IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v285y2021ics0306261921000258.html
   My bibliography  Save this article

Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand

Author

Listed:
  • Li, Xiaozhu
  • Wang, Weiqing
  • Wang, Haiyun

Abstract

In view of the complex energy coupling and multiple market entities competition in integrated energy system, a hybrid time-scale energy optimal scheduling model based on game interaction with supply and demand is presented. Considering the initiative of market players in the day-ahead scale, a bilateral game interaction framework for the operator of integrated energy system and a calibration model considering differences in energy distinguishing feature in the intraday scale are presented. At the intraday scale, the cold and thermal energy related equipment and controllable resources with low time resolution were modified combined with the day-ahead plan in slow layer, while the power related’s with high time resolution were modified combined with the slow layer plan in fast layer. Aim at the above-mentioned complex model, such as multi-objective, nonconvex, strong constraint, large-scale decision variables and irregular Pareto front shape, an adaptive reference point based large scale multi-objective whale optimization algorithm is proposed. Finally, the bilateral interactivity and sensitivity for scheduling results were quantitatively analyzed, under the influence of power generation and consumption uncertainty. The results show that the strategy can balance the economy and robustness, improve the profit benefit of IES by 61.5% with the traditional robustness. Balance the benefits of market entities, bilateral game can increase the benefit of IES by 57.6%. The model based on different energy characteristics is more in line with the actual scheduling situation.

