An NSGA-II based multi-objective optimization for combined gas and electricity network expansion planning

•Developed a multi-objective model for the combined natural gas network and electricity network.•Taken into account the uncertainty and correlations of wind power in the proposed model.•Presented an improved point-estimation method to solve the combined optimal power and natural gas load flow. With...

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Published in:	Applied energy Vol. 167; pp. 280 - 293
Main Authors:	Hu, Yuan, Bie, Zhaohong, Ding, Tao, Lin, Yanling
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.04.2016
Subjects:	algorithms China Decision making Electricity Mathematical models Multi-objective Natural gas Natural gas network expansion planning Networks Optimization Pareto optimality planning Point-estimate method power generation Primal–Dual Interior-Point method production costs Stochasticity Transmission expansion planning wind power ISEW, China, People's Rep., Hainan Prov China Natural gas network expansion planning Primal–Dual Interior-Point method Point-estimate method Multi-objective Transmission expansion planning
ISSN:	0306-2619, 1872-9118
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Abstract	•Developed a multi-objective model for the combined natural gas network and electricity network.•Taken into account the uncertainty and correlations of wind power in the proposed model.•Presented an improved point-estimation method to solve the combined optimal power and natural gas load flow. With the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any individual system regardless of such interdependence will increase the total cost of the whole combined systems. Therefore, a multi-objective optimization model for the combined gas and electricity network planning is presented in this work. To be specific, the objectives of the proposed model are to minimize both investment cost and production cost of the combined system while taking into account the N−1 network security criterion. Moreover, the stochastic nature of wind power generation is addressed in the proposed model. Consequently, it leads to a mixed integer non-linear, multi-objective, stochastic programming problem. To solve this complex model, the Elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to capture the optimal Pareto front, wherein the Primal–Dual Interior-Point (PDIP) method combined with the point-estimate method is adopted to evaluate the objective functions. In addition, decision makers can use a fuzzy decision making approach based on their preference to select the final optimal solution from the optimal Pareto front. The effectiveness of the proposed model and method are validated on a modified IEEE 24-bus electricity network integrated with a 15-node natural gas system as well as a real-world system of Hainan province.
AbstractList	With the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any individual system regardless of such interdependence will increase the total cost of the whole combined systems. Therefore, a multi-objective optimization model for the combined gas and electricity network planning is presented in this work. To be specific, the objectives of the proposed model are to minimize both investment cost and production cost of the combined system while taking into account the N−1 network security criterion. Moreover, the stochastic nature of wind power generation is addressed in the proposed model. Consequently, it leads to a mixed integer non-linear, multi-objective, stochastic programming problem. To solve this complex model, the Elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to capture the optimal Pareto front, wherein the Primal–Dual Interior-Point (PDIP) method combined with the point-estimate method is adopted to evaluate the objective functions. In addition, decision makers can use a fuzzy decision making approach based on their preference to select the final optimal solution from the optimal Pareto front. The effectiveness of the proposed model and method are validated on a modified IEEE 24-bus electricity network integrated with a 15-node natural gas system as well as a real-world system of Hainan province. •Developed a multi-objective model for the combined natural gas network and electricity network.•Taken into account the uncertainty and correlations of wind power in the proposed model.•Presented an improved point-estimation method to solve the combined optimal power and natural gas load flow. With the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any individual system regardless of such interdependence will increase the total cost of the whole combined systems. Therefore, a multi-objective optimization model for the combined gas and electricity network planning is presented in this work. To be specific, the objectives of the proposed model are to minimize both investment cost and production cost of the combined system while taking into account the N−1 network security criterion. Moreover, the stochastic nature of wind power generation is addressed in the proposed model. Consequently, it leads to a mixed integer non-linear, multi-objective, stochastic programming problem. To solve this complex model, the Elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to capture the optimal Pareto front, wherein the Primal–Dual Interior-Point (PDIP) method combined with the point-estimate method is adopted to evaluate the objective functions. In addition, decision makers can use a fuzzy decision making approach based on their preference to select the final optimal solution from the optimal Pareto front. The effectiveness of the proposed model and method are validated on a modified IEEE 24-bus electricity network integrated with a 15-node natural gas system as well as a real-world system of Hainan province. With the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any individual system regardless of such interdependence will increase the total cost of the whole combined systems. Therefore, a multi-objective optimization model for the combined gas and electricity network planning is presented in this work. To be specific, the objectives of the proposed model are to minimize both investment cost and production cost of the combined system while taking into account the N-1 network security criterion. Moreover, the stochastic nature of wind power generation is addressed in the proposed model. Consequently, it leads to a mixed integer non-linear, multi-objective, stochastic programming problem. To solve this complex model, the Elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to capture the optimal Pareto front, wherein the Primal-Dual Interior-Point (PDIP) method combined with the point-estimate method is adopted to evaluate the objective functions. In addition, decision makers can use a fuzzy decision making approach based on their preference to select the final optimal solution from the optimal Pareto front. The effectiveness of the proposed model and method are validated on a modified IEEE 24-bus electricity network integrated with a 15-node natural gas system as well as a real-world system of Hainan province.
