IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v327y2022ics030626192201412x.html
   My bibliography  Save this article

A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response

Author

Listed:
  • Ju, Liwei
  • Lu, Xiaolong
  • Yang, Shenbo
  • Li, Gen
  • Fan, Wei
  • Pan, Yushu
  • Qiao, Huiting

Abstract

Aiming at utilizing straw, garbage, domestic sewage and other biomass waste resources in rural areas, this study designed a rural biomass wastes energy conversion system (BWs)-based micro energy grid (BWs-MEG), and the mathematical modeling of BWs-MEG is carried out including multi-energy transforms system (METS) and multi-energy demand response (MEDR). Then, a two-stage optimal framework for rural BWs-MEG multi-time scale dispatching is designed. In the day-ahead stage, a multi-objective dispatching optimal model was constructed with the objectives of minimum operating costs and maximum eco-environment benefits. In the intra-day stage, the robust optimization theory was utilized to characterize the uncertainties of wind power plant (WPP) and photovoltaic power generation (PV) and a rolling dispatching optimal model was constructed with the objective of minimum deviation costs. After that, the above dispatching model was fuzzified and linearized, and then converted into a mixed integer linear programming model. Finally, a micro-energy grid in northern China was selected as an example for case study. The results showed: (1) BWs can utilize rural biomass waste resources for pyrolysis power generation (PG) and gas production to achieve energy utilization and provide power, heating and gas output. In the islanded operation mode and grid-connected operation mode, when MEG is configured with BWs, the deviation costs decrease by 25.6 % and 26.33 %, while the operating costs increases only by 7.60 % and 13.52 %, respectively. The power output of WPP and PV increase by 1.03 % and 2.19 % in the grid-connected operation mode, indicating that BWs is conducive to realizing the multi-dimension supply and demand balance of power, heating and gas loads. (2) Multi-time scale dispatching model can give play to the regulation ability of BWs, METS and MEDR and connect the day-ahead dispatching plan with the intra-day dispatching strategy to formulate the optimal dispatching strategy. When there is deviation in the day-ahead dispatching strategy, METS and MEDR could maintain the supply and demand balance of power load. AHP can change the heating period and BWs could maintain the supply and balance of heating and gas loads. Compared with the day-ahead dispatching plan, the output of PG and power-to-gas device in intra-day dispatching strategy increase by 21.22 % and 9.78 %. (3) Robust stochastic optimization method can characterize the uncertainties of WPP and PV and formulate the dispatching decision schemes with different risk attitudes. With the robust coefficient Г increasing, MEG operating costs and eco-environment benefits increase and deviation adjustment costs decreases, but the robustness of the dispatching scheme is improved. When 0.25≤Г≤0.75, the increase of the uncertainty parameter will have a direct impact on the formulation of dispatching scheme. And the decision maker belongs to risk preference type, who is willing to take certain risks to win excess benefits. Besides, if MEG operates in the grid-connected mode, the uncertainty risks will be weakened and the operation mode shall be reasonably selected according to the demand for dispatching decision. Overall, the proposed optimization model can promote the energy utilization of rural biomass waste resources, which is conducive to the realization of a clean and low-carbon transformation of the overall energy structure.

