A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy

This study proposes a multi-objective optimization methodology for planning multi-energy complementary distributed energy systems considering process synergy and thermal integration. The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and...

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Veröffentlicht in:Journal of cleaner production 2023-03, Vol.390, p.135905, Article 135905
Hauptverfasser: Li, Chengzhou, Wang, Ligang, Zhang, Yumeng, Yu, Hangyu, Wang, Zhuo, Li, Liang, Wang, Ningling, Yang, Zhiping, Maréchal, François, Yang, Yongping
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container_issue
container_start_page 135905
container_title Journal of cleaner production
container_volume 390
creator Li, Chengzhou
Wang, Ligang
Zhang, Yumeng
Yu, Hangyu
Wang, Zhuo
Li, Liang
Wang, Ningling
Yang, Zhiping
Maréchal, François
Yang, Yongping
description This study proposes a multi-objective optimization methodology for planning multi-energy complementary distributed energy systems considering process synergy and thermal integration. The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and temporal source-load matching. The system design and dispatch strategy are optimized by an augmented ε-constraint method with three objectives (economics, carbon emission, and fossil fuel consumption), and then the optimal tradeoff solution is identified by the Technique for Order Preference by Similarity to an Ideal Solution. Moreover, a novel multi-energy complementary distributed energy system is developed, which includes comprehensive utilization of solar energy (photovoltaic, photothermal, and thermochemical) and middle-low temperature heat utilization technologies, as well as hybrid energy storage technologies. Finally, a case study located in Beijing is selected as an illustrated example. The obtained single-objective optimization solutions and Pareto optimal solutions are further analyzed and compared in terms of system configuration, hourly/yearly energy balance, and thermal integration condition. The results show that the multi-energy complementary distributed energy system presents an economic benefit (reducing 25% of the annual total cost) compared to a gas turbine-based integrated energy system. Considering thermal integration contributes to 5.13% of the cost reduction. The configuration of the energy storage devices will reduce 18% energy supply cost, 9% fossil fuel consumption, and 42% carbon emission with the storage devices' boundary increase from 2 MWh to 60 MWh. Moreover, the optimal design of the system provides a reference for decision-making and a basis for flexible operation. The annual total cost, carbon emission, and fossil fuel consumption of the optimal solution in the Pareto frontier are 8.19 million CNY, 2.91 kt CO2-eq./year, and 18.4 GWh, respectively. [Display omitted]
doi_str_mv 10.1016/j.jclepro.2023.135905
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The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and temporal source-load matching. The system design and dispatch strategy are optimized by an augmented ε-constraint method with three objectives (economics, carbon emission, and fossil fuel consumption), and then the optimal tradeoff solution is identified by the Technique for Order Preference by Similarity to an Ideal Solution. Moreover, a novel multi-energy complementary distributed energy system is developed, which includes comprehensive utilization of solar energy (photovoltaic, photothermal, and thermochemical) and middle-low temperature heat utilization technologies, as well as hybrid energy storage technologies. Finally, a case study located in Beijing is selected as an illustrated example. The obtained single-objective optimization solutions and Pareto optimal solutions are further analyzed and compared in terms of system configuration, hourly/yearly energy balance, and thermal integration condition. The results show that the multi-energy complementary distributed energy system presents an economic benefit (reducing 25% of the annual total cost) compared to a gas turbine-based integrated energy system. Considering thermal integration contributes to 5.13% of the cost reduction. The configuration of the energy storage devices will reduce 18% energy supply cost, 9% fossil fuel consumption, and 42% carbon emission with the storage devices' boundary increase from 2 MWh to 60 MWh. Moreover, the optimal design of the system provides a reference for decision-making and a basis for flexible operation. The annual total cost, carbon emission, and fossil fuel consumption of the optimal solution in the Pareto frontier are 8.19 million CNY, 2.91 kt CO2-eq./year, and 18.4 GWh, respectively. 