Sustainable urban energy-environment management with multiple objectives
We present a goal programming (GP) model designed to capture multiple objectives involved in sustainable energy-environment management in an urban area. The basic structure in the GP model is a Reference Energy System (RES) that maps the optimal flow of intermediate forms of energy from supply side...
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Veröffentlicht in: | Energy (Oxford) 1996, Vol.21 (4), p.305-318 |
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creator | Bose, Ranjan K. Anandalingam, G. |
description | We present a
goal programming (GP) model designed to capture multiple objectives involved in sustainable energy-environment management in an urban area. The basic structure in the GP model is a
Reference Energy System (RES) that maps the optimal flow of intermediate forms of energy from supply side to demand nodes at the end use level in the four major economic sectors, viz.,
domestic, transport, industry, and
services and commercial. The sustainability objectives include: (a) meeting minimum useful energy demand of each end use in different sectors, (b) maximizing the capacity utilization of power stations and the stock of modal fleet, (c) minimizing expenditure on energy within the budget limits, (d) minimizing emissions of different pollutants with respect to the 1990 loading, and (e) minimizing over-utilization of energy resources. The relative weights of importance of each of the goals and sub-goals have been elicited from experts using the
Analytical Hierarchy Process (AHP) method. The integrated urban model is used to assist in developing an effective sectoral energy plan and is applied to the city of Delhi (India) to examine the effects in the year 2001 under two scenarios. In the first scenario, the possibilities for improving efficiency and abating pollution are ignored. The second scenario illustrates the effect on emissions by improving device, technology and economic efficiency, while reducing urban traffic congestion. Around 10% energy savings is possible in Delhi under scenario 2, with consequent emission reductions of lead (33%), CO (24%), HCs (21%), SPM (17%), SO
2 (12%), NO
x
, and CO
2 (10% each). |
doi_str_mv | 10.1016/0360-5442(95)00098-4 |
format | Article |
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goal programming (GP) model designed to capture multiple objectives involved in sustainable energy-environment management in an urban area. The basic structure in the GP model is a
Reference Energy System (RES) that maps the optimal flow of intermediate forms of energy from supply side to demand nodes at the end use level in the four major economic sectors, viz.,
domestic, transport, industry, and
services and commercial. The sustainability objectives include: (a) meeting minimum useful energy demand of each end use in different sectors, (b) maximizing the capacity utilization of power stations and the stock of modal fleet, (c) minimizing expenditure on energy within the budget limits, (d) minimizing emissions of different pollutants with respect to the 1990 loading, and (e) minimizing over-utilization of energy resources. The relative weights of importance of each of the goals and sub-goals have been elicited from experts using the
Analytical Hierarchy Process (AHP) method. The integrated urban model is used to assist in developing an effective sectoral energy plan and is applied to the city of Delhi (India) to examine the effects in the year 2001 under two scenarios. In the first scenario, the possibilities for improving efficiency and abating pollution are ignored. The second scenario illustrates the effect on emissions by improving device, technology and economic efficiency, while reducing urban traffic congestion. Around 10% energy savings is possible in Delhi under scenario 2, with consequent emission reductions of lead (33%), CO (24%), HCs (21%), SPM (17%), SO
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goal programming (GP) model designed to capture multiple objectives involved in sustainable energy-environment management in an urban area. The basic structure in the GP model is a
Reference Energy System (RES) that maps the optimal flow of intermediate forms of energy from supply side to demand nodes at the end use level in the four major economic sectors, viz.,
domestic, transport, industry, and
services and commercial. The sustainability objectives include: (a) meeting minimum useful energy demand of each end use in different sectors, (b) maximizing the capacity utilization of power stations and the stock of modal fleet, (c) minimizing expenditure on energy within the budget limits, (d) minimizing emissions of different pollutants with respect to the 1990 loading, and (e) minimizing over-utilization of energy resources. The relative weights of importance of each of the goals and sub-goals have been elicited from experts using the
Analytical Hierarchy Process (AHP) method. The integrated urban model is used to assist in developing an effective sectoral energy plan and is applied to the city of Delhi (India) to examine the effects in the year 2001 under two scenarios. In the first scenario, the possibilities for improving efficiency and abating pollution are ignored. The second scenario illustrates the effect on emissions by improving device, technology and economic efficiency, while reducing urban traffic congestion. Around 10% energy savings is possible in Delhi under scenario 2, with consequent emission reductions of lead (33%), CO (24%), HCs (21%), SPM (17%), SO
2 (12%), NO
x
, and CO