Suggested Citation

  • Ju, Liwei & Lu, Xiaolong & Yang, Shenbo & Li, Gen & Fan, Wei & Pan, Yushu & Qiao, Huiting, 2022. "A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response," Applied Energy, Elsevier, vol. 327(C).
    • Handle: RePEc:eee:appene:v:327:y:2022:i:c:s030626192201412x
    DOI: 10.1016/j.apenergy.2022.120155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192201412X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120155?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. Chen, Yusheng & Standl, Phillip & Weiker, Sebastian & Gaderer, Matthias, 2022. "A general approach to integrating compression heat pumps into biomass heating networks for heat recovery," Applied Energy, Elsevier, vol. 310(C).
    2. Ju, Liwei & Wu, Jing & Lin, Hongyu & Tan, Qinliang & Li, Gen & Tan, Zhongfu & Li, Jiayu, 2020. "Robust purchase and sale transactions optimization strategy for electricity retailers with energy storage system considering two-stage demand response," Applied Energy, Elsevier, vol. 271(C).
    3. Wang, Shubin & Sun, Shaolong & Zhao, Erlong & Wang, Shouyang, 2021. "Urban and rural differences with regional assessment of household energy consumption in China," Energy, Elsevier, vol. 232(C).
    4. De Lorenzi, Andrea & Gambarotta, Agostino & Marzi, Emanuela & Morini, Mirko & Saletti, Costanza, 2022. "Predictive control of a combined heat and power plant for grid flexibility under demand uncertainty," Applied Energy, Elsevier, vol. 314(C).
    5. Sun, Qie & Fu, Yu & Lin, Haiyang & Wennersten, Ronald, 2022. "A novel integrated stochastic programming-information gap decision theory (IGDT) approach for optimization of integrated energy systems (IESs) with multiple uncertainties," Applied Energy, Elsevier, vol. 314(C).
    6. Yang, Qiangda & Liu, Peng & Zhang, Jie & Dong, Ning, 2022. "Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation," Applied Energy, Elsevier, vol. 307(C).
    7. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
    8. Galimshina, Alina & Moustapha, Maliki & Hollberg, Alexander & Padey, Pierryves & Lasvaux, Sébastien & Sudret, Bruno & Habert, Guillaume, 2022. "Bio-based materials as a robust solution for building renovation: A case study," Applied Energy, Elsevier, vol. 316(C).
    9. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic programming and market equilibrium analysis of microgrids energy management systems," Energy, Elsevier, vol. 113(C), pages 662-670.
    10. Han, Dongho & Lee, Jay H., 2021. "Two-stage stochastic programming formulation for optimal design and operation of multi-microgrid system using data-based modeling of renewable energy sources," Applied Energy, Elsevier, vol. 291(C).
    11. Yang, Hanyu & Dou, Xun & Pan, Feng & Wu, Qiuwei & Li, Canbing & Zhou, Bin & Hao, Lili, 2022. "Optimal planning of local biomass-based integrated energy system considering anaerobic co-digestion," Applied Energy, Elsevier, vol. 316(C).
    12. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    13. Wang, Jiangjiang & Ma, Chaofan & Wu, Jing, 2019. "Thermodynamic analysis of a combined cooling, heating and power system based on solar thermal biomass gasification☆," Applied Energy, Elsevier, vol. 247(C), pages 102-115.
    14. Wu, Zitao & Zhai, Haibo, 2021. "Consumptive life cycle water use of biomass-to-power plants with carbon capture and sequestration," Applied Energy, Elsevier, vol. 303(C).
    15. Zheng, Bingle & Wu, Xiao, 2022. "Integrated capacity configuration and control optimization of off-grid multiple energy system for transient performance improvement," Applied Energy, Elsevier, vol. 311(C).
    16. Wu, Zhen & Zhu, Pengfei & Yao, Jing & Zhang, Shengan & Ren, Jianwei & Yang, Fusheng & Zhang, Zaoxiao, 2020. "Combined biomass gasification, SOFC, IC engine, and waste heat recovery system for power and heat generation: Energy, exergy, exergoeconomic, environmental (4E) evaluations," Applied Energy, Elsevier, vol. 279(C).
    17. An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(C).
    18. Ju, Liwei & Tan, Qinliang & Lin, Hongyu & Mei, Shufang & Li, Nan & Lu, Yan & Wang, Yao, 2020. "A two-stage optimal coordinated scheduling strategy for micro energy grid integrating intermittent renewable energy sources considering multi-energy flexible conversion," Energy, Elsevier, vol. 196(C).