Author	Hu, Yuan Lin, Yanling Ding, Tao Bie, Zhaohong
Author_xml	– sequence: 1 givenname: Yuan surname: Hu fullname: Hu, Yuan – sequence: 2 givenname: Zhaohong surname: Bie fullname: Bie, Zhaohong email: zhbie@mail.xjtu.edu.cn – sequence: 3 givenname: Tao surname: Ding fullname: Ding, Tao – sequence: 4 givenname: Yanling surname: Lin fullname: Lin, Yanling
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Cites_doi	10.1109/4235.996017 10.1016/j.enpol.2010.05.016 10.1109/TIA.2004.841032 10.1109/TPWRS.2009.2020530 10.1109/TPWRS.2009.2036797 10.1109/TPWRS.2013.2263256 10.1049/iet-gtd.2010.0151 10.1109/TPWRS.2014.2299714 10.1109/TPWRS.2002.807083 10.1175/1520-0450(1976)015<0673:NAOPOF>2.0.CO;2 10.1016/j.apenergy.2013.08.071 10.1063/1.3600761 10.1049/iet-gtd.2009.0639 10.1109/TPWRS.2012.2191984 10.1002/2013EF000196 10.1109/TPWRS.2011.2182363 10.1016/j.epsr.2007.11.002 10.1016/j.apenergy.2014.06.042 10.1016/j.rser.2011.07.122 10.1109/TPWRS.2009.2023262 10.1109/TPWRS.2014.2369011 10.1109/TPWRS.2014.2344861
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References	De Gouw, Parrish, Frost, Trainer (b0020) 2014; 2 Martinez-Mares, Fuerte-Esquivel (b0095) 2013; 28 Liu, Shahidehpour, Fu, Li (b0055) 2009; 24 Cui, Li, Ren, Xue, Fang (b0085) 2012 Wang, Gong, Jiang (b0130) 2015; 30 Chompoo-Inwai, Lee, Fuangfoo, Williams, Liao (b0080) 2005; 41 An, Li, Gedra (b0030) 2003; 1 Deb, Pratap, Agarwal, Meyarivan (b0110) 2002; 6 Morales, Baringo, Conejo, Mínguez (b0120) 2010; 4 Qadrdan, Chaudry, Wu, Jenkins, Ekanayake (b0090) 2010; 38 Liu, Shahidehpour, Wang (b0050) 2011; 21 NERC. NERC planning standard; 1997. Qiu, Dong, Zhao, Meng, Zheng, Hill (b0075) 2015; 30 Unsihuay-Vila, Marangon-Lima, Perez-Arriaga, Balestrassi (b0065) 2010; 25 Liu, Shahidehpour, Wang (b0060) 2010; 4 Chaudry, Jenkins, Strbac (b0040) 2008; 78 Hedman, O’Neill, Fisher, Oren (b0115) 2009; 24 Chaudry, Jenkins, Qadrdan, Wu (b0025) 2014; 113 Martínez-Mares, Fuerte-Esquivel (b0035) 2012; 27 Justus, Hargraves, Yalcin (b0125) 1976; 15 Barati, Seifi, Sepasian, Nateghi, Shafie-khah, Catalão (b0070) 2014 Wei, Li, Zijun, Junzhao, Li (b0105) 2011 Üster, Dilaveroğlu (b0005) 2014; 133 Fang, Hill (b0140) 2003; 18 Ozturk, Yuksel, Ozek (b0010) 2011; 15 Moeini-Aghtaie, Abbaspour, Fotuhi-Firuzabad (b0135) 2012; 27 International energy agency. World energy, Outlook 2010; 2010. Correa-Posada, Sánchez-Martın (b0045) 2014; 29 Ozturk (10.1016/j.apenergy.2015.10.148_b0010) 2011; 15 Chaudry (10.1016/j.apenergy.2015.10.148_b0025) 2014; 113 Qadrdan (10.1016/j.apenergy.2015.10.148_b0090) 2010; 38 Martinez-Mares (10.1016/j.apenergy.2015.10.148_b0095) 2013; 28 Üster (10.1016/j.apenergy.2015.10.148_b0005) 2014; 133 Liu (10.1016/j.apenergy.2015.10.148_b0050) 2011; 21 Hedman (10.1016/j.apenergy.2015.10.148_b0115) 2009; 24 Liu (10.1016/j.apenergy.2015.10.148_b0055) 2009; 24 Martínez-Mares (10.1016/j.apenergy.2015.10.148_b0035) 2012; 27 Justus (10.1016/j.apenergy.2015.10.148_b0125) 1976; 15 Qiu (10.1016/j.apenergy.2015.10.148_b0075) 2015; 30 Morales (10.1016/j.apenergy.2015.10.148_b0120) 2010; 4 Cui (10.1016/j.apenergy.2015.10.148_b0085) 2012 Chaudry (10.1016/j.apenergy.2015.10.148_b0040) 2008; 78 Wang (10.1016/j.apenergy.2015.10.148_b0130) 2015; 30 Fang (10.1016/j.apenergy.2015.10.148_b0140) 2003; 18 Chompoo-Inwai (10.1016/j.apenergy.2015.10.148_b0080) 2005; 41 Wei (10.1016/j.apenergy.2015.10.148_b0105) 2011 Moeini-Aghtaie (10.1016/j.apenergy.2015.10.148_b0135) 2012; 27 10.1016/j.apenergy.2015.10.148_b0015 Unsihuay-Vila (10.1016/j.apenergy.2015.10.148_b0065) 2010; 25 10.1016/j.apenergy.2015.10.148_b0100 Liu (10.1016/j.apenergy.2015.10.148_b0060) 2010; 4 De Gouw (10.1016/j.apenergy.2015.10.148_b0020) 2014; 2 Deb (10.1016/j.apenergy.2015.10.148_b0110) 2002; 6 An (10.1016/j.apenergy.2015.10.148_b0030) 2003; 1 Correa-Posada (10.1016/j.apenergy.2015.10.148_b0045) 2014; 29 Barati (10.1016/j.apenergy.2015.10.148_b0070) 2014
