IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v246y2022ics0360544222003322.html
   My bibliography  Save this article

Optimal configuration and operation analysis of solar-assisted natural gas distributed energy system with energy storage

Author

Listed:
  • Ge, Yi
  • Han, Jitian
  • Ma, Qingzhao
  • Feng, Jiahui

Abstract

A solar-assisted natural gas distributed energy system (DES) with energy storage is proposed to determine the optimal configuration of the DES in this study. A mixed-integer nonlinear programming (MINLP) model is established considering the part-load performances of devices and the annual total cost (ATC) as objective. Taking an energy center in Jinan, China as the objective building, three scenarios of different structural DESs are designed in which different candidate devices of a certain type of equipment are listed, and the optimal configurations and the energy management strategies are studied. The results show that in comparison with the conventional DES (Scenario 1), the ATCs of the DES with solar energy (Scenario 2) and the solar-assisted natural gas DES with energy storage (Scenario 3) are decreased by 2.90% and 7.48%. The economy and flexibility of the power grid is verified to regulating the electrical load of DES. The sensitivities of the DES to energy price changes are analyzed and the DES is more sensitive to the natural gas price under the research ranges. The model and method can be applied to practical engineering and give guidance on device operation.

Suggested Citation

  • Ge, Yi & Han, Jitian & Ma, Qingzhao & Feng, Jiahui, 2022. "Optimal configuration and operation analysis of solar-assisted natural gas distributed energy system with energy storage," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222003322
    DOI: 10.1016/j.energy.2022.123429
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222003322
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123429?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, Mingxi & Shi, Yang & Fang, Fang, 2014. "Combined cooling, heating and power systems: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 1-22.
    2. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    3. Biglarian, Hassan & Abbaspour, Madjid & Saidi, Mohammad Hassan, 2018. "Evaluation of a transient borehole heat exchanger model in dynamic simulation of a ground source heat pump system," Energy, Elsevier, vol. 147(C), pages 81-93.
    4. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    5. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    6. Ma, Linwei & Liu, Pei & Fu, Feng & Li, Zheng & Ni, Weidou, 2011. "Integrated energy strategy for the sustainable development of China," Energy, Elsevier, vol. 36(2), pages 1143-1154.
    7. Kopanos, Georgios M. & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "Energy production planning of a network of micro combined heat and power generators," Applied Energy, Elsevier, vol. 102(C), pages 1522-1534.
    8. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    9. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2017. "Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation," Applied Energy, Elsevier, vol. 205(C), pages 1244-1259.
    10. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    11. Kim, Jong Suk & Edgar, Thomas F., 2014. "Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming," Energy, Elsevier, vol. 77(C), pages 675-690.
    12. Rong, Aiying & Lahdelma, Risto, 2005. "An efficient linear programming model and optimization algorithm for trigeneration," Applied Energy, Elsevier, vol. 82(1), pages 40-63, September.
    13. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    14. Yan, Bofeng & Xue, Song & Li, Yuanfei & Duan, Jinhui & Zeng, Ming, 2016. "Gas-fired combined cooling, heating and power (CCHP) in Beijing: A techno-economic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 118-131.
    15. Marzband, Mousa & Sumper, Andreas & Ruiz-Álvarez, Albert & Domínguez-García, José Luis & Tomoiagă, Bogdan, 2013. "Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets," Applied Energy, Elsevier, vol. 106(C), pages 365-376.
    16. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    17. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2018. "Optimal sizing of distributed generation in gas/electricity/heat supply networks," Energy, Elsevier, vol. 151(C), pages 675-688.
    18. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    19. Wang, Jiangjiang & Yang, Ying & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Life cycle assessment (LCA) optimization of solar-assisted hybrid CCHP system," Applied Energy, Elsevier, vol. 146(C), pages 38-52.
    20. Wu, Jing-yi & Wang, Jia-long & Li, Sheng, 2012. "Multi-objective optimal operation strategy study of micro-CCHP system," Energy, Elsevier, vol. 48(1), pages 472-483.
    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. Huang, Z.F. & Chen, W.D. & Wan, Y.D. & Shao, Y.L. & Islam, M.R. & Chua, K.J., 2024. "Techno-economic comparison of different energy storage configurations for renewable energy combined cooling heating and power system," Applied Energy, Elsevier, vol. 356(C).
    2. Zhu, Xiaoxuan & Wang, Peng & Zhang, Hui & Wang, Shiqiang & Xv, Shuaiquan & Liu, Hailong & Zhang, Yihua & Zhao, Dong & Han, Jitian, 2024. "A highly efficient, low-carbon CCHP system and its comprehensive optimization for an integrated medical and nursing complex," Renewable Energy, Elsevier, vol. 227(C).
    3. Li, Yuxin & Wang, Jiangjiang & Zhou, Yuan & Wei, Changqi & Guan, Zhimin & Chen, Haiyue, 2023. "Multi-dimension day-ahead scheduling optimization of a community-scale solar-driven CCHP system with demand-side management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    4. Li, Jinyu & Yang, Zhengda & Ge, Yi & Wang, Yiya & Dong, Qiwei & Wang, Xinwei & Lin, Riyi, 2024. "Performance study of photovoltaic-thermochemical hybrid system with Cassegrain concentrator and spectral splitting integration," Energy, Elsevier, vol. 292(C).
    5. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(C).
    6. Yang, Lihua & Wu, Xiao, 2024. "Net-zero carbon configuration approach for direct air carbon capture based integrated energy system considering dynamic characteristics of CO2 adsorption and desorption," Applied Energy, Elsevier, vol. 358(C).
    7. Akulker, Handan & Aydin, Erdal, 2023. "Optimal design and operation of a multi-energy microgrid using mixed-integer nonlinear programming: Impact of carbon cap and trade system and taxing on equipment selections," Applied Energy, Elsevier, vol. 330(PA).
    8. Zhou, Yuan & Wang, Jiangjiang & Li, Yuxin & Wei, Changqi, 2023. "A collaborative management strategy for multi-objective optimization of sustainable distributed energy system considering cloud energy storage," Energy, Elsevier, vol. 280(C).
    9. Pengying Wang & Shuo Zhang & Limei Chen, 2023. "Research on the Integration of a Natural Gas-Distributed Energy System into the Oilfield Facility in China," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    10. Li, Jinyu & Yang, Zhengda & Wang, Yiya & Dong, Qiwei & Qi, Shitao & Huang, Chenxing & Wang, Xinwei & Lin, Riyi, 2023. "A novel non-confocal two-stage dish concentrating photovoltaic/thermal hybrid system utilizing spectral beam splitting technology: Optical and thermal performance investigations," Renewable Energy, Elsevier, vol. 206(C), pages 609-622.

