IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v233-234y2019ip338-351.html
   My bibliography  Save this article

Homogenized adjacent points method: A novel Pareto optimizer for linearized multi-objective optimal energy flow of integrated electricity and gas system

Author

Listed:
  • Qu, Kaiping
  • Yu, Tao
  • Zhang, Xiaoshun
  • Li, Haofei

Abstract

This paper constructs a novel multi-objective optimal energy flow of an integrated electricity and gas system to fully exploit complementary benefits of the system. To ensure a reliable convergence, an incremental piecewise linearization is employed to linearize the original nonlinear problem into a mixed integer linear programming. Actually, the proposed issue represents a highly constrained optimization with numerous variables and multiple conflicting objectives. To effectively solve the problem, a novel analytical Pareto optimizer called homogenized adjacent points method (HAPM) is first proposed, which aims to obtain a Pareto solution set with three basic strategies, including axes homogenization, adjacent points calculation and adjacent points filtration. Compared to the existing methods, the major superiority of HAPM is that the algorithm can obtain a full distribution of Pareto solution set with the boundary of Pareto front and non-dominated quality of the solutions. Finally, a best compromise solution is identified from the Pareto solution set using an entropy weight based ideal point method. Simulation results indicate an environmentally friendly and reliable integrated electricity and gas system is realized with a slight cost sacrifice, and validate the robustness of HAPM to obtain a non-dominated, uniform and widespread Pareto solution set compared with existing methods.