References_xml	– volume: 38 start-page: 5684 year: 2010 end-page: 5695 ident: b0090 article-title: Impact of a large penetration of wind generation on the GB gas network publication-title: Energy Policy – start-page: 285 year: 2012 end-page: 288 ident: b0085 article-title: Review of transmission planning with large-scale wind power integration publication-title: 2012 Electromagn Comp (APEMC) – volume: 28 start-page: 3964 year: 2013 end-page: 3976 ident: b0095 article-title: A robust optimization approach for the interdependency analysis of integrated energy systems considering wind power uncertainty publication-title: IEEE Trans Power Syst – volume: 133 start-page: 56 year: 2014 end-page: 69 ident: b0005 article-title: Optimization for design and operation of natural gas transmission networks publication-title: Appl Energy – volume: 30 start-page: 1094 year: 2015 end-page: 1103 ident: b0130 article-title: Regional carbon emission management based on probabilistic power flow with correlated stochastic variables publication-title: IEEE Trans Power Syst – volume: 18 start-page: 374 year: 2003 end-page: 380 ident: b0140 article-title: A new strategy for transmission expansion in competitive electricity markets publication-title: IEEE Trans Power Syst – reference: International energy agency. World energy, Outlook 2010; 2010. – volume: 25 start-page: 1154 year: 2010 end-page: 1168 ident: b0065 article-title: A model to long-term, multiarea, multistage, and integrated expansion planning of electricity and natural gas systems publication-title: IEEE Trans Power Syst – volume: 1 start-page: 138 year: 2003 end-page: 143 ident: b0030 article-title: Natural gas and electricity optimal power flow, transmission and distribution conference and exposition publication-title: IEEE Power Eng Soc – volume: 24 start-page: 1577 year: 2009 end-page: 1586 ident: b0115 article-title: Optimal transmission switching with contingency analysis publication-title: IEEE Trans Power Syst – volume: 30 start-page: 1035 year: 2015 end-page: 1046 ident: b0075 article-title: Low carbon oriented expansion planning of integrated gas and power systems publication-title: IEEE Trans Power Syst – reference: NERC. NERC planning standard; 1997. – volume: 4 start-page: 641 year: 2010 end-page: 651 ident: b0120 article-title: Probabilistic power flow with correlated wind sources publication-title: Gener Transm Distrib – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: b0110 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: Evol Comput – volume: 15 start-page: 673 year: 1976 end-page: 678 ident: b0125 article-title: Nationwide assessment of potential output from wind-powered generators publication-title: J Appl Meteorol – volume: 113 start-page: 1171 year: 2014 end-page: 1187 ident: b0025 article-title: Combined gas and electricity network expansion planning publication-title: Appl Energy – year: 2014 