    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. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    2. Zhang, Na & Wang, Zefeng & Lior, Noam & Han, Wei, 2018. "Advancement of distributed energy methods by a novel high efficiency solar-assisted combined cooling, heating and power system," Applied Energy, Elsevier, vol. 219(C), pages 179-186.
    3. Ma, Tengfei & Wu, Junyong & Hao, Liangliang & Lee, Wei-Jen & Yan, Huaguang & Li, Dezhi, 2018. "The optimal structure planning and energy management strategies of smart multi energy systems," Energy, Elsevier, vol. 160(C), pages 122-141.
    4. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    5. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2018. "Effect of load following strategies, hardware, and thermal load distribution on stand-alone hybrid CCHP systems," Applied Energy, Elsevier, vol. 220(C), pages 735-753.
    6. Gao, Lei & Hwang, Yunho & Cao, Tao, 2019. "An overview of optimization technologies applied in combined cooling, heating and power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    7. 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.
    8. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    9. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    10. Zhigang Duan & Yamin Yan & Xiaohan Yan & Qi Liao & Wan Zhang & Yongtu Liang & Tianqi Xia, 2017. "An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand," Energies, MDPI, vol. 11(1), pages 1-23, December.
    11. 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.
    12. Xin Zhao & Yanqi Chen & Gang Xu & Heng Chen, 2022. "Economic Assessment of Operation Strategies on Park-Level Integrated Energy System Coupled with Biogas: A Case Study in a Sewage Treatment Plant," Energies, MDPI, vol. 16(1), pages 1-21, December.
    13. Obara, Shin’ya & Morizane, Yuta & Morel, Jorge, 2013. "Study on method of electricity and heat storage planning based on energy demand and tidal flow velocity forecasts for a tidal microgrid," Applied Energy, Elsevier, vol. 111(C), pages 358-373.
    14. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    15. Afzali, Sayyed Faridoddin & Cotton, James S. & Mahalec, Vladimir, 2020. "Urban community energy systems design under uncertainty for specified levels of carbon dioxide emissions," Applied Energy, Elsevier, vol. 259(C).
    16. Cao, Tao & Hwang, Yunho & Radermacher, Reinhard, 2017. "Development of an optimization based design framework for microgrid energy systems," Energy, Elsevier, vol. 140(P1), pages 340-351.
    17. Chen, Yuzhu & Hua, Huilian & Xu, Jinzhao & Yun, Zhonghua & Wang, Jun & Lund, Peter D., 2022. "Techno-economic cost assessment of a combined cooling heating and power system coupled to organic Rankine cycle with life cycle method," Energy, Elsevier, vol. 239(PA).
    18. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    19. Liting Zhang & Weijun Gao & Yongwen Yang & Fanyue Qian, 2020. "Impacts of Investment Cost, Energy Prices and Carbon Tax on Promoting the Combined Cooling, Heating and Power (CCHP) System of an Amusement Park Resort in Shanghai," Energies, MDPI, vol. 13(16), pages 1-22, August.
    20. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhai, Zhiqiang (John), 2011. "Performance comparison of combined cooling heating and power system in different operation modes," Applied Energy, Elsevier, vol. 88(12), pages 4621-4631.

    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:246:y:2022:i:c:s0360544222003322. 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.