L Sinklayerr Cost Cost of treating the gases outside the park Sourcelayerr j Flow from a source to participant j2Jlayerrin layer r2L Sourcelayerr Cost Cost of obtaining raw material from outside the park USD t G Valenzuela Venegas et al Journal of Cleaner Production 243 2020 1186102 Particularly to establish a possible connection between two fi rms and to defi ne an EIP confi guration the main barriers are to meet their operation requirements e g fl ow magnitude compo sition temperature etc and to establish a feasible and suitable location Moreover if these elements are defi ned for a set of fi rms their confi guration should improve the economic environmental and social aspects of each participant and the whole park All these considerations make an EIP a more complex system than the stand alone operation of each fi rm For this reason a system integration approach has become necessary to facilitate the confi guration of an EIP and to help the decision makers to plan and design complex systems Lovelady and El Halwagi 2009 A systematic manner to design this kind of industrial complexes is through the formulation and solution of an optimization prob lem specifi cally a multi objective optimization problem Biegler and Grossmann 2004 This approach is widely used in the industry and depending on the characteristic of the problem decision variables and nature of the equation it could be classifi ed in Linear Programming LP Mixed Integer Linear Programming MILP Nonlinear Program ming NLP and Mixed Integer Nonlinear Programming MINLP In general the EIP design aims at improving sustainability di mensions objective function deciding over the location of the participants in the park their connections and concentration of a contaminant decision variables All these decisions are subject to constraints namely operation requirements process limitations and context considerations Grossmann 1985 There are several works in the literature where the authors formulate an optimization problem to design an EIP e g Cimren et al 2011 Chae et al 2010 Liew et al 2013 Lovelady and El Halwagi 2009 Rubio Castro et al 2011 Tietze St ockinger et al 2004 All these works has been classifi ed in water mate rial and energy networks design according tothe type of exchanges among participants of the park Tudor et al 2007 In Boix et al 2015 the authors present a large reviewabout the use of this optimization approach to design EIPs highlighting the objective functions that have been considered in each problem Boix et al 2015 Based on this the main optimized objectives are related to sustainability dimensions specifi cally to the economic and environmental ones while the social dimension is typically considered as part of the other two This behavior is mainly due to the lack of social indicators and to the requirement of complex information about each participant fi rms process etc by these indicators Valenzuela Venegas et al 2016 On the other hand it is also important to consider other aspects related to safety issues when processes are connected in an EIP especially when its proper operation and attainment of the sus tainable benefi ts depends on these connections Since some of its participants could suffer disruptive events during its normal operation the optimal EIP confi guration should also ensure the continuous operation of each participant and the whole park Valenzuela Venegas et al 2018 In this sense the concept of resilience has been defi ned for different process integration problem not only for the EIP design For example in Zhu and Ruth 2013 the authors defi ne this concept for industrial ecosystems They defi ne the resilience as the ability to maintain their main feature related to eco effi ciency material and energy fl ows under possible disruptions Zhu and Ruth 2013 Through this defi nition they analyze certain charac teristics of an ecosystem that may cause damage in its resilience The authors propose guidelines for design and management that policy makers planners and managers should take into account to improve the resilience on any system On the other hand in Aguilar et al 2008 the authors consider the concept of reliability in designing and optimizing a utility system They propose an integrated methodology that considers maintenance and failure situation during the design phase of these systems achieving this task by considering the redundancy in the objective function Other authors use the network theory to study the resilience of industrial systems specifi cally of EIPs Chopra and Khanna 2014 Li and Xiao 2017 Xiao et al 2016 Zeng et al 2013 In Li and Xiao 2017 the authors adopt this approach to analyze the topological characteristics of Ningdong CCEIP in China Li and Xiao 2017 They propose a methodology to study the resilience through the sequential removal of the most important nodes of the EIP and analyzing changes on the network effi ciency Furthermore the authors mention that even though the proposed approach obtains consistent results it is only based on the topological characteristics of the industrial network In this sense they highlight the necessity of including the material fl ows in the analysis to represent the re lationships among the nodes and be closed to reality Following this idea in Valenzuela Venegas et al 2018 a resilience indicator has been proposed to measure resilience of an EIP considering both characteristics This indicator is based on two sub indicators NetworkConnectivityIndex NCI andFlow Adaptability Index f The former is related to the number of connections among participants of the park the latter to the ca pacity of the participants to absorb a disruptive event on the park Both sub indicators together determine if an industrial network can maintain its identity as EIP when a disruptive event affects the park and quantify the operation performance when a fi rm stops sharing material There are some previous works related to the design of an EIP through an optimization problem where resilience is also included in its formulation beside sustainability aspects For example in Afshari et al 2017 and Aviso et al 2010 the authors take into account resilience by considering uncertainty in the optimization They consider demand and cost respectively as a fuzzy goal in their works It is believed that their models could improve EIP s resil ience under uncertainties In Dave and Layton 2019 the authors redesign the water network of the Kalundborg EIP in Denmark considering a bio inspired design optimization based on Ecological Network Anal ysis techniques Dave and Layton 2019 They compare this new approach and the conventional one to confi gure EIPs concluding that even though both obtain minimization in freshwater con sumption the fi rst one also confi gures networks more robust In this sense they highlight the necessity to consider not only sus tainability aspects when a complex system is designed but also its resilience in order to face of disturbance in its operation and to support the success of EIPs use Even though resilience is assessed considering and improving other aspects in these works none of them directly address resil ience in the design of EIPs or other systems In Leong et al 2017 the authors consider resilience as an objective of the optimization problem Leong et al 2017 They formulate a multi objective optimizationproblem where resilience is represented by two indicators connectivity and reliability where the latter considers the susceptibility degree and fl ow tolerance of each participating plant However the focus of this work is the application of a decision making tool AHP Analytic Hierarchy Process in order to consider each participants prefer ence improving its economic environmental connectivity and reliability benefi ts Accordingly to our knowledge there is no previous work focused on including resilience in the design of an EIP considering the indicator developed by Valenzuela Venegas et al 2018 Therefore the main goal of this paper is to systematically design an EIP by means of a mathematical formulation of a multi objective optimization problem considering sustainability dimensions and G Valenzuela Venegas et al Journal of Cleaner Production 243 2020 1186103 resilience of the park as objective functions And to analyze the consequences of the inclusion of the resilience aspect in the design of EIPs To illustrate the use of this formulation and to analyze resilience inclusion two case study are used the EIP in Ulsan South Korea Beheraet al 2012 andthe EIP in Kalundborg Denmark Jacobsen 2006 First a mono objective formulation is defi ned fi rst to confi gure a park considering economic environmental and resil ience aspects separately Then two multi objective problems are formulated to address an economic and environmental confi gu ration and to address an economic environmental and resilient confi guration The presentpaper is organized as follows Section 2 presents the general model defi nition Section 3 shows each case study and its resulting EIP confi gurations as well as the respective discussions about these confi gurations and fi nally in Section 4 the main conclusions are presented 2 Problem defi nition 2 1 Model assumptions In order to formulate the optimization problem the following assumptions are considered The possible connections among the participants are considered as material fl ows between two participants and are represented by oriented edges connecting the respective participants Since there is a lack of information in the literature about the internal processes of the participating fi rms and plants in each case study only their inputs and output requirements are taken into account No contaminant or other concentrations are considered in the EIP design In this sense a connection is possible if the partici pating fi rms or plants are only sharing the same material Since in an EIP the participating fi r