Suggested Citation

  • Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
  • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000258
    DOI: 10.1016/j.apenergy.2021.116458
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921000258
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.116458?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. Liu, Yangyang & Shen, Zhongqi & Tang, Xiaowei & Lian, Hongbo & Li, Jiarui & Gong, Jinxia, 2019. "Worst-case conditional value-at-risk based bidding strategy for wind-hydro hybrid systems under probability distribution uncertainties," Applied Energy, Elsevier, vol. 256(C).
    2. Zhou, Bo & Chen, Guo & Song, Qiankun & Dong, Zhao Yang, 2020. "Robust chance-constrained programming approach for the planning of fast-charging stations in electrified transportation networks," Applied Energy, Elsevier, vol. 262(C).
    3. Wang, Yongli & Wang, Yudong & Huang, Yujing & Yang, Jiale & Ma, Yuze & Yu, Haiyang & Zeng, Ming & Zhang, Fuwei & Zhang, Yanfu, 2019. "Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Xie, Shiwei & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "The optimal planning of smart multi-energy systems incorporating transportation, natural gas and active distribution networks," Applied Energy, Elsevier, vol. 269(C).
    5. Ferreira, Willian M. & Meneghini, Ivan R. & Brandao, Danilo I. & Guimarães, Frederico G., 2020. "Preference cone based multi-objective evolutionary algorithm applied to optimal management of distributed energy resources in microgrids," Applied Energy, Elsevier, vol. 274(C).
    6. Zhang, Wei & Valencia, Andrea & Gu, Lixing & Zheng, Qipeng P. & Chang, Ni-Bin, 2020. "Integrating emerging and existing renewable energy technologies into a community-scale microgrid in an energy-water nexus for resilience improvement," Applied Energy, Elsevier, vol. 279(C).
    7. Basu, M., 2019. "Squirrel search algorithm for multi-region combined heat and power economic dispatch incorporating renewable energy sources," Energy, Elsevier, vol. 182(C), pages 296-305.
    8. Tang, Rui & Wang, Shengwei & Li, Hangxin, 2019. "Game theory based interactive demand side management responding to dynamic pricing in price-based demand response of smart grids," Applied Energy, Elsevier, vol. 250(C), pages 118-130.
    9. Bi, Yalan & Choe, Song-Yul, 2020. "An adaptive sigma-point Kalman filter with state equality constraints for online state-of-charge estimation of a Li(NiMnCo)O2/Carbon battery using a reduced-order electrochemical model," Applied Energy, Elsevier, vol. 258(C).
    10. Farahani, Samira S. & Bleeker, Cliff & van Wijk, Ad & Lukszo, Zofia, 2020. "Hydrogen-based integrated energy and mobility system for a real-life office environment," Applied Energy, Elsevier, vol. 264(C).
    11. Tan, Zhongfu & Wang, Guan & Ju, Liwei & Tan, Qingkun & Yang, Wenhai, 2017. "Application of CVaR risk aversion approach in the dynamical scheduling optimization model for virtual power plant connected with wind-photovoltaic-energy storage system with uncertainties and demand r," Energy, Elsevier, vol. 124(C), pages 198-213.
    12. Zhou, Yue & Wu, Jianzhong & Song, Guanyu & Long, Chao, 2020. "Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community," Applied Energy, Elsevier, vol. 278(C).
    13. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).
    14. Motlagh, Tara Yazdani & Azadani, Leila N. & Yazdani, Kaveh, 2020. "Multi-objective optimization of diesel injection parameters in a natural gas/diesel reactivity controlled compression ignition engine," Applied Energy, Elsevier, vol. 279(C).
    15. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    16. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    17. Li, Longxi & Yu, Shiwei & Mu, Hailin & Li, Huanan, 2018. "Optimization and evaluation of CCHP systems considering incentive policies under different operation strategies," Energy, Elsevier, vol. 162(C), pages 825-840.
    18. Kotireddy, Rajesh & Hoes, Pieter-Jan & Hensen, Jan L.M., 2018. "A methodology for performance robustness assessment of low-energy buildings using scenario analysis," Applied Energy, Elsevier, vol. 212(C), pages 428-442.
    19. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    20. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun & Wu, Jiahui & Fan, Xiaochao & Xu, Qidan, 2020. "Dynamic environmental economic dispatch of hybrid renewable energy systems based on tradable green certificates," Energy, Elsevier, vol. 193(C).
    21. Moser, A. & Muschick, D. & Gölles, M. & Nageler, P. & Schranzhofer, H. & Mach, T. & Ribas Tugores, C. & Leusbrock, I. & Stark, S. & Lackner, F. & Hofer, A., 2020. "A MILP-based modular energy management system for urban multi-energy systems: Performance and sensitivity analysis," Applied Energy, Elsevier, vol. 261(C).
