IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v243y2022ics0360544222000184.html
   My bibliography  Save this article

A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system

Author

Listed:
  • Liu, Fang
  • Mo, Qiu
  • Yang, Yongwen
  • Li, Pai
  • Wang, Shuai
  • Xu, Yanping

Abstract

In this study, a nonlinear model-based dynamic optimal coordinated scheduling strategy was developed for a grid-connected integrated energy microgrid on a university campus. This integrated energy system (IES) consists of power grid, photovoltaic/wind power generator, buildings, electric batteries, and heat pumps with thermal energy storages (HPTES). Peak load shifting index, a new indicator, is proposed for evaluating the capability of energy storages for peak-shaving and valley-filling of the grid power and thermal load, and the stability of the power grid with renewables. Comparison of the performances of IES under three scenarios shows that through adopting high-efficient HPTES together with an optimal coordinated scheduling strategy, the penetration rate of renewable energy and the stability of IES can be enhanced significantly; while the operation cost, peak power, grid interactive power, peak load shifting index and CO2 emissions can be reduced significantly. Moreover, compared with the optimal scheduling strategy previously developed based on a linear model, the optimal scheduling strategy developed based on a dynamic nonlinear model can help to reduce the grid-connected time of the IES containing HPTES. This study would be useful for increasing the penetration rate of renewables and the stability of grid, as well as reducing the grid-disconnected time of an IES at a low operation cost in practice.