Suggested Citation

  • Qu, Kaiping & Yu, Tao & Zhang, Xiaoshun & Li, Haofei, 2019. "Homogenized adjacent points method: A novel Pareto optimizer for linearized multi-objective optimal energy flow of integrated electricity and gas system," Applied Energy, Elsevier, vol. 233, pages 338-351.
  • Handle: RePEc:eee:appene:v:233-234:y:2019:i::p:338-351
    DOI: 10.1016/j.apenergy.2018.10.037
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918315939
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2018.10.037?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. McKenna, R.C. & Bchini, Q. & Weinand, J.M. & Michaelis, J. & König, S. & Köppel, W. & Fichtner, W., 2018. "The future role of Power-to-Gas in the energy transition: Regional and local techno-economic analyses in Baden-Württemberg," Applied Energy, Elsevier, vol. 212(C), pages 386-400.
    2. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    3. Gu, Wei & Wang, Jun & Lu, Shuai & Luo, Zhao & Wu, Chenyu, 2017. "Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings," Applied Energy, Elsevier, vol. 199(C), pages 234-246.
    4. Wei, Li & Yan, Fuwu & Hu, Jie & Xi, Guangwei & Liu, Bo & Zeng, Jiawei, 2017. "Nox conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine," Applied Energy, Elsevier, vol. 206(C), pages 959-971.
    5. Touretzky, Cara R. & McGuffin, Dana L. & Ziesmer, Jena C. & Baldea, Michael, 2016. "The effect of distributed electricity generation using natural gas on the electric and natural gas grids," Applied Energy, Elsevier, vol. 177(C), pages 500-514.
    6. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Li, Xiaojing, 2017. "Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process," Applied Energy, Elsevier, vol. 194(C), pages 696-704.
    7. Reddy, S. Surender & Abhyankar, A.R. & Bijwe, P.R., 2011. "Reactive power price clearing using multi-objective optimization," Energy, Elsevier, vol. 36(5), pages 3579-3589.
    8. Zeng, Qing & Fang, Jiakun & Li, Jinghua & Chen, Zhe, 2016. "Steady-state analysis of the integrated natural gas and electric power system with bi-directional energy conversion," Applied Energy, Elsevier, vol. 184(C), pages 1483-1492.
    9. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Liu, Yuquan & Xiong, Wen, 2017. "An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power," Applied Energy, Elsevier, vol. 201(C), pages 343-353.
    10. Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    2. Qu, Kaiping & Yu, Tao & Pan, Zhenning & Zhang, Xiaoshun, 2020. "Point estimate-based stochastic robust dispatch for electricity-gas combined system under wind uncertainty using iterative convex optimization," Energy, Elsevier, vol. 211(C).
    3. Xie, Shiwei & Hu, Zhijian & Wang, Jueying, 2020. "Two-stage robust optimization for expansion planning of active distribution systems coupled with urban transportation networks," Applied Energy, Elsevier, vol. 261(C).
    4. Belderbos, Andreas & Valkaert, Thomas & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William, 2020. "Facilitating renewables and power-to-gas via integrated electrical power-gas system scheduling," Applied Energy, Elsevier, vol. 275(C).
    5. Chen, Binbin & Wu, Wenchuan & Guo, Qinglai & Sun, Hongbin, 2022. "An efficient optimal energy flow model for integrated energy systems based on energy circuit modeling in the frequency domain," Applied Energy, Elsevier, vol. 326(C).
    6. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    7. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    8. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    9. Chen, Yixuan & Qu, Kaiping & Pan, Zhenning & Yu, Tao, 2020. "Multi-objective electricity-gas flow with stochastic dispersion control for air pollutants using two-stage Pareto optimization," Applied Energy, Elsevier, vol. 279(C).
    10. Ju, Liwei & Zhao, Rui & Tan, Qinliang & Lu, Yan & Tan, Qingkun & Wang, Wei, 2019. "A multi-objective robust scheduling model and solution algorithm for a novel virtual power plant connected with power-to-gas and gas storage tank considering uncertainty and demand response," Applied Energy, Elsevier, vol. 250(C), pages 1336-1355.
    11. Chen, Yixuan & Hou, Yunhe, 2022. "Fast yet balanced trade-offs for multi-timescale multi-objective economic-environmental dispatch under varying conflicts," Applied Energy, Elsevier, vol. 328(C).
    12. Yin, Linfei & Sun, Zhixiang, 2021. "Multi-layer distributed multi-objective consensus algorithm for multi-objective economic dispatch of large-scale multi-area interconnected power systems," Applied Energy, Elsevier, vol. 300(C).
    13. Wenhui Zhang & Yajing Song & Ge Zhou & Ziwen Song & Cong Xi, 2023. "Multiobjective-Based Decision-Making for the Optimization of an Urban Passenger Traffic System Structure," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    14. Nie, Yonghui & Qiu, Yu & Yang, Annan & Zhao, Yan, 2024. "Risk-limiting dispatching strategy considering demand response in multi-energy microgrids," Applied Energy, Elsevier, vol. 353(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qu, Kaiping & Shi, Shouyuan & Yu, Tao & Wang, Wenrui, 2019. "A convex decentralized optimization for environmental-economic power and gas system considering diversified emission control," Applied Energy, Elsevier, vol. 240(C), pages 630-645.
    2. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    3. Bao, Zhejing & Chen, Dawei & Wu, Lei & Guo, Xiaogang, 2019. "Optimal inter- and intra-hour scheduling of islanded integrated-energy system considering linepack of gas pipelines," Energy, Elsevier, vol. 171(C), pages 326-340.
    4. He, Liangce & Lu, Zhigang & Zhang, Jiangfeng & Geng, Lijun & Zhao, Hao & Li, Xueping, 2018. "Low-carbon economic dispatch for electricity and natural gas systems considering carbon capture systems and power-to-gas," Applied Energy, Elsevier, vol. 224(C), pages 357-370.
    5. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Sheng, Tongtian, 2018. "Multi-time period optimized configuration and scheduling of gas storage in gas-fired power plants," Applied Energy, Elsevier, vol. 226(C), pages 924-934.
    6. Wang, Rutian & Wen, Xiangyun & Wang, Xiuyun & Fu, Yanbo & Zhang, Yu, 2022. "Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading," Applied Energy, Elsevier, vol. 311(C).
    7. Szoplik, Jolanta & Stelmasińska, Paulina, 2019. "Analysis of gas network storage capacity for alternative fuels in Poland," Energy, Elsevier, vol. 172(C), pages 343-353.
    8. Juanwei, Chen & Tao, Yu & Yue, Xu & Xiaohua, Cheng & Bo, Yang & Baomin, Zhen, 2019. "Fast analytical method for reliability evaluation of electricity-gas integrated energy system considering dispatch strategies," Applied Energy, Elsevier, vol. 242(C), pages 260-272.
    9. He, Chuan & Wu, Lei & Liu, Tianqi & Wei, Wei & Wang, Cheng, 2018. "Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties," Energy, Elsevier, vol. 159(C), pages 1003-1015.
    10. Pambour, Kwabena Addo & Cakir Erdener, Burcin & Bolado-Lavin, Ricardo & Dijkema, Gerard P.J., 2017. "SAInt – A novel quasi-dynamic model for assessing security of supply in coupled gas and electricity transmission networks," Applied Energy, Elsevier, vol. 203(C), pages 829-857.
    11. Kong, Xiangyu & Sun, Fangyuan & Huo, Xianxu & Li, Xue & Shen, Yu, 2020. "Hierarchical optimal scheduling method of heat-electricity integrated energy system based on Power Internet of Things," Energy, Elsevier, vol. 210(C).
    12. Ravnik, J. & Hriberšek, M., 2019. "A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles," Energy, Elsevier, vol. 180(C), pages 149-162.
    13. Xing, Xuetao & Lin, Jin & Song, Yonghua & Hu, Qiang & Zhou, You & Mu, Shujun, 2018. "Optimization of hydrogen yield of a high-temperature electrolysis system with coordinated temperature and feed factors at various loading conditions: A model-based study," Applied Energy, Elsevier, vol. 232(C), pages 368-385.
    14. Bailera, Manuel & Peña, Begoña & Lisbona, Pilar & Romeo, Luis M., 2018. "Decision-making methodology for managing photovoltaic surplus electricity through Power to Gas: Combined heat and power in urban buildings," Applied Energy, Elsevier, vol. 228(C), pages 1032-1045.
    15. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
    16. Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Somayeh Asadi, 2020. "Optimal Operation of Multi-Carrier Energy Networks Considering Uncertain Parameters and Thermal Energy Storage," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    17. Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
    18. Fu, Xueqian & Li, Gengyin & Zhang, Xiurong & Qiao, Zheng, 2018. "Failure probability estimation of the gas supply using a data-driven model in an integrated energy system," Applied Energy, Elsevier, vol. 232(C), pages 704-714.
    19. Raheli, Enrica & Wu, Qiuwei & Zhang, Menglin & Wen, Changyun, 2021. "Optimal coordinated operation of integrated natural gas and electric power systems: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    20. Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:233-234:y:2019:i::p:338-351. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.