Optimal heterogeneity in a simplified highly renewable European electricity system
The resource quality and the temporal generation pattern of variable renewable energy sources vary significantly across Europe. In this paper spatial distributions of renewable assets are explored which exploit this heterogeneity to lower the total system costs for a high level of renewable electric...
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Veröffentlicht in: | Energy (Oxford) 2017-08, Vol.133, p.913-928 |
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description | The resource quality and the temporal generation pattern of variable renewable energy sources vary significantly across Europe. In this paper spatial distributions of renewable assets are explored which exploit this heterogeneity to lower the total system costs for a high level of renewable electricity in Europe. Several intuitive heuristic algorithms, optimal portfolio theory and a local search algorithm are used to find optimal distributions of renewable generation capacities that minimise the total costs of backup, transmission and renewable capacity simultaneously. Using current cost projections, an optimal heterogeneous distribution favours onshore wind, particularly in countries bordering the North Sea, which results in average electricity costs that are up to 11% lower than for a homogeneous reference distribution of renewables proportional to each country's mean load. The reduction becomes even larger, namely 18%, once the transmission capacities are put to zero in the homogeneous reference distribution. Heuristic algorithms to distribute renewable capacity based on each country's wind and solar capacity factors are shown to provide a satisfactory approximation to fully optimised renewable distributions, while maintaining the benefits of transparency and comprehensibility. The sensitivities of the results to changing costs of solar generation and gas supply as well as to the possible cross-sectoral usage of unavoidable curtailment energy are also examined.
•Derivation of optimal spatial distributions of wind and solar generation capacities.•Application of several intuitive heuristic algorithms and optimal portfolio theory.•Application of a local search algorithm to minimise the total infrastructure costs.•Application to a simplified highly renewable European networked electricity system.•Optimal heterogeneous distributions reduce average electricity costs by 11–18%. |
doi_str_mv | 10.1016/j.energy.2017.05.170 |
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•Derivation of optimal spatial distributions of wind and solar generation capacities.•Application of several intuitive heuristic algorithms and optimal portfolio theory.•Application of a local search algorithm to minimise the total infrastructure costs.•Application to a simplified highly renewable European networked electricity system.•Optimal heterogeneous distributions reduce average electricity costs by 11–18%.</description><identifier>ISSN: 0360-5442</identifier><identifier>EISSN: 1873-6785</identifier><identifier>DOI: 10.1016/j.energy.2017.05.170</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Algorithms ; Alternative energy ; Alternative energy sources ; Costs ; Electricity ; Electricity pricing ; Energy costs ; Energy sources ; Europe ; Heterogeneity ; Large-scale integration of renewables ; Levelised system cost of electricity ; Load distribution ; Renewable energy networks ; Renewable energy sources ; Search algorithms ; Solar energy ; Solar power generation ; Spatial distribution ; Stress concentration ; System design ; Transparency ; Wind ; Wind power generation</subject><ispartof>Energy (Oxford), 2017-08, Vol.133, p.913-928</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier BV Aug 15, 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-c13d2cab4b69d5f5cead7d9f90b626099b4643e2531a3b543796dffae0ded3a83</citedby><cites>FETCH-LOGICAL-c438t-c13d2cab4b69d5f5cead7d9f90b626099b4643e2531a3b543796dffae0ded3a83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0360544217309593$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Eriksen, Emil H.</creatorcontrib><creatorcontrib>Schwenk-Nebbe, Leon J.</creatorcontrib><creatorcontrib>Tranberg, Bo</creatorcontrib><creatorcontrib>Brown, Tom</creatorcontrib><creatorcontrib>Greiner, Martin</creatorcontrib><title>Optimal heterogeneity in a simplified highly renewable European electricity system</title><title>Energy (Oxford)</title><description>The resource quality and the temporal generation pattern of variable renewable energy sources vary significantly across Europe. In this paper spatial distributions of renewable assets are explored which exploit this heterogeneity to lower the total system costs for a high level of renewable electricity in Europe. Several intuitive heuristic algorithms, optimal portfolio theory and a local search algorithm are used to find optimal distributions of renewable generation capacities that minimise the total costs of backup, transmission and renewable capacity simultaneously. Using current cost projections, an optimal heterogeneous distribution favours onshore wind, particularly in countries bordering the North Sea, which results in average electricity costs that are up to 11% lower than for a homogeneous reference distribution of renewables proportional to each country's mean load. The reduction becomes even larger, namely 18%, once the transmission capacities are put to zero in the homogeneous reference distribution. Heuristic algorithms to distribute renewable capacity based on each country's wind and solar capacity factors are shown to provide a satisfactory approximation to fully optimised renewable distributions, while maintaining the benefits of transparency and comprehensibility. The sensitivities of the results to changing costs of solar generation and gas supply as well as to the possible cross-sectoral usage of unavoidable curtailment energy are also examined.