ident: b0070 article-title: Multi-period integrated framework of generation, transmission, and natural gas grid expansion planning for large-scale systems publication-title: IEEE Trans Power Syst – volume: 15 start-page: 4286 year: 2011 end-page: 4294 ident: b0010 article-title: A bridge between east and west: Turkey’s natural gas policy publication-title: Renew Sustain Energy Rev – volume: 27 start-page: 2156 year: 2012 end-page: 2166 ident: b0035 article-title: A unified gas and power flow analysis in natural gas and electricity coupled networks publication-title: IEEE Trans Power Syst – volume: 24 start-page: 1523 year: 2009 end-page: 1536 ident: b0055 article-title: Security-constrained unit commitment with natural gas transmission constraints publication-title: IEEE Trans Power Syst – volume: 2 start-page: 75 year: 2014 end-page: 82 ident: b0020 article-title: Reduced emissions of CO2, NOx, and SO2 from US power plants owing to switch from coal to natural gas with combined cycle technology publication-title: Earth’s Future – volume: 41 start-page: 163 year: 2005 end-page: 168 ident: b0080 article-title: System impact study for the interconnection of wind generation and utility system publication-title: Ind Appl – volume: 21 start-page: 025102 year: 2011 ident: b0050 article-title: Coordinated scheduling of electricity and natural gas infrastructures with a transient model for natural gas flow publication-title: Chaos: An Interdiscipl J Nonlinear Sci – start-page: 1250 year: 2011 end-page: 1254 ident: b0105 article-title: Transmission network planning with N-1 security criterion based on improved multi-objective genetic algorithm publication-title: Electr Utility Deregul Restruct Power Technol (DRPT) – volume: 29 start-page: 1780 year: 2014 end-page: 1787 ident: b0045 article-title: Security-constrained optimal power and natural-gas flow publication-title: IEEE Trans Power Syst – volume: 27 start-page: 1585 year: 2012 end-page: 1593 ident: b0135 article-title: Incorporating large-scale distant wind farms in probabilistic transmission expansion planning—Part I: Theory and algorithm publication-title: IEEE Trans Power Syst – volume: 78 start-page: 1265 year: 2008 end-page: 1279 ident: b0040 article-title: Multi-time period combined gas and electricity network optimisation publication-title: Electr Power Syst Res – volume: 4 start-page: 1314 year: 2010 end-page: 1325 ident: b0060 article-title: Application of augmented Lagrangian relaxation to coordinated scheduling of interdependent hydrothermal power and natural gas systems publication-title: Gener Transm Distrib – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.apenergy.2015.10.148_b0110 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: Evol Comput doi: 10.1109/4235.996017 – ident: 10.1016/j.apenergy.2015.10.148_b0015 – volume: 38 start-page: 5684 issue: 10 year: 2010 ident: 10.1016/j.apenergy.2015.10.148_b0090 article-title: Impact of a large penetration of wind generation on the GB gas network publication-title: Energy Policy doi: 10.1016/j.enpol.2010.05.016 – start-page: 1250 year: 2011 ident: 10.1016/j.apenergy.2015.10.148_b0105 article-title: Transmission network planning with N-1 security criterion based on improved multi-objective genetic algorithm publication-title: Electr Utility Deregul Restruct Power Technol (DRPT) – volume: 41 start-page: 163 issue: 1 year: 2005 ident: 