    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. Ju, Liwei & Liu, Li & Han, Yingzhu & Yang, Shenbo & Li, Gen & Lu, Xiaolong & Liu, Yi & Qiao, Huiting, 2023. "Robust Multi-objective optimal dispatching model for a novel island micro energy grid incorporating biomass waste energy conversion system, desalination and power-to-hydrogen devices," Applied Energy, Elsevier, vol. 343(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. Ju, Liwei & Liu, Li & Han, Yingzhu & Yang, Shenbo & Li, Gen & Lu, Xiaolong & Liu, Yi & Qiao, Huiting, 2023. "Robust Multi-objective optimal dispatching model for a novel island micro energy grid incorporating biomass waste energy conversion system, desalination and power-to-hydrogen devices," Applied Energy, Elsevier, vol. 343(C).
    2. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    3. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
    4. Hang Liu & Yongcheng Wang & Shilin Nie & Yi Wang & Yu Chen, 2022. "Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
    5. Yuan, Yu & Bai, Zhang & Liu, Qibin & Hu, Wenxin & Zheng, Bo, 2021. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Route of enhancing the operation flexibility," Applied Energy, Elsevier, vol. 301(C).
    6. Wu, Qunli & Li, Chunxiang, 2023. "Modeling and operation optimization of hydrogen-based integrated energy system with refined power-to-gas and carbon-capture-storage technologies under carbon trading," Energy, Elsevier, vol. 270(C).
    7. Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    8. József Magyari & Krisztina Hegedüs & Botond Sinóros-Szabó, 2022. "Integration Opportunities of Power-to-Gas and Internet-of-Things Technical Advancements: A Systematic Literature Review," Energies, MDPI, vol. 15(19), pages 1-19, September.
    9. Ju, Liwei & Tan, Qinliang & Lin, Hongyu & Mei, Shufang & Li, Nan & Lu, Yan & Wang, Yao, 2020. "A two-stage optimal coordinated scheduling strategy for micro energy grid integrating intermittent renewable energy sources considering multi-energy flexible conversion," Energy, Elsevier, vol. 196(C).
    10. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    11. Nyong-Bassey, Bassey Etim & Giaouris, Damian & Patsios, Charalampos & Papadopoulou, Simira & Papadopoulos, Athanasios I. & Walker, Sara & Voutetakis, Spyros & Seferlis, Panos & Gadoue, Shady, 2020. "Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty," Energy, Elsevier, vol. 193(C).
    12. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    13. Zhao, Xinyue & Chen, Heng & Zheng, Qiwei & Liu, Jun & Pan, Peiyuan & Xu, Gang & Zhao, Qinxin & Jiang, Xue, 2023. "Thermo-economic analysis of a novel hydrogen production system using medical waste and biogas with zero carbon emission," Energy, Elsevier, vol. 265(C).
    14. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    15. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    16. Chen, Yizhong & He, Li & Li, Jing, 2017. "Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty," Energy, Elsevier, vol. 130(C), pages 581-598.
    17. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Dai, Guyu & Chai, Jianxue, 2022. "Cost compensation method for PEVs participating in dynamic economic dispatch based on carbon trading mechanism," Energy, Elsevier, vol. 239(PA).
    18. Sheng, Wanxing & Li, Rui & Yan, Tao & Tseng, Ming-Lang & Lou, Jiale & Li, Lingling, 2023. "A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm," Renewable Energy, Elsevier, vol. 204(C), pages 493-506.
    19. Hu, Haowen & Ou, Kai & Yuan, Wei-Wei, 2023. "Fused multi-model predictive control with adaptive compensation for proton exchange membrane fuel cell air supply system," Energy, Elsevier, vol. 284(C).
    20. Ebrahimi-Moghadam, Amir & Farzaneh-Gord, Mahmood, 2022. "Optimal operation of a multi-generation district energy hub based on electrical, heating, and cooling demands and hydrogen production," Applied Energy, Elsevier, vol. 309(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:appene:v:327:y:2022:i:c:s030626192201412x. 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.