•Derivation of optimal spatial distributions of wind and solar generation capacities.•Application of several intuitive heuristic algorithms and optimal portfolio theory.•Application of a local search algorithm to minimise the total infrastructure costs.•Application to a simplified highly renewable European networked electricity system.•Optimal heterogeneous distributions reduce average electricity costs by 11–18%.</description><subject>Algorithms</subject><subject>Alternative energy</subject><subject>Alternative energy sources</subject><subject>Costs</subject><subject>Electricity</subject><subject>Electricity pricing</subject><subject>Energy costs</subject><subject>Energy sources</subject><subject>Europe</subject><subject>Heterogeneity</subject><subject>Large-scale integration of renewables</subject><subject>Levelised system cost of electricity</subject><subject>Load distribution</subject><subject>Renewable energy networks</subject><subject>Renewable energy sources</subject><subject>Search algorithms</subject><subject>Solar energy</subject><subject>Solar power generation</subject><subject>Spatial distribution</subject><subject>Stress concentration</subject><subject>System design</subject><subject>Transparency</subject><subject>Wind</subject><subject>Wind power generation</subject><issn>0360-5442</issn><issn>1873-6785</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAQhoMouK7-Aw8Fz61J89HmIsjiFywsiJ5Dmkx3U7ptTbpK_70p9expDjPvOzwPQrcEZwQTcd9k0IHfT1mOSZFhnpECn6EVKQuaiqLk52iFqcApZyy_RFchNBhjXkq5Qu-7YXRH3SYHGMH3-1jkxilxXaKT4I5D62oHNjm4_aGdEh_XP7pqIXk6-X4A3SXQghm9M3MqTGGE4zW6qHUb4OZvrtHn89PH5jXd7l7eNo_b1DBajqkh1OZGV6wS0vKaG9C2sLKWuBK5wFJWTDAKOadE04ozWkhh61oDtmCpLuka3S29g--_ThBG1fQn38WXishImpeMzVdsuTK-D8FDrQYfgf2kCFazPdWoxZ6a7SnMVbQXYw9LDCLBtwOvgnHQGbDOR2Ble_d_wS_1AXxB</recordid><startdate>20170815</startdate><enddate>20170815</enddate><creator>Eriksen, Emil H.</creator><creator>Schwenk-Nebbe, Leon J.</creator><creator>Tranberg, Bo</creator><creator>Brown, Tom</creator><creator>Greiner, Martin</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>20170815</creationdate><title>Optimal heterogeneity in a simplified highly renewable European electricity system</title><author>Eriksen, Emil H. ; Schwenk-Nebbe, Leon J. ; Tranberg, Bo ; Brown, Tom ; Greiner, Martin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-c13d2cab4b69d5f5cead7d9f90b626099b4643e2531a3b543796dffae0ded3a83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Algorithms</topic><topic>Alternative energy</topic><topic>Alternative energy sources</topic><topic>Costs</topic><topic>Electricity</topic><topic>Electricity pricing</topic><topic>Energy costs</topic><topic>Energy sources</topic><topic>Europe</topic><topic>Heterogeneity</topic><topic>Large-scale integration of renewables</topic><topic>Levelised system cost of electricity</topic><topic>Load distribution</topic><topic>Renewable energy networks</topic><topic>Renewable energy sources</topic><topic>Search algorithms</topic><topic>Solar energy</topic><topic>Solar power generation</topic><topic>Spatial distribution</topic><topic>Stress concentration</topic><topic>System design</topic><topic>Transparency</topic><topic>Wind</topic><topic>Wind power generation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Eriksen, Emil H.</creatorcontrib><creatorcontrib>Schwenk-Nebbe, Leon J.</creatorcontrib><creatorcontrib>Tranberg, Bo</creatorcontrib><creatorcontrib>Brown, Tom</creatorcontrib><creatorcontrib>Greiner, Martin</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Eriksen, Emil H.</au><au>Schwenk-Nebbe, Leon J.</au><au>Tranberg, Bo</au><au>Brown, Tom</au><au>Greiner, Martin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal heterogeneity in a simplified highly renewable European electricity system</atitle><jtitle>Energy (Oxford)</jtitle><date>2017-08-15</date><risdate>2017</risdate><volume>133</volume><spage>913</spage><epage>928</epage><pages>913-928</pages><issn>0360-5442</issn><eissn>1873-6785</eissn><abstract>The resource quality and the temporal generation pattern of variable renewable energy sources vary significantly across Europe. In this paper spatial distributions of renewable assets are explored which exploit this heterogeneity to lower the total system costs for a high level of renewable electricity in Europe. Several intuitive heuristic algorithms, optimal portfolio theory and a local search algorithm are used to find optimal distributions of renewable generation capacities that minimise the total costs of backup, transmission and renewable capacity simultaneously. Using current cost projections, an optimal heterogeneous distribution favours onshore wind, particularly in countries bordering the North Sea, which results in average electricity costs that are up to 11% lower than for a homogeneous reference distribution of renewables proportional to each country's mean load. The reduction becomes even larger, namely 18%, once the transmission capacities are put to zero in the homogeneous reference distribution. Heuristic algorithms to distribute renewable capacity based on each country's wind and solar capacity factors are shown to provide a satisfactory approximation to fully optimised renewable distributions, while maintaining the benefits of transparency and comprehensibility. The sensitivities of the results to changing costs of solar generation and gas supply as well as to the possible cross-sectoral usage of unavoidable curtailment energy are also examined.
•Derivation of optimal spatial distributions of wind and solar generation capacities.•Application of several intuitive heuristic algorithms and optimal portfolio theory.•Application of a local search algorithm to minimise the total infrastructure costs.•Application to a simplified highly renewable European networked electricity system.•Optimal heterogeneous distributions reduce average electricity costs by 11–18%.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2017.05.170</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alternative energy Alternative energy sources Costs Electricity Electricity pricing Energy costs Energy sources Europe Heterogeneity Large-scale integration of renewables Levelised system cost of electricity Load distribution Renewable energy networks Renewable energy sources Search algorithms Solar energy Solar power generation Spatial distribution Stress concentration System design Transparency Wind Wind power generation |
title | Optimal heterogeneity in a simplified highly renewable European electricity system |
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