10.1016/j.apenergy.2015.10.148_b0080 article-title: System impact study for the interconnection of wind generation and utility system publication-title: Ind Appl doi: 10.1109/TIA.2004.841032 – volume: 24 start-page: 1577 issue: 3 year: 2009 ident: 10.1016/j.apenergy.2015.10.148_b0115 article-title: Optimal transmission switching with contingency analysis publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2020530 – volume: 25 start-page: 1154 issue: 2 year: 2010 ident: 10.1016/j.apenergy.2015.10.148_b0065 article-title: A model to long-term, multiarea, multistage, and integrated expansion planning of electricity and natural gas systems publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2036797 – year: 2014 ident: 10.1016/j.apenergy.2015.10.148_b0070 article-title: Multi-period integrated framework of generation, transmission, and natural gas grid expansion planning for large-scale systems publication-title: IEEE Trans Power Syst – volume: 28 start-page: 3964 issue: 4 year: 2013 ident: 10.1016/j.apenergy.2015.10.148_b0095 article-title: A robust optimization approach for the interdependency analysis of integrated energy systems considering wind power uncertainty publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2013.2263256 – volume: 4 start-page: 1314 issue: 12 year: 2010 ident: 10.1016/j.apenergy.2015.10.148_b0060 article-title: Application of augmented Lagrangian relaxation to coordinated scheduling of interdependent hydrothermal power and natural gas systems publication-title: Gener Transm Distrib doi: 10.1049/iet-gtd.2010.0151 – volume: 29 start-page: 1780 issue: 4 year: 2014 ident: 10.1016/j.apenergy.2015.10.148_b0045 article-title: Security-constrained optimal power and natural-gas flow publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2014.2299714 – volume: 18 start-page: 374 issue: 1 year: 2003 ident: 10.1016/j.apenergy.2015.10.148_b0140 article-title: A new strategy for transmission expansion in competitive electricity markets publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2002.807083 – volume: 15 start-page: 673 issue: 7 year: 1976 ident: 10.1016/j.apenergy.2015.10.148_b0125 article-title: Nationwide assessment of potential output from wind-powered generators publication-title: J Appl Meteorol doi: 10.1175/1520-0450(1976)015<0673:NAOPOF>2.0.CO;2 – volume: 113 start-page: 1171 year: 2014 ident: 10.1016/j.apenergy.2015.10.148_b0025 article-title: Combined gas and electricity network expansion planning publication-title: Appl Energy doi: 10.1016/j.apenergy.2013.08.071 – volume: 1 start-page: 138 year: 2003 ident: 10.1016/j.apenergy.2015.10.148_b0030 article-title: Natural gas and electricity optimal power flow, transmission and distribution conference and exposition publication-title: IEEE Power Eng Soc – volume: 21 start-page: 025102 issue: 2 year: 2011 ident: 10.1016/j.apenergy.2015.10.148_b0050 article-title: Coordinated scheduling of electricity and natural gas infrastructures with a transient model for natural gas flow publication-title: Chaos: An Interdiscipl J Nonlinear Sci doi: 10.1063/1.3600761 – volume: 4 start-page: 641 issue: 5 year: 2010 ident: 10.1016/j.apenergy.2015.10.148_b0120 article-title: Probabilistic power flow with correlated wind sources publication-title: Gener Transm Distrib doi: 10.1049/iet-gtd.2009.0639 – volume: 27 start-page: 2156 issue: 4 year: 2012 ident: 10.1016/j.apenergy.2015.10.148_b0035 