    22. Salata, Ferdinando & Ciancio, Virgilio & Dell'Olmo, Jacopo & Golasi, Iacopo & Palusci, Olga & Coppi, Massimo, 2020. "Effects of local conditions on the multi-variable and multi-objective energy optimization of residential buildings using genetic algorithms," Applied Energy, Elsevier, vol. 260(C).
    23. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    24. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    25. Poplavskaya, Ksenia & Totschnig, Gerhard & Leimgruber, Fabian & Doorman, Gerard & Etienne, Gilles & de Vries, Laurens, 2020. "Integration of day-ahead market and redispatch to increase cross-border exchanges in the European electricity market," Applied Energy, Elsevier, vol. 278(C).
    26. Tushar, Wayes & Saha, Tapan Kumar & Yuen, Chau & Morstyn, Thomas & McCulloch, Malcolm D. & Poor, H. Vincent & Wood, Kristin L., 2019. "A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid," Applied Energy, Elsevier, vol. 243(C), pages 10-20.
    27. Yang, Weiwei & Ruan, Jiageng & Yang, Jue & Zhang, Nong, 2020. "Investigation of integrated uninterrupted dual input transmission and hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    28. Wang, Cong & Zhang, Hongli & Ma, Ping, 2020. "Wind power forecasting based on singular spectrum analysis and a new hybrid Laguerre neural network," Applied Energy, Elsevier, vol. 259(C).
    29. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    30. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2018. "Microgrids energy management systems: A critical review on methods, solutions, and prospects," Applied Energy, Elsevier, vol. 222(C), pages 1033-1055.
    31. Qu, Kaiping & Zheng, Baomin & Yu, Tao & Li, Haofei, 2019. "Convex decoupled-synergetic strategies for robust multi-objective power and gas flow considering power to gas," Energy, Elsevier, vol. 168(C), pages 753-771.
    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. Gejirifu De & Xinlei Wang & Xueqin Tian & Tong Xu & Zhongfu Tan, 2022. "A Collaborative Optimization Model for Integrated Energy System Considering Multi-Load Demand Response," Energies, MDPI, vol. 15(6), pages 1-26, March.
    2. Wu, Min & Xu, Jiazhu & Shi, Zhenglu, 2023. "Low carbon economic dispatch of integrated energy system considering extended electric heating demand response," Energy, Elsevier, vol. 278(PA).
    3. Wang, L.X. & Zheng, J.H. & Li, Z.G. & Jing, Z.X. & Wu, Q.H., 2022. "Order reduction method for high-order dynamic analysis of heterogeneous integrated energy systems," Applied Energy, Elsevier, vol. 308(C).
    4. Li, Hangxin & Wang, Shengwei, 2022. "Two-time-scale coordinated optimal control of building energy systems for demand response considering forecast uncertainties," Energy, Elsevier, vol. 253(C).
    5. Chen, Changming & Wu, Xueyan & Li, Yan & Zhu, Xiaojun & Li, Zesen & Ma, Jien & Qiu, Weiqiang & Liu, Chang & Lin, Zhenzhi & Yang, Li & Wang, Qin & Ding, Yi, 2021. "Distributionally robust day-ahead scheduling of park-level integrated energy system considering generalized energy storages," Applied Energy, Elsevier, vol. 302(C).
    6. Chen, Jing & Li, Fan & Li, Haoran & Sun, Bo & Zhang, Chenghui & Liu, Shuai, 2023. "Novel dynamic equivalent circuit model of integrated energy systems," Energy, Elsevier, vol. 262(PA).
    7. Qin, Yuxiao & Liu, Pei & Li, Zheng, 2022. "Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    8. Jiawei Wang & Aidong Zeng & Yaheng Wan, 2023. "Multi-Time-Scale Optimal Scheduling of Integrated Energy System Considering Transmission Delay and Heat Storage of Heating Network," Sustainability, MDPI, vol. 15(19), pages 1-26, September.
    9. Frank Pierie & Christian E. J. van Someren & Sandór N. M. Kruse & Gideon A. H. Laugs & René M. J. Benders & Henri C. Moll, 2021. "Local Balancing of the Electricity Grid in a Renewable Municipality; Analyzing the Effectiveness and Cost of Decentralized Load Balancing Looking at Multiple Combinations of Technologies," Energies, MDPI, vol. 14(16), pages 1-35, August.
    10. Lu, Qing & Guo, Qisheng & Zeng, Wei, 2022. "Optimization scheduling of integrated energy service system in community: A bi-layer optimization model considering multi-energy demand response and user satisfaction," Energy, Elsevier, vol. 252(C).
    11. Zeljković, Čedomir & Mršić, Predrag & Erceg, Bojan & Lekić, Đorđe & Kitić, Nemanja & Matić, Petar, 2022. "Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations," Energy, Elsevier, vol. 242(C).
    12. He, Shuaijia & Gao, Hongjun & Liu, Junyong & Zhang, Xi & Chen, Zhe, 2022. "Distribution system planning considering peak shaving of energy station," Applied Energy, Elsevier, vol. 312(C).
    13. Wang, Yudong & Hu, Junjie, 2023. "Two-stage energy management method of integrated energy system considering pre-transaction behavior of energy service provider and users," Energy, Elsevier, vol. 271(C).