Suggested Citation

  • Liu, Fang & Mo, Qiu & Yang, Yongwen & Li, Pai & Wang, Shuai & Xu, Yanping, 2022. "A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system," Energy, Elsevier, vol. 243(C).
  • Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544222000184
    DOI: 10.1016/j.energy.2022.123115
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222000184
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.123115?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. Hesaraki, Arefeh & Holmberg, Sture & Haghighat, Fariborz, 2015. "Seasonal thermal energy storage with heat pumps and low temperatures in building projects—A comparative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1199-1213.
    2. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    3. Deo, Ravinesh C. & Şahin, Mehmet, 2017. "Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 828-848.
    4. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    5. Petrollese, Mario & Valverde, Luis & Cocco, Daniele & Cau, Giorgio & Guerra, José, 2016. "Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid," Applied Energy, Elsevier, vol. 166(C), pages 96-106.
    6. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    7. Mansoor, Muhammad & Stadler, Michael & Zellinger, Michael & Lichtenegger, Klaus & Auer, Hans & Cosic, Armin, 2021. "Optimal planning of thermal energy systems in a microgrid with seasonal storage and piecewise affine cost functions," Energy, Elsevier, vol. 215(PA).
    8. 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.
    9. Rech, S. & Lazzaretto, A., 2018. "Smart rules and thermal, electric and hydro storages for the optimum operation of a renewable energy system," Energy, Elsevier, vol. 147(C), pages 742-756.
    10. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
    11. Lu, Yuehong & Wang, Shengwei & Sun, Yongjun & Yan, Chengchu, 2015. "Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming," Applied Energy, Elsevier, vol. 147(C), pages 49-58.
    12. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    13. Li, Zhengmao & Xu, Yan, 2019. "Temporally-coordinated optimal operation of a multi-energy microgrid under diverse uncertainties," Applied Energy, Elsevier, vol. 240(C), pages 719-729.
    14. Renaldi, R. & Kiprakis, A. & Friedrich, D., 2017. "An optimisation framework for thermal energy storage integration in a residential heat pump heating system," Applied Energy, Elsevier, vol. 186(P3), pages 520-529.
    15. 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).
    16. Mazzoni, Stefano & Ooi, Sean & Nastasi, Benedetto & Romagnoli, Alessandro, 2019. "Energy storage technologies as techno-economic parameters for master-planning and optimal dispatch in smart multi energy systems," Applied Energy, Elsevier, vol. 254(C).
    17. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    18. Baeten, Brecht & Rogiers, Frederik & Helsen, Lieve, 2017. "Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response," Applied Energy, Elsevier, vol. 195(C), pages 184-195.
    19. Moghaddam, Iman Gerami & Saniei, Mohsen & Mashhour, Elaheh, 2016. "A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building," Energy, Elsevier, vol. 94(C), pages 157-170.
    20. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
    21. Zhang, Yan & Meng, Fanlin & Wang, Rui & Kazemtabrizi, Behzad & Shi, Jianmai, 2019. "Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid," Energy, Elsevier, vol. 179(C), pages 1265-1278.
    22. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).
    23. Fischer, David & Madani, Hatef, 2017. "On heat pumps in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 342-357.
    24. Talaat, M. & Farahat, M.A. & Elkholy, M.H., 2019. "Renewable power integration: Experimental and simulation study to investigate the ability of integrating wave, solar and wind energies," Energy, Elsevier, vol. 170(C), pages 668-682.
    25. Vorushylo, Inna & Keatley, Patrick & Shah, Nikhilkumar & Green, Richard & Hewitt, Neil, 2018. "How heat pumps and thermal energy storage can be used to manage wind power: A study of Ireland," Energy, Elsevier, vol. 157(C), pages 539-549.
    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. Liu, Fang & Mo, Qiu & Zhao, Xudong, 2023. "Two-level optimal scheduling method for a renewable microgrid considering charging performances of heat pump with thermal storages," Renewable Energy, Elsevier, vol. 203(C), pages 102-112.
    2. Wang, Kaiwen & Tong, Lige & Yin, Shaowu & Yang, Yan & Zhang, Peikun & Liu, Chuanping & Zuo, Zhongqi & Wang, Li & Ding, Yulong, 2024. "Novel ASU–LAES system with flexible energy release: Analysis of cycle performance, economics, and peak shaving advantages," Energy, Elsevier, vol. 288(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. Liu, Fang & Mo, Qiu & Zhao, Xudong, 2023. "Two-level optimal scheduling method for a renewable microgrid considering charging performances of heat pump with thermal storages," Renewable Energy, Elsevier, vol. 203(C), pages 102-112.
    2. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    3. Zheng, Lingwei & Zhou, Xingqiu & Qiu, Qi & Yang, Lan, 2020. "Day-ahead optimal dispatch of an integrated energy system considering time-frequency characteristics of renewable energy source output," Energy, Elsevier, vol. 209(C).
    4. Omais Abdur Rehman & Valeria Palomba & Andrea Frazzica & Luisa F. Cabeza, 2021. "Enabling Technologies for Sector Coupling: A Review on the Role of Heat Pumps and Thermal Energy Storage," Energies, MDPI, vol. 14(24), pages 1-30, December.
    5. Aguilera, José Joaquín & Meesenburg, Wiebke & Ommen, Torben & Markussen, Wiebke Brix & Poulsen, Jonas Lundsted & Zühlsdorf, Benjamin & Elmegaard, Brian, 2022. "A review of common faults in large-scale heat pumps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    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. Matthias Eydner & Lu Wan & Tobias Henzler & Konstantinos Stergiaropoulos, 2022. "Real-Time Grid Signal-Based Energy Flexibility of Heating Generation: A Methodology for Optimal Scheduling of Stratified Storage Tanks," Energies, MDPI, vol. 15(5), pages 1-31, February.
    8. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    9. Walden, Jasper V.M. & Bähr, Martin & Glade, Anselm & Gollasch, Jens & Tran, A. Phong & Lorenz, Tom, 2023. "Nonlinear operational optimization of an industrial power-to-heat system with a high temperature heat pump, a thermal energy storage and wind energy," Applied Energy, Elsevier, vol. 344(C).
    10. White, Philip R. & Rhodes, Joshua D. & Wilson, Eric J.H. & Webber, Michael E., 2021. "Quantifying the impact of residential space heating electrification on the Texas electric grid," Applied Energy, Elsevier, vol. 298(C).
    11. Lingmin, Chen & Jiekang, Wu & Fan, Wu & Huiling, Tang & Changjie, Li & Yan, Xiong, 2020. "Energy flow optimization method for multi-energy system oriented to combined cooling, heating and power," Energy, Elsevier, vol. 211(C).
    12. Alessandro Franco & Carlo Bartoli & Paolo Conti & Daniele Testi, 2021. "Optimal Operation of Low-Capacity Heat Pump Systems for Residential Buildings through Thermal Energy Storage," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    13. Hong-Hai Niu & Yang Zhao & Shang-Shang Wei & Yi-Guo Li, 2021. "A Variable Performance Parameters Temperature–Flowrate Scheduling Model for Integrated Energy Systems," Energies, MDPI, vol. 14(17), pages 1-25, August.
    14. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).
    15. Diana Enescu & Gianfranco Chicco & Radu Porumb & George Seritan, 2020. "Thermal Energy Storage for Grid Applications: Current Status and Emerging Trends," Energies, MDPI, vol. 13(2), pages 1-21, January.
    16. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2021. "Robust design optimization of a photovoltaic-battery-heat pump system with thermal storage under aleatory and epistemic uncertainty," Energy, Elsevier, vol. 229(C).
    17. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    18. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    19. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    20. 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).

    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:energy:v:243:y:2022:i:c:s0360544222000184. 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.journals.elsevier.com/energy .

    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.