article-title: A unified gas and power flow analysis in natural gas and electricity coupled networks publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2012.2191984 – ident: 10.1016/j.apenergy.2015.10.148_b0100 – volume: 2 start-page: 75 issue: 2 year: 2014 ident: 10.1016/j.apenergy.2015.10.148_b0020 article-title: Reduced emissions of CO2, NOx, and SO2 from US power plants owing to switch from coal to natural gas with combined cycle technology publication-title: Earth’s Future doi: 10.1002/2013EF000196 – volume: 27 start-page: 1585 issue: 3 year: 2012 ident: 10.1016/j.apenergy.2015.10.148_b0135 article-title: Incorporating large-scale distant wind farms in probabilistic transmission expansion planning—Part I: Theory and algorithm publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2011.2182363 – volume: 78 start-page: 1265 issue: 7 year: 2008 ident: 10.1016/j.apenergy.2015.10.148_b0040 article-title: Multi-time period combined gas and electricity network optimisation publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2007.11.002 – volume: 133 start-page: 56 year: 2014 ident: 10.1016/j.apenergy.2015.10.148_b0005 article-title: Optimization for design and operation of natural gas transmission networks publication-title: Appl Energy doi: 10.1016/j.apenergy.2014.06.042 – start-page: 285 year: 2012 ident: 10.1016/j.apenergy.2015.10.148_b0085 article-title: Review of transmission planning with large-scale wind power integration publication-title: 2012 Electromagn Comp (APEMC) – volume: 15 start-page: 4286 issue: 9 year: 2011 ident: 10.1016/j.apenergy.2015.10.148_b0010 article-title: A bridge between east and west: Turkey’s natural gas policy publication-title: Renew Sustain Energy Rev doi: 10.1016/j.rser.2011.07.122 – volume: 24 start-page: 1523 issue: 3 year: 2009 ident: 10.1016/j.apenergy.2015.10.148_b0055 article-title: Security-constrained unit commitment with natural gas transmission constraints publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2023262 – volume: 30 start-page: 1035 issue: 2 year: 2015 ident: 10.1016/j.apenergy.2015.10.148_b0075 article-title: Low carbon oriented expansion planning of integrated gas and power systems publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2014.2369011 – volume: 30 start-page: 1094 issue: 2 year: 2015 ident: 10.1016/j.apenergy.2015.10.148_b0130 article-title: Regional carbon emission management based on probabilistic power flow with correlated stochastic variables publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2014.2344861
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Snippet	•Developed a multi-objective model for the combined natural gas network and electricity network.•Taken into account the uncertainty and correlations of wind... With the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any...
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SubjectTerms	algorithms China Decision making Electricity Mathematical models Multi-objective Natural gas Natural gas network expansion planning Networks Optimization Pareto optimality planning Point-estimate method power generation Primal–Dual Interior-Point method production costs Stochasticity Transmission expansion planning wind power
Title	An NSGA-II based multi-objective optimization for combined gas and electricity network expansion planning
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