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Spatial and sectoral benefit distribution in water-energy system design
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Rekke forfattare: 162020 (engelsk)Inngår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 269, artikkel-id 114794Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The design of water and energy systems has traditionally been done independently or considering simplified interdependencies between the two systems. This potentially misses valuable synergies between them and does not consider in detail the distribution of benefits between different sectors or regions. This paper presents a framework to couple integrated water-power network simulators with multi-objective optimisation under uncertainty to explore the implications of explicitly including spatial topology and interdependencies in the design of multi-sector integrated systems. A synthetic case study that incorporates sectoral dependencies in resource allocation, operation of multi-purpose reservoirs and spatially distributed infrastructure selection in both systems is used. The importance of explicitly modelling the distribution of benefits across different sectors and regions is explored by comparing different spatially aggregated and disaggregated multi-objective optimisation formulations. The results show the disaggregated formulation identifies a diverse set of non-dominated portfolios that enables addressing the spatial and sectoral distribution of benefits, whilst the aggregated formulations arbitrarily induce unintended biases. The proposed disaggregated approach allows for detailed spatial design of interlinked water and energy systems considering their complex regional and sectoral trade-offs. The framework is intended to assist planners in real resource systems where diverse stakeholder groups are mindful of receiving their fair share of development benefits.

sted, utgiver, år, opplag, sider
2020. Vol. 269, artikkel-id 114794
Emneord [en]
Water-energy system design, Multi-sector benefit distribution, Multi-objective robust optimisation under uncertainty, Multi-objective evolutionary algorithms
HSV kategori
Forskningsprogram
data- och systemvetenskap
Identifikatorer
URN: urn:nbn:se:su:diva-182822DOI: 10.1016/j.apenergy.2020.114794ISI: 000537619800001OAI: oai:DiVA.org:su-182822DiVA, id: diva2:1457646
Tilgjengelig fra: 2020-08-12 Laget: 2020-08-12 Sist oppdatert: 2023-12-06bibliografisk kontrollert

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Siddiqui, Afzal

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