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The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and temporal source-load matching. The system design and dispatch strategy are optimized by an augmented ε-constraint method with three objectives (economics, carbon emission, and fossil fuel consumption), and then the optimal tradeoff solution is identified by the Technique for Order Preference by Similarity to an Ideal Solution. Moreover, a novel multi-energy complementary distributed energy system is developed, which includes comprehensive utilization of solar energy (photovoltaic, photothermal, and thermochemical) and middle-low temperature heat utilization technologies, as well as hybrid energy storage technologies. Finally, a case study located in Beijing is selected as an illustrated example. The obtained single-objective optimization solutions and Pareto optimal solutions are further analyzed and compared in terms of system configuration, hourly/yearly energy balance, and thermal integration condition. The results show that the multi-energy complementary distributed energy system presents an economic benefit (reducing 25% of the annual total cost) compared to a gas turbine-based integrated energy system. Considering thermal integration contributes to 5.13% of the cost reduction. The configuration of the energy storage devices will reduce 18% energy supply cost, 9% fossil fuel consumption, and 42% carbon emission with the storage devices' boundary increase from 2 MWh to 60 MWh. Moreover, the optimal design of the system provides a reference for decision-making and a basis for flexible operation. The annual total cost, carbon emission, and fossil fuel consumption of the optimal solution in the Pareto frontier are 8.19 million CNY, 2.91 kt CO2-eq./year, and 18.4 GWh, respectively. [Display omitted]</description><subject>carbon</subject><subject>case studies</subject><subject>China</subject><subject>cost effectiveness</subject><subject>decision making</subject><subject>Distributed energy system</subject><subject>energy balance</subject><subject>Energy hub</subject><subject>Energy planning</subject><subject>energy use and consumption</subject><subject>financial economics</subject><subject>fossil fuels</subject><subject>heat</subject><subject>Multi-energy complementary</subject><subject>Multi-objective optimization</subject><subject>Process integration</subject><subject>solar energy</subject><subject>systems engineering</subject><subject>temperature</subject><issn>0959-6526</issn><issn>1879-1786</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkEFr3DAQhUVoINukPyGgYy_ejGxLlnopITRpIJBLchayPN7IsaWtpA3sf8iPrra798LAXN57M-8j5JrBmgETN9N6sjNuY1jXUDdr1nAF_IysmOxUxTopvpAVKK4qwWtxQb6mNAGwDrp2RT5v6bKbs6tCP6HN7gPpdjbeO7-hC-a3MNAxxJMGPcbNntqwbGdc0GcT93RwKUfX7zIO9CRI-5Rx-UFfjH2fD0n5DeNiZup8xk002QVPjR9o-dliSsXwz3hFzkczJ_x22pfk9f7Xy93v6un54fHu9qmyTVvnUsmAaoXlfW1aKSXvQbSj6qzgVsGIjRTYwNjWIK3sRiUsgpF9C2NfKwBoLsn3Y265_2eHKevFJYtzKY5hl3TDeBnWqYOUH6U2hpQijnob3VJ6awb6QF9P-kRfH-jrI_3i-3n0Yenx4TDqZB16i4OLhbMegvtPwl_E3pQi</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Li, Chengzhou</creator><creator>Wang, Ligang</creator><creator>Zhang, Yumeng</creator><creator>Yu, Hangyu</creator><creator>Wang, Zhuo</creator><creator>Li, Liang</creator><creator>Wang, Ningling</creator><creator>Yang, Zhiping</creator><creator>Maréchal, François</creator><creator>Yang, Yongping</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20230301</creationdate><title>A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy</title><author>Li, Chengzhou ; Wang, Ligang ; Zhang, Yumeng ; Yu, Hangyu ; Wang, Zhuo ; Li, Liang ; Wang, Ningling ; Yang, Zhiping ; Maréchal, François ; Yang, Yongping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c342t-17a0946c5b2a48885b064f97c65c90fe386e30f4208c87f96ce0a8b40fb290003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>carbon</topic><topic>case