    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. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China," Energy, Elsevier, vol. 228(C).
    2. Wu, Qiong & Xie, Zhun & Ren, Hongbo & Li, Qifen & Yang, Yongwen, 2022. "Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study," Energy, Elsevier, vol. 254(PC).
    3. Zhu, Yilin & Xu, Yujie & Chen, Haisheng & Guo, Huan & Zhang, Hualiang & Zhou, Xuezhi & Shen, Haotian, 2023. "Optimal dispatch of a novel integrated energy system combined with multi-output organic Rankine cycle and hybrid energy storage," Applied Energy, Elsevier, vol. 343(C).
    4. Wang, Shouxiang & Wang, Shaomin & Zhao, Qianyu & Dong, Shuai & Li, Hao, 2023. "Optimal dispatch of integrated energy station considering carbon capture and hydrogen demand," Energy, Elsevier, vol. 269(C).
    5. Pu, Yuchen & Li, Qi & Zou, Xueli & Li, Ruirui & Li, Luoyi & Chen, Weirong & Liu, Hong, 2021. "Optimal sizing for an integrated energy system considering degradation and seasonal hydrogen storage," Applied Energy, Elsevier, vol. 302(C).
    6. Nemanja Mišljenović & Matej Žnidarec & Goran Knežević & Damir Šljivac & Andreas Sumper, 2023. "A Review of Energy Management Systems and Organizational Structures of Prosumers," Energies, MDPI, vol. 16(7), pages 1-32, March.
    7. Chen, Changming & Wu, Xueyan & Li, Yan & Zhu, Xiaojun & Li, Zesen & Ma, Jien & Qiu, Weiqiang & Liu, Chang & Lin, Zhenzhi & Yang, Li & Wang, Qin & Ding, Yi, 2021. "Distributionally robust day-ahead scheduling of park-level integrated energy system considering generalized energy storages," Applied Energy, Elsevier, vol. 302(C).
    8. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
    9. Wang, Ni & Liu, Ziyi & Heijnen, Petra & Warnier, Martijn, 2022. "A peer-to-peer market mechanism incorporating multi-energy coupling and cooperative behaviors," Applied Energy, Elsevier, vol. 311(C).
    10. Li, Peng & Wang, Zixuan & Wang, Jiahao & Yang, Weihong & Guo, Tianyu & Yin, Yunxing, 2021. "Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response," Energy, Elsevier, vol. 225(C).
    11. Yang, Hangbo & You, Pengcheng & Shang, Ce, 2021. "Distributed planning of electricity and natural gas networks and energy hubs," Applied Energy, Elsevier, vol. 282(PA).
    12. Yang, Dechang & Wang, Ming & Yang, Ruiqi & Zheng, Yingying & Pandzic, Hrvoje, 2021. "Optimal dispatching of an energy system with integrated compressed air energy storage and demand response," Energy, Elsevier, vol. 234(C).
    13. Zhang, Han & Han, Zhonghe & Wu, Di & Li, Peng & Li, Peng, 2023. "Energy optimization and performance analysis of a novel integrated energy system coupled with solar thermal unit and preheated organic cycle under extended following electric load strategy," Energy, Elsevier, vol. 272(C).
    14. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    15. Montuori, Lina & Alcázar-Ortega, Manuel, 2021. "Demand response strategies for the balancing of natural gas systems: Application to a local network located in The Marches (Italy)," Energy, Elsevier, vol. 225(C).
    16. Yin, Linfei & Zhang, Bin, 2023. "Relaxed deep generative adversarial networks for real-time economic smart generation dispatch and control of integrated energy systems," Applied Energy, Elsevier, vol. 330(PA).
    17. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    18. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    19. Li, Bo & Li, Xu & Su, Qingyu, 2022. "A system and game strategy for the isolated island electric-gas deeply coupled energy network," Applied Energy, Elsevier, vol. 306(PA).
    20. Li, Shenglin & Zhu, Jizhong & Chen, Ziyu & Luo, Tengyan, 2021. "Double-layer energy management system based on energy sharing cloud for virtual residential microgrid," Applied Energy, Elsevier, vol. 282(PA).

    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:285:y:2021:i:c:s0306261921000258. 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.