2 (10% each).</description><subject>Air pollution control</subject><subject>Applied sciences</subject><subject>Demand</subject><subject>Economics</subject><subject>Energy</subject><subject>Energy conservation</subject><subject>Energy economics</subject><subject>Energy efficiency</subject><subject>Energy of formation</subject><subject>Energy policy</subject><subject>Energy use</subject><subject>Environmental impact</subject><subject>Exact sciences and technology</subject><subject>Expert systems</subject><subject>General, economic and professional studies</subject><subject>Management</subject><subject>Marketing</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>Methodology. Modelling</subject><subject>Nodes</subject><subject>Optimization</subject><subject>Q1</subject><subject>Sustainability</subject><subject>Urban areas</subject><subject>Urban planning</subject><issn>0360-5442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><recordid>eNqNkEFLwzAUx3tQcE6_gYcdRPRQfWmTtLkIMtQJAw_qOaTpy8xo05m0k317223sqELghbzf-7_wi6ILArcECL-DlEPMKE2uBbsBAJHH9CgaHZ5PotMQln2D5UKMotlbF1plnSoqnHS-UG6CDv1iE6NbW9-4Gl07qZVTC9xev237Oam7qrWrfqIplqhbu8ZwFh0bVQU839dx9PH0-D6dxfPX55fpwzzWNEvaODciy2heUijRgCCl1kYDLwwHyoRGZcpSk7zkoBgSzpKCIijITWooQWHScXS1y1355qvD0MraBo1VpRw2XZAJT5OUAv0TJCzrD2T_ADlLgYkepDtQ-yYEj0auvK2V30gCcpAvB8tysCwFk1v5cvjI5T5fBa0q45XTNhxm-2gigPfY_Q7D3t7aopdBW3QaS-t7x7Js7O97fgBG9ZtO</recordid><startdate>1996</startdate><enddate>1996</enddate><creator>Bose, Ranjan K.</creator><creator>Anandalingam, G.</creator><general>Elsevier Ltd</general><general>Elsevier Science</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TV</scope><scope>C1K</scope><scope>7SU</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>1996</creationdate><title>Sustainable urban energy-environment management with multiple objectives</title><author>Bose, Ranjan K. ; Anandalingam, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c472t-8f97748d40def091dccfc06bf60459ceafddc18d60a5e1652b4e0a08f3f41e9f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Air pollution control</topic><topic>Applied sciences</topic><topic>Demand</topic><topic>Economics</topic><topic>Energy</topic><topic>Energy conservation</topic><topic>Energy economics</topic><topic>Energy efficiency</topic><topic>Energy of formation</topic><topic>Energy policy</topic><topic>Energy use</topic><topic>Environmental impact</topic><topic>Exact sciences and technology</topic><topic>Expert systems</topic><topic>General, economic and professional studies</topic><topic>Management</topic><topic>Marketing</topic><topic>Mathematical models</topic><topic>Methodology</topic><topic>Methodology. Modelling</topic><topic>Nodes</topic><topic>Optimization</topic><topic>Q1</topic><topic>Sustainability</topic><topic>Urban areas</topic><topic>Urban planning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bose, Ranjan K.</creatorcontrib><creatorcontrib>Anandalingam, G.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Pollution Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environmental Engineering Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bose, Ranjan K.</au><au>Anandalingam, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sustainable urban energy-environment management with multiple objectives</atitle><jtitle>Energy (Oxford)</jtitle><date>1996</date><risdate>1996</risdate><volume>21</volume><issue>4</issue><spage>305</spage><epage>318</epage><pages>305-318</pages><issn>0360-5442</issn><coden>ENEYDS</coden><abstract>We present a
goal programming (GP) model designed to capture multiple objectives involved in sustainable energy-environment management in an urban area. The basic structure in the GP model is a
Reference Energy System (RES) that maps the optimal flow of intermediate forms of energy from supply side to demand nodes at the end use level in the four major economic sectors, viz.,
domestic, transport, industry, and
services and commercial. The sustainability objectives include: (a) meeting minimum useful energy demand of each end use in different sectors, (b) maximizing the capacity utilization of power stations and the stock of modal fleet, (c) minimizing expenditure on energy within the budget limits, (d) minimizing emissions of different pollutants with respect to the 1990 loading, and (e) minimizing over-utilization of energy resources. The relative weights of importance of each of the goals and sub-goals have been elicited from experts using the
Analytical Hierarchy Process (AHP) method. The integrated urban model is used to assist in developing an effective sectoral energy plan and is applied to the city of Delhi (India) to examine the effects in the year 2001 under two scenarios. In the first scenario, the possibilities for improving efficiency and abating pollution are ignored. The second scenario illustrates the effect on emissions by improving device, technology and economic efficiency, while reducing urban traffic congestion. Around 10% energy savings is possible in Delhi under scenario 2, with consequent emission reductions of lead (33%), CO (24%), HCs (21%), SPM (17%), SO
2 (12%), NO
x
, and CO
2 (10% each).</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/0360-5442(95)00098-4</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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source | Elsevier ScienceDirect Journals Complete |
subjects | Air pollution control Applied sciences Demand Economics Energy Energy conservation Energy economics Energy efficiency Energy of formation Energy policy Energy use Environmental impact Exact sciences and technology Expert systems General, economic and professional studies Management Marketing Mathematical models Methodology Methodology. Modelling Nodes Optimization Q1 Sustainability Urban areas Urban planning |
title | Sustainable urban energy-environment management with multiple objectives |
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