studies</topic><topic>China</topic><topic>cost effectiveness</topic><topic>decision making</topic><topic>Distributed energy system</topic><topic>energy balance</topic><topic>Energy hub</topic><topic>Energy planning</topic><topic>energy use and consumption</topic><topic>financial economics</topic><topic>fossil fuels</topic><topic>heat</topic><topic>Multi-energy complementary</topic><topic>Multi-objective optimization</topic><topic>Process integration</topic><topic>solar energy</topic><topic>systems engineering</topic><topic>temperature</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Chengzhou</creatorcontrib><creatorcontrib>Wang, Ligang</creatorcontrib><creatorcontrib>Zhang, Yumeng</creatorcontrib><creatorcontrib>Yu, Hangyu</creatorcontrib><creatorcontrib>Wang, Zhuo</creatorcontrib><creatorcontrib>Li, Liang</creatorcontrib><creatorcontrib>Wang, Ningling</creatorcontrib><creatorcontrib>Yang, Zhiping</creatorcontrib><creatorcontrib>Maréchal, François</creatorcontrib><creatorcontrib>Yang, Yongping</creatorcontrib><collection>CrossRef</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of cleaner production</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Chengzhou</au><au>Wang, Ligang</au><au>Zhang, Yumeng</au><au>Yu, Hangyu</au><au>Wang, Zhuo</au><au>Li, Liang</au><au>Wang, Ningling</au><au>Yang, Zhiping</au><au>Maréchal, François</au><au>Yang, Yongping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy</atitle><jtitle>Journal of cleaner production</jtitle><date>2023-03-01</date><risdate>2023</risdate><volume>390</volume><spage>135905</spage><pages>135905-</pages><artnum>135905</artnum><issn>0959-6526</issn><eissn>1879-1786</eissn><abstract>This study proposes a multi-objective optimization methodology for planning multi-energy complementary distributed energy systems considering process synergy and thermal integration. The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and temporal source-load matching. The system design and dispatch strategy are optimized by an augmented ε-constraint method with three objectives (economics, carbon emission, and fossil fuel consumption), and then the optimal tradeoff solution is identified by the Technique for Order Preference by Similarity to an Ideal Solution. Moreover, a novel multi-energy complementary distributed energy system is developed, which includes comprehensive utilization of solar energy (photovoltaic, photothermal, and thermochemical) and middle-low temperature heat utilization technologies, as well as hybrid energy storage technologies. Finally, a case study located in Beijing is selected as an illustrated example. The obtained single-objective optimization solutions and Pareto optimal solutions are further analyzed and compared in terms of system configuration, hourly/yearly energy balance, and thermal integration condition. The results show that the multi-energy complementary distributed energy system presents an economic benefit (reducing 25% of the annual total cost) compared to a gas turbine-based integrated energy system. Considering thermal integration contributes to 5.13% of the cost reduction. The configuration of the energy storage devices will reduce 18% energy supply cost, 9% fossil fuel consumption, and 42% carbon emission with the storage devices' boundary increase from 2 MWh to 60 MWh. Moreover, the optimal design of the system provides a reference for decision-making and a basis for flexible operation. The annual total cost, carbon emission, and fossil fuel consumption of the optimal solution in the Pareto frontier are 8.19 million CNY, 2.91 kt CO2-eq./year, and 18.4 GWh, respectively. [Display omitted]</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.jclepro.2023.135905</doi></addata></record>
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source Elsevier ScienceDirect Journals Complete
subjects carbon
case studies
China
cost effectiveness
decision making
Distributed energy system
energy balance
Energy hub
Energy planning
energy use and consumption
financial economics
fossil fuels
heat
Multi-energy complementary
Multi-objective optimization
Process integration
solar energy
systems engineering